Work with thought leaders and academic experts in computer science applications

Companies can benefit from collaborating with academic researchers in Computer Science Applications in several ways. These researchers have deep knowledge and expertise in areas such as artificial intelligence, data analysis, software development, and more. By working with them, companies can drive innovation, solve complex problems, and stay ahead of the competition. Researchers can provide valuable insights and solutions to optimize business processes, develop cutting-edge technologies, and improve customer experiences. They can also help companies leverage big data and implement machine learning algorithms to gain actionable insights and make data-driven decisions. Additionally, academic researchers can assist in developing secure and robust software systems, ensuring the company's technology infrastructure is efficient and protected.

Experts on NotedSource with backgrounds in computer science applications include Keiran Thompson, Christos Makridis, Daniel Milej, Ph.D., Tim Osswald, Elle Wang, Serena Booth, Jo Boaler, Jeffrey Townsend, Edoardo Airoldi, Ryan Howell, Emmanouil Mentzakis, Konstantinos Tsavdaridis, Suhang Wang, Mengying Li, Osaye Fadekemi, PhD, Mark Ryan, Anna Jobin, Anindya Ghose, ARNOLD RAYMOND, Elizabeth Groff, Dan Baack, Weijun Luo, Ph.D., Steve Joordens, Ping Luo, Trina Fletcher, Ph.D., Athul Prasad, Dr Abiodun Alao, Ariel Aptekmann, Ludovica Cesareo, Panos Ipeirotis, Amber Bartosh, Deep Jariwala, Jiang Wang, Nima Ziraknejad, Robert Gitter, Ph.D., Dr. Abdussalam Elhanashi, Samiul Amin, Asst. Prof. Eng. Davide Verzotto, Ph.D., Bernd Stahl, Christophe Schinckus, Ramy Ayoub, Sina Soleymani, Dr. Sandeep Aashish, Hendrik Wolff, Kayvan Najarian, Bianca Trinkenreich, Marc St-Pierre, Paul Schrater, Gianfranco Santovito, Muhammad Shahbaz, Daniel Greenfield, Upavan Gupta, Ph.D., Patrick Reeson, Ernesto Lowy, Jonathan Tamir, Vartika Bisht, Niko Popitsch, John Joe, Tania Lorido, and Dr. Wen Cebuhar, PhD.

Keiran Thompson

Palo Alto, California, United States of America
Stanford University
Most Relevant Research Interests
Computer Science Applications
Other Research Interests (19)
Artificial Intelligence
Machine Learning
Numerical Computing
Quantitative Analysis (Finance)
Quantum Chemistry
And 14 more
About
Keiran Thompson is a machine learning and quantum chemistry researcher. Originally from Australia, he currently works as an AI research scientist at Stanford University where he transfers machine learning knowledge from the private sector to academic research which can then be reconverted back to private sector usage. He is experienced with large scale numerical computing and has led several startups as Chief Scientist.
Most Relevant Publications (2+)

30 total publications

Large-Scale Functional Group Symmetry-Adapted Perturbation Theory on Graphical Processing Units

Journal of Chemical Theory and Computation / Jan 18, 2018

Parrish, R. M., Thompson, K. C., & Martínez, T. J. (2018). Large-Scale Functional Group Symmetry-Adapted Perturbation Theory on Graphical Processing Units. Journal of Chemical Theory and Computation, 14(3), 1737–1753. https://doi.org/10.1021/acs.jctc.7b01053

TeraChem Cloud: A High-Performance Computing Service for Scalable Distributed GPU-Accelerated Electronic Structure Calculations

Journal of Chemical Information and Modeling / Apr 08, 2020

Seritan, S., Thompson, K., & Martínez, T. J. (2020). TeraChem Cloud: A High-Performance Computing Service for Scalable Distributed GPU-Accelerated Electronic Structure Calculations. Journal of Chemical Information and Modeling, 60(4), 2126–2137. https://doi.org/10.1021/acs.jcim.9b01152

Christos Makridis

Nashville, TN
Web3 and Labor Economist in Academia, Entrepreneurship, and Policy
Most Relevant Research Interests
Computer Science Applications
Other Research Interests (29)
Web3
Crypto
Blockchain
Fine art
Opera
And 24 more
About
Christos A. Makridis holds academic appointments at Columbia Business School, Stanford University, Baylor University, University of Nicosia, and Arizona State University. He is also an adjunct scholar at the Manhattan Institute, senior adviser at Gallup, and senior adviser at the National AI Institute in the Department of Veterans Affairs. Christos is the CEO/co-founder of [Dainamic](https://www.dainamic.ai/), a technology startup working to democratize the use and application of data science and AI techniques for small and mid sized organizations, and CTO/co-founder of [Living Opera](https://www.livingopera.org/), a web3 startup working to bridge classical music and blockchain technologies. Christos previously served on the White House Council of Economic Advisers managing the cybersecurity, technology, and space activities, as a Non-resident Fellow at the Cyber Security Project in the Harvard Kennedy School of Government, as a Digital Fellow at the Initiative at the Digital Economy in the MIT Sloan School of Management, a a Non-resident Research Scientist at Datacamp, and as a Visiting Fellow at the Foundation for Defense of Democracies. Christos’ primary academic research focuses on labor economics, the digital economy, and personal finance and well-being. He has published over 70 peer-reviewed research papers in academic journals and over 170 news articles in the press. Christos earned a Bachelor’s in Economics and Minor in Mathematics at Arizona State University, as well a dual Masters and PhDs in Economics and Management Science & Engineering at Stanford University.
Most Relevant Publications (2+)

25 total publications

Leveraging machine learning to characterize the role of socio-economic determinants on physical health and well-being among veterans

Computers in Biology and Medicine / Jun 01, 2021

Makridis, C. A., Zhao, D. Y., Bejan, C. A., & Alterovitz, G. (2021). Leveraging machine learning to characterize the role of socio-economic determinants on physical health and well-being among veterans. Computers in Biology and Medicine, 133, 104354. https://doi.org/10.1016/j.compbiomed.2021.104354

Designing COVID-19 mortality predictions to advance clinical outcomes: Evidence from the Department of Veterans Affairs

BMJ Health & Care Informatics / Jun 01, 2021

Makridis, C. A., Strebel, T., Marconi, V., & Alterovitz, G. (2021). Designing COVID-19 mortality predictions to advance clinical outcomes: Evidence from the Department of Veterans Affairs. BMJ Health & Care Informatics, 28(1), e100312. https://doi.org/10.1136/bmjhci-2020-100312

Daniel Milej, Ph.D.

London, Ontario, Canada
Ph.D. in biomedical engineering
Most Relevant Research Interests
Computer Science Applications
Other Research Interests (40)
Biomedical Optics
NIRS
fNIRS
Diffuse Correlation Spectroscopy
CBF
And 35 more
About
Dr. Daniel Milej is a multidisciplinary researcher with experience in medical biophysics, electronics, biocybernetics, biomedical optics and engineering. He is highly knowledgeable and experienced in a range of research techniques. He is currently a Research Associate at the Lawson Health Research Institute, leading the transition of multimodal optical imaging systems from a research setting to clinical use in an ICU and OR environment, working closely with teams of nurses, surgeons, doctors and respiratory therapists. Previously he was a postdoctoral fellow working on developing noninvasive modalities for brain activity monitoring in the Department of Medical Biophysics at Western University. Before that, Dr. Milej worked as a researcher at the Nalecz Institute of Biocybernetics and Biomedical Engineering. He obtained his Ph.D. in 2014 from the Polish Academy of Science, specializing in Electronics and Biomedical Engineering. He received his MSc from the Military University of Technology in 2008.
Most Relevant Publications (1+)

91 total publications

Analysis of estimation of optical properties of sub superficial structures in multi layered tissue model using distribution function method

Computer Methods and Programs in Biomedicine / Jan 01, 2020

Żołek, N., Rix, H., & Botwicz, M. (2020). Analysis of estimation of optical properties of sub superficial structures in multi layered tissue model using distribution function method. Computer Methods and Programs in Biomedicine, 183, 105084. https://doi.org/10.1016/j.cmpb.2019.105084

Tim Osswald

Polymers Professor - University of Wisconsin
Most Relevant Research Interests
Computer Science Applications
Other Research Interests (64)
Polymer and Composites Engineering
Polymer Engineering
Advanced Manufacturing
Composites
Additive Manufacturing
And 59 more
About
T. Osswald is Hoeganaes Professor of Materials at the University of Wisconsin-Madison, where he has been a faculty member since 1989. Osswald received the PhD in Mechanical Engineering from the University of Illinois at Urbana-Champaign in 1987, the MS in Mechanical Engineering from the South Dakota School of Mines and Technology in 1982, and the BS in Mechanical Engineering from the South Dakota School of Mines and Technology in 1981. Before joining the UW-Madison faculty, Osswald was a Humboldt Fellow at the Rheinisch Westfalische Technische Hochschule Aachen. Osswald’s research interests are in the areas of processing-structure-property relationships for metals and composites, with a focus on powder metallurgy and metal injection molding. His research has been supported by the National Science Foundation, the Department of Energy, the US Army Research Office, and industry. Osswald is a Fellow of ASM International and the American Academy of Mechanics, and he has received the Extrusion Division Award, the Powder Metallurgy Division Award, and the Distinguished Teaching Award from TMS.
Most Relevant Publications (2+)

117 total publications

Numerical simulation of three-dimensional viscoelastic planar contraction flow using the software OpenFOAM

Computers & Chemical Engineering / Feb 01, 2012

Holmes, L., Favero, J., & Osswald, T. (2012). Numerical simulation of three-dimensional viscoelastic planar contraction flow using the software OpenFOAM. Computers & Chemical Engineering, 37, 64–73. https://doi.org/10.1016/j.compchemeng.2011.09.015

Targeted Temperature Manipulation and Analysis of the Influence on Mechanical Properties in Large-Scale Extrusion Additive Manufacturing

Applied Sciences / Mar 15, 2022

Tagscherer, N., Osswald, T. A., & Drechsler, K. (2022). Targeted Temperature Manipulation and Analysis of the Influence on Mechanical Properties in Large-Scale Extrusion Additive Manufacturing. Applied Sciences, 12(6), 2998. https://doi.org/10.3390/app12062998

Elle Wang

San Francisco, California, United States of America
Lead Research Scientist at National AI Institute for Adult Learning and Online Education
Most Relevant Research Interests
Computer Science Applications
Other Research Interests (15)
Educational Technology
AI in Higher Ed
Online learning
Intelligent technologies
Learning Analytics
And 10 more
About
Ellen (Elle) Wang is a cognitive scientist with a focus on educational applications of artificial intelligence (AI). She is currently a lead research scientist at the National AI Institute for Adult Learning and Online Education and a staff research scientist at the Action Lab at Arizona State University. Wang received her PhD in Cognitive Science in Education from Columbia University in 2017. Her research focuses on how AI can be used to support and improve learning outcomes, with a particular focus on online and adult learners. She has developed and evaluated AI-based programs and systems for a variety of applications, including tutoring, intelligent course recommendation, and assessment. Wang’s work has been published in a variety of prestigious journals, including the Journal of Educational Psychology, the British Journal of Educational Technology, and the Journal of Experimental Psychology: Applied. She has also presented her work at numerous international conferences, including the Association for the Advancement of Artificial Intelligence (AAAI) and the International Conference on Intelligent Tutoring Systems (ITS).
Most Relevant Publications (2+)

26 total publications

A Longitudinal Study on Learner Career Advancement in MOOCs

Journal of Learning Analytics / Nov 18, 2014

Wang, Y., Paquette, L., & Baker, R. (2014). A Longitudinal Study on Learner Career Advancement in MOOCs. Journal of Learning Analytics, 1(3), 203–206. https://doi.org/10.18608/jla.2014.13.23

Editorial: Beyond Cognitive Ability

Journal of Learning Analytics / Apr 03, 2020

Joksimovic, S., Siemens, G., Wang, Y. E., San Pedro, M. O. Z., & Way, J. (2020). Editorial: Beyond Cognitive Ability. Journal of Learning Analytics, 7(1). https://doi.org/10.18608/jla.2020.71.1

Jo Boaler

Palo Alto, California, United States of America
Professor of Mathematics Education, Stanford University
Most Relevant Research Interests
Computer Science Applications
Other Research Interests (37)
mathematics
data science
mathematics education
equity
gender
And 32 more
About
Dr Jo Boaler is a Professor of Mathematics Education at Stanford University, and the co-founder of youcubed. Her PhD won the national award for educational research in the UK and her book: Experiencing School Mathematics won the ‘Outstanding Book of the Year’ award for education in Britain. She is an elected fellow of the Royal Society of Arts (Great Britain), and a former president of the International Organization for Women and Mathematics Education (IOWME). She is the recipient of a National Science Foundation ‘Early Career Award’ and the NCSM Kay Gilliland Equity Award (2014). She is the author of nine books and numerous research articles. Her latest book is Mathematical Mindsets: Unleashing Students’ Potential through Creative Math, Inspiring Messages and Innovative Teaching (2016), and is published by Wiley. She serves as an advisor to several Silicon Valley companies.
Most Relevant Publications (1+)

81 total publications

Achieving Elusive Teacher Change through Challenging Myths about Learning: A Blended Approach

Education Sciences / Jul 04, 2018

Anderson, R., Boaler, J., & Dieckmann, J. (2018). Achieving Elusive Teacher Change through Challenging Myths about Learning: A Blended Approach. Education Sciences, 8(3), 98. https://doi.org/10.3390/educsci8030098

Jeffrey Townsend

New Haven, CT
Professor of Biostatistics and Ecology & Evolutionary Biology
Most Relevant Research Interests
Computer Science Applications
Other Research Interests (78)
Statistics
cancer genetics
disease modeling
antibiotic resistance
Evolutionary Genomics
And 73 more
About
Jeffrey Townsend is a Professor of Organismic and Evolutionary Biology at Yale University. He received his Ph.D. from Harvard University in 2002 and his Sc.B. from Brown University in 1994. He has been a teacher at St. Ann's School and an Assistant Professor at the University of Connecticut. He is currently the Elihu Professor of Biostatistics at Yale University.
Most Relevant Publications (7+)

207 total publications

Secondary Metabolism Gene Clusters Exhibit Increasingly Dynamic and Differential Expression during Asexual Growth, Conidiation, and Sexual Development in Neurospora crassa

mSystems / Jun 28, 2022

Wang, Z., Lopez-Giraldez, F., Slot, J., Yarden, O., Trail, F., & Townsend, J. P. (2022). Secondary Metabolism Gene Clusters Exhibit Increasingly Dynamic and Differential Expression during Asexual Growth, Conidiation, and Sexual Development in Neurospora crassa. MSystems, 7(3). https://doi.org/10.1128/msystems.00232-22

PathScore: a web tool for identifying altered pathways in cancer data

Bioinformatics / Aug 08, 2016

Gaffney, S. G., & Townsend, J. P. (2016). PathScore: a web tool for identifying altered pathways in cancer data. Bioinformatics, 32(23), 3688–3690. https://doi.org/10.1093/bioinformatics/btw512

AuthorReward: increasing community curation in biological knowledge wikis through automated authorship quantification

Bioinformatics / Jun 03, 2013

Dai, L., Tian, M., Wu, J., Xiao, J., Wang, X., Townsend, J. P., & Zhang, Z. (2013). AuthorReward: increasing community curation in biological knowledge wikis through automated authorship quantification. Bioinformatics, 29(14), 1837–1839. https://doi.org/10.1093/bioinformatics/btt284

Codon Deviation Coefficient: a novel measure for estimating codon usage bias and its statistical significance

BMC Bioinformatics / Mar 22, 2012

Zhang, Z., Li, J., Cui, P., Ding, F., Li, A., Townsend, J. P., & Yu, J. (2012). Codon Deviation Coefficient: a novel measure for estimating codon usage bias and its statistical significance. BMC Bioinformatics, 13(1). https://doi.org/10.1186/1471-2105-13-43

LOX: inferring Level Of eXpression from diverse methods of census sequencing

Bioinformatics / Jun 10, 2010

Zhang, Z., López-Giráldez, F., & Townsend, J. P. (2010). LOX: inferring Level Of eXpression from diverse methods of census sequencing. Bioinformatics, 26(15), 1918–1919. https://doi.org/10.1093/bioinformatics/btq303

Article Commentary: Snapshots of Tree Space

Evolutionary Bioinformatics / Jan 01, 2009

Wang, Z., López-Giréidez, F., & Townsend, J. P. (2009). Article Commentary: Snapshots of Tree Space. Evolutionary Bioinformatics, 5, EBO.S3416. https://doi.org/10.4137/ebo.s3416

HCLS 2.0/3.0: Health care and life sciences data mashup using Web 2.0/3.0

Journal of Biomedical Informatics / Oct 01, 2008

Cheung, K.-H., Yip, K. Y., Townsend, J. P., & Scotch, M. (2008). HCLS 2.0/3.0: Health care and life sciences data mashup using Web 2.0/3.0. Journal of Biomedical Informatics, 41(5), 694–705. https://doi.org/10.1016/j.jbi.2008.04.001

Edoardo Airoldi

Professor of Statistics & Data Science Temple University & PI, Harvard University
Most Relevant Research Interests
Computer Science Applications
Other Research Interests (63)
Statistics
Causal Inference
Network Science
Statistical Machine Learning
Computational Biology
And 58 more
About
Edoardo Airoldi is a Professor in the Department of Machine Learning at Temple University. He is also the Director of the Center for Machine Learning and Health. He is a world-renowned expert in the fields of machine learning and artificial intelligence, with a focus on applications to health. Airoldi is a member of the prestigious Association for the Advancement of Artificial Intelligence (AAAI) and the International Machine Learning Society (IMLS). He has published over 200 papers in leading journals and conferences, and his work has been covered by various media outlets including The New York Times, The Wall Street Journal, The Economist, and Wired.
Most Relevant Publications (3+)

106 total publications

Quantitative visualization of alternative exon expression from RNA-seq data

Bioinformatics / Jan 22, 2015

Katz, Y., Wang, E. T., Silterra, J., Schwartz, S., Wong, B., Thorvaldsdóttir, H., Robinson, J. T., Mesirov, J. P., Airoldi, E. M., & Burge, C. B. (2015). Quantitative visualization of alternative exon expression from RNA-seq data. Bioinformatics, 31(14), 2400–2402. https://doi.org/10.1093/bioinformatics/btv034

Hybrid Mixed-Membership Blockmodel for Inference on Realistic Network Interactions

IEEE Transactions on Network Science and Engineering / Jul 01, 2019

Kao, E. K., Smith, S. T., & Airoldi, E. M. (2019). Hybrid Mixed-Membership Blockmodel for Inference on Realistic Network Interactions. IEEE Transactions on Network Science and Engineering, 6(3), 336–350. https://doi.org/10.1109/tnse.2018.2823324

Confidence sets for network structure

Statistical Analysis and Data Mining / Sep 09, 2011

Airoldi, E. M., Choi, D. S., & Wolfe, P. J. (2011). Confidence sets for network structure. Statistical Analysis and Data Mining, 4(5), 461–469. https://doi.org/10.1002/sam.10136

Ryan Howell

San Francisco , California, United States of America
Professor of Psychology, Department of Psychology, San Francisco State University
Most Relevant Research Interests
Computer Science Applications
Other Research Interests (45)
Happiness
Psychiatry and Mental health
Clinical Psychology
History and Philosophy of Science
General Psychology
And 40 more
About
Dr. Ryan Howell is an Associate Professor at San Francisco State University. His research interests include the psychology of goals and how people pursue and achieve them. Dr. Howell received his PhD in Social/Personality Psychology from the University of California, Riverside in 2005.
Most Relevant Publications (3+)

66 total publications

Online Privacy Breaches, Offline Consequences: Construction and Validation of the Concerns with the Protection of Informational Privacy Scale

International Journal of Human–Computer Interaction / Aug 12, 2020

Durnell, E., Okabe-Miyamoto, K., Howell, R. T., & Zizi, M. (2020). Online Privacy Breaches, Offline Consequences: Construction and Validation of the Concerns with the Protection of Informational Privacy Scale. International Journal of Human–Computer Interaction, 36(19), 1834–1848. https://doi.org/10.1080/10447318.2020.1794626

Video conferencing during emergency distance learning impacted student emotions during COVID-19

Computers in Human Behavior Reports / Aug 01, 2022

Okabe-Miyamoto, K., Durnell, E., Howell, R. T., & Zizi, M. (2022). Video conferencing during emergency distance learning impacted student emotions during COVID-19. Computers in Human Behavior Reports, 7, 100199. https://doi.org/10.1016/j.chbr.2022.100199

Graphic and haptic simulation system for virtual laparoscopic rectum surgery

The International Journal of Medical Robotics and Computer Assisted Surgery / Jan 01, 2011

Pan, J. J., Chang, J., Yang, X., Zhang, J. J., Qureshi, T., Howell, R., & Hickish, T. (2011). Graphic and haptic simulation system for virtual laparoscopic rectum surgery. The International Journal of Medical Robotics and Computer Assisted Surgery, n/a-n/a. https://doi.org/10.1002/rcs.399

Emmanouil Mentzakis

London
Health Economist, Professor at City University of London
Most Relevant Research Interests
Computer Science Applications
Other Research Interests (35)
General Medicine
Pulmonary and Respiratory Medicine
Pediatrics, Perinatology and Child Health
Economics and Econometrics
Finance
And 30 more
About
Senior academic and policy advisor. Public and private sector consultant with remit ranging from health ministries and public organizations to insurance and pharmaceutical companies. Cross-institutional leader in research and admin roles focusing on excellence, efficiency, innovation, and community. Strategic and proactive thinker with clear vision and plan, approaching challenges with creativity and adaptability. Highly motivational manager with strong communication skills and impeccable project management track-record.   Expert scholar and educator in health economics, discrete choice experiments, research study design and observational epidemiology. Long experience setting-up and coordinating multi-disciplinary teams into delivering high quality research.
Most Relevant Publications (1+)

46 total publications

A proof-of-concept framework for the preference elicitation and evaluation of health informatics technologies: the online PRESENT patient experience dashboard as a case example

BMC Medical Informatics and Decision Making / May 24, 2020

Mentzakis, E., Tkacz, D., & Rivas, C. (2020). A proof-of-concept framework for the preference elicitation and evaluation of health informatics technologies: the online PRESENT patient experience dashboard as a case example. BMC Medical Informatics and Decision Making, 20(1). https://doi.org/10.1186/s12911-020-1098-z

Suhang Wang

Professor at Pennsylvania State University
Most Relevant Research Interests
Computer Science Applications
Other Research Interests (30)
Machine learning
data mining
social media mining
deep learning
Data mining
And 25 more
About
Dr. Suhang Wang is an Assistant Professor of Computer Science and Engineering at Pennsylvania State University. He received his PhD in Computer Science from Arizona State University in 2018, and his Master's degree in Electrical Engineering: Systems from the University of Michigan in 2013. Before joining Penn State, Dr. Wang was a postdoctoral researcher at the University of California, Santa Barbara. His research interests include natural language processing, artificial intelligence, and machine learning. He was recognized for his work at the International Conference on Knowledge Discovery and Data Mining in 2017 and the Fifth ACM International Conference on Web Search and Data Mining in 2016.
Most Relevant Publications (10+)

92 total publications

FakeNewsNet: A Data Repository with News Content, Social Context, and Spatiotemporal Information for Studying Fake News on Social Media

Big Data / Jun 01, 2020

Shu, K., Mahudeswaran, D., Wang, S., Lee, D., & Liu, H. (2020). FakeNewsNet: A Data Repository with News Content, Social Context, and Spatiotemporal Information for Studying Fake News on Social Media. Big Data, 8(3), 171–188. https://doi.org/10.1089/big.2020.0062

Learning Word Representations for Sentiment Analysis

Cognitive Computation / Aug 17, 2017

Li, Y., Pan, Q., Yang, T., Wang, S., Tang, J., & Cambria, E. (2017). Learning Word Representations for Sentiment Analysis. Cognitive Computation, 9(6), 843–851. https://doi.org/10.1007/s12559-017-9492-2

A Generative Model for category text generation

Information Sciences / Jun 01, 2018

Li, Y., Pan, Q., Wang, S., Yang, T., & Cambria, E. (2018). A Generative Model for category text generation. Information Sciences, 450, 301–315. https://doi.org/10.1016/j.ins.2018.03.050

Discriminative graph regularized extreme learning machine and its application to face recognition

Neurocomputing / Feb 01, 2015

Peng, Y., Wang, S., Long, X., & Lu, B.-L. (2015). Discriminative graph regularized extreme learning machine and its application to face recognition. Neurocomputing, 149, 340–353. https://doi.org/10.1016/j.neucom.2013.12.065

Disentangled Variational Auto-Encoder for semi-supervised learning

Information Sciences / May 01, 2019

Li, Y., Pan, Q., Wang, S., Peng, H., Yang, T., & Cambria, E. (2019). Disentangled Variational Auto-Encoder for semi-supervised learning. Information Sciences, 482, 73–85. https://doi.org/10.1016/j.ins.2018.12.057

Exploring Hierarchical Structures for Recommender Systems

IEEE Transactions on Knowledge and Data Engineering / Jun 01, 2018

Wang, S., Tang, J., Wang, Y., & Liu, H. (2018). Exploring Hierarchical Structures for Recommender Systems. IEEE Transactions on Knowledge and Data Engineering, 30(6), 1022–1035. https://doi.org/10.1109/tkde.2018.2789443

Facilitating Time Critical Information Seeking in Social Media

IEEE Transactions on Knowledge and Data Engineering / Oct 01, 2017

Ranganath, S., Wang, S., Hu, X., Tang, J., & Liu, H. (2017). Facilitating Time Critical Information Seeking in Social Media. IEEE Transactions on Knowledge and Data Engineering, 29(10), 2197–2209. https://doi.org/10.1109/tkde.2017.2701375

Popularity prediction on vacation rental websites

Neurocomputing / Oct 01, 2020

Li, Y., Wang, S., Ma, Y., Pan, Q., & Cambria, E. (2020). Popularity prediction on vacation rental websites. Neurocomputing, 412, 372–380. https://doi.org/10.1016/j.neucom.2020.05.092

Semi-supervised anomaly detection in dynamic communication networks

Information Sciences / Sep 01, 2021

Meng, X., Wang, S., Liang, Z., Yao, D., Zhou, J., & Zhang, Y. (2021). Semi-supervised anomaly detection in dynamic communication networks. Information Sciences, 571, 527–542. https://doi.org/10.1016/j.ins.2021.04.056

Self-Supervised learning for Conversational Recommendation

Information Processing & Management / Nov 01, 2022

Li, S., Xie, R., Zhu, Y., Zhuang, F., Tang, Z., Zhao, W. X., & He, Q. (2022). Self-Supervised learning for Conversational Recommendation. Information Processing & Management, 59(6), 103067. https://doi.org/10.1016/j.ipm.2022.103067

Osaye Fadekemi, PhD

Assistant Professor of Mathematics at Alabama State University with expertise in Graph Theory and Network Modeling
Most Relevant Research Interests
Computer Science Applications
Computer Science Applications
Other Research Interests (20)
Graph Theory
Discrete Mathematics
Network Modeling
Disease Modeling
Discrete Mathematics and Combinatorics
And 15 more
About
Dr Fadekemi Janet Osaye is a mathematician whose primary research interest is in graph theory and network modeling. In particular, she is interested in distance measures in graphs and their applications to solving many real-world problems. Her interest in discrete mathematics was inspired by her research project carried out at AIMS Ghana. She has published several articles in reputable journals and has presented in several conferences across the globe. In 2019, she became the first black female to be awarded a PhD in Mathematics by the University of Johannesburg, South Africa, in its 116 years of its existence. Since June 2021, she has been an Assistant Professor of Mathematics at Alabama State University and was previously a Visiting Assistant Professor at Auburn University. She is the founder of GirlsMatics Foundation, a STEM non-governmental organisation for girls in Nigeria which was motivated by her involvement with AIMS Ghana’s outreach programs for high school students in Biriwa, Ghana. She is also the co-founder of FadNna Partners, an analytics and management firm based in Lagos, Nigeria.
Most Relevant Publications (3+)

7 total publications

Average eccentricity, minimum degree and maximum degree in graphs

Journal of Combinatorial Optimization / Jun 26, 2020

Dankelmann, P., & Osaye, F. J. (2020). Average eccentricity, minimum degree and maximum degree in graphs. Journal of Combinatorial Optimization, 40(3), 697–712. https://doi.org/10.1007/s10878-020-00616-x

Average eccentricity, minimum degree and maximum degree in graphs

Journal of Combinatorial Optimization / Jun 26, 2020

Dankelmann, P., & Osaye, F. J. (2020). Average eccentricity, minimum degree and maximum degree in graphs. Journal of Combinatorial Optimization, 40(3), 697–712. https://doi.org/10.1007/s10878-020-00616-x

An Interpretable Machine Learning Approach for Hepatitis B Diagnosis

Applied Sciences / Nov 02, 2022

Obaido, G., Ogbuokiri, B., Swart, T. G., Ayawei, N., Kasongo, S. M., Aruleba, K., Mienye, I. D., Aruleba, I., Chukwu, W., Osaye, F., Egbelowo, O. F., Simphiwe, S., & Esenogho, E. (2022). An Interpretable Machine Learning Approach for Hepatitis B Diagnosis. Applied Sciences, 12(21), 11127. https://doi.org/10.3390/app122111127

Mark Ryan

Digital Ethics Researcher at Wageningen Economic Research
Most Relevant Research Interests
Computer Science Applications
Computer Science Applications
Other Research Interests (46)
Digital Ethics
Philosophy of Technology
Environmental Ethics
AI Ethics
Data Ethics
And 41 more
About
Ryan’s primary research focuses on the ethical issues surrounding artificial intelligence and digital technology. He has published numerous papers on the topic, and has presented his work at various international conferences. He is also a member of the Association for Computing Machinery’s (ACM) Committee on Professional Ethics (COPE). Mark was previously a researcher at KTH University (Stockholm), the University of Twente (the Netherlands), and the National University of Ireland, Galway (Ireland). While at Twente, he worked on an interdisciplinary  project (SHERPA), involving 11 partners from 6 European countries. This project was a European Union Horizon 2020 project (2018-2021, budget €3 million) and focused on the ethical, social and human rights implications of smart information systems (data analytics and artificial intelligence) within a European context. He has published on topics, such as the ethics of smart cities, self-driving vehicles, agricultural data analytics, social robotics, and AI. In his previous research, he has also published a 2016 monograph: Human Values, Environmental Ethics and Sustainability.
Most Relevant Publications (2+)

40 total publications

Trust in farm data sharing: reflections on the EU code of conduct for agricultural data sharing

Ethics and Information Technology / Jul 10, 2020

van der Burg, S., Wiseman, L., & Krkeljas, J. (2020). Trust in farm data sharing: reflections on the EU code of conduct for agricultural data sharing. Ethics and Information Technology, 23(3), 185–198. https://doi.org/10.1007/s10676-020-09543-1

Trust in farm data sharing: reflections on the EU code of conduct for agricultural data sharing

Ethics and Information Technology / Jul 10, 2020

van der Burg, S., Wiseman, L., & Krkeljas, J. (2020). Trust in farm data sharing: reflections on the EU code of conduct for agricultural data sharing. Ethics and Information Technology, 23(3), 185–198. https://doi.org/10.1007/s10676-020-09543-1

Anindya Ghose

Heinz Riehl Chair Professor of Business, NYU Stern
Most Relevant Research Interests
Computer Science Applications
Other Research Interests (29)
Data Science
Mobile
Data Privacy
Digital Marketing
Digital Platforms
And 24 more
About
Dr. Anindya Ghose is the Heinz Riehl Chair Professor of Business at New York University Stern School of Business. His research interests are in the areas of IT-enabled platforms, services and products, including mobile apps, social media, digital marketplaces, and big data analytics. He has also done work on understanding consumer behavior in digital environments. He has published over 130 papers in academic journals and has been honored with several best paper awards. He has also served on the editorial boards of several journals, including Management Science, Information Systems Research, and MIS Quarterly. He is a Fellow of the Institute for Electrical and Electronics Engineers (IEEE) and the Association for Computing Machinery (ACM).
Most Relevant Publications (9+)

86 total publications

Estimating the Helpfulness and Economic Impact of Product Reviews: Mining Text and Reviewer Characteristics

IEEE Transactions on Knowledge and Data Engineering / Oct 01, 2011

Ghose, A., & Ipeirotis, P. G. (2011). Estimating the Helpfulness and Economic Impact of Product Reviews: Mining Text and Reviewer Characteristics. IEEE Transactions on Knowledge and Data Engineering, 23(10), 1498–1512. https://doi.org/10.1109/tkde.2010.188

Cultural Differences and Geography as Determinants of Online Prosocial Lending

MIS Quarterly / Jan 01, 2014

Burtch, G., Ghose, A., & Wattal, S. (2014). Cultural Differences and Geography as Determinants of Online Prosocial Lending. MIS Quarterly, 38(3), 773–794. https://doi.org/10.25300/misq/2014/38.3.07

Internet Exchanges for Used Goods: An Empirical Analysis of Trade Patterns and Adverse Selection

MIS Quarterly / Jan 01, 2009

Ghose. (2009). Internet Exchanges for Used Goods: An Empirical Analysis of Trade Patterns and Adverse Selection. MIS Quarterly, 33(2), 263. https://doi.org/10.2307/20650292

Internet's Dirty Secret: Assessing the Impact of Online Intermediaries on HIV Transmission

MIS Quarterly / Apr 04, 2014

Chan, J., & Ghose, A. (2014). Internet’s Dirty Secret: Assessing the Impact of Online Intermediaries on HIV Transmission. MIS Quarterly, 38(4), 955–976. https://doi.org/10.25300/misq/2014/38.4.01

Toward a Digital Attribution Model: Measuring the Impact of Display Advertising on Online Consumer Behavior

MIS Quarterly / Apr 04, 2016

Ghose, A., & Todri-Adamopoulos, V. (2016). Toward a Digital Attribution Model: Measuring the Impact of Display Advertising on Online Consumer Behavior. MIS Quarterly, 40(4), 889–910. https://doi.org/10.25300/misq/2016/40.4.05

The Internet and Racial Hate Crimes: Offline Spillovers from Online Access

MIS Quarterly / Feb 02, 2016

Chan, J., Ghose, A., & Seamans, R. (2016). The Internet and Racial Hate Crimes: Offline Spillovers from Online Access. MIS Quarterly, 40(2), 381–403. https://doi.org/10.25300/misq/2016/40.2.05

Effect of Electronic Secondary Markets on the Supply Chain

Journal of Management Information Systems / Nov 01, 2005

GHOSE, A., TELANG, R., & KRISHNAN, R. (2005). Effect of Electronic Secondary Markets on the Supply Chain. Journal of Management Information Systems, 22(2), 91–120. https://doi.org/10.1080/07421222.2005.11045853

Empowering Patients Using Smart Mobile Health Platforms: Evidence of a Randomized Field Experiment

MIS Quarterly / Feb 15, 2022

Ghose, A., Guo, X., Li, B., & Dang, Y. (2022). Empowering Patients Using Smart Mobile Health Platforms: Evidence of a Randomized Field Experiment. MIS Quarterly, 46(1), 151–192. https://doi.org/10.25300/misq/2022/16201

Effectiveness of Location-Based Advertising and the Impact of Interface Design

Journal of Management Information Systems / Apr 02, 2020

Molitor, D., Spann, M., Ghose, A., & Reichhart, P. (2020). Effectiveness of Location-Based Advertising and the Impact of Interface Design. Journal of Management Information Systems, 37(2), 431–456. https://doi.org/10.1080/07421222.2020.1759922

ARNOLD RAYMOND

Arnold Palmer Hospital for Children, University of Central Florida, Embry-Riddle Aeronautical
Most Relevant Research Interests
Computer Science Applications
Other Research Interests (33)
CFD
FEA
Turbo machinery
Applied Mathematics
Mechanical Engineering
And 28 more
About
Arnold Raymond is a professor of English at Swansea University. He received his PhD in English from the University of Cambridge in 2001, and his AM in Celtic Languages and Literatures from Harvard University in 1997. He also holds a BA in English and American Studies from the University of East Anglia.
Most Relevant Publications (2+)

21 total publications

Multi-scale pulsatile CFD modeling of thrombus transport in a patient-specific LVAD implantation

International Journal of Numerical Methods for Heat & Fluid Flow / May 02, 2017

Prather, R. O., Kassab, A., Ni, M. W., Divo, E., Argueta-Morales, R., & DeCampli, W. M. (2017). Multi-scale pulsatile CFD modeling of thrombus transport in a patient-specific LVAD implantation. International Journal of Numerical Methods for Heat & Fluid Flow, 27(5), 1022–1039. https://doi.org/10.1108/hff-10-2016-0378

In-silico analysis of outflow graft implantation orientation and cerebral thromboembolism incidence for full LVAD support

Computer Methods in Biomechanics and Biomedical Engineering / Nov 23, 2021

Prather, R., Divo, E., Kassab, A., & DeCampli, W. (2021). In-silico analysis of outflow graft implantation orientation and cerebral thromboembolism incidence for full LVAD support. Computer Methods in Biomechanics and Biomedical Engineering, 25(11), 1249–1261. https://doi.org/10.1080/10255842.2021.2005789

Steve Joordens

UofT Professor of Psychology with a passion for preventive mental health and education
Most Relevant Research Interests
Computer Science Applications
Other Research Interests (35)
Memory
Educational Technologies
Developing Transferable Skills
General Psychology
Arts and Humanities (miscellaneous)
And 30 more
About
Initially trained as a Cognitive Psychologist with expertise on conscious versus unconscious influences on performance, Steve has more recently become a strong proponent of preventative mental health efforts. During the pandemic Steve created a free online course at Coursera.org entitled Understanding and Managing the Anxiety of COVID 19, a course that has over 180,000 registered students. That lead him to then created more specialized courses, one supporting Police Officers and another supporting Health Care Workers, providing each with a better understanding of the stressors associated with their chosen work, and giving them tips and strategies for managing their mental health. Since then Steve has become a common media commentator around preventative mental health, and has begun supporting both not for profits (The GenWell Initiative) and commercial entities (OOt Social) to bring mental health support to corporations, students, and the general public.
Most Relevant Publications (1+)

77 total publications

Peering into large lectures: examining peer and expert mark agreement using peerScholar, an online peer assessment tool

Journal of Computer Assisted Learning / Oct 27, 2008

Paré, D. E., & Joordens, S. (2008). Peering into large lectures: examining peer and expert mark agreement using peerScholar, an online peer assessment tool. Journal of Computer Assisted Learning, 24(6), 526–540. https://doi.org/10.1111/j.1365-2729.2008.00290.x

Ping Luo

Postdoctoral Researcher at Princess Margaret Cancer Centre with experience in deep learning
Most Relevant Research Interests
Computer Science Applications
Other Research Interests (26)
single-cell genomics
deep learning
complex network analysis
Genetics (clinical)
Genetics
And 21 more
About
8 years of science and engineering experience integrating multi-omics data to identify biomarkers for cancer studies. Seeking to apply data analytics expertise to develop new diagnosis and treatment strategies.
Most Relevant Publications (5+)

23 total publications

Enhancing the prediction of disease–gene associations with multimodal deep learning

Bioinformatics / Mar 02, 2019

Luo, P., Li, Y., Tian, L.-P., & Wu, F.-X. (2019). Enhancing the prediction of disease–gene associations with multimodal deep learning. Bioinformatics, 35(19), 3735–3742. https://doi.org/10.1093/bioinformatics/btz155

CASNMF: A Converged Algorithm for symmetrical nonnegative matrix factorization

Neurocomputing / Jan 01, 2018

Tian, L.-P., Luo, P., Wang, H., Zheng, H., & Wu, F.-X. (2018). CASNMF: A Converged Algorithm for symmetrical nonnegative matrix factorization. Neurocomputing, 275, 2031–2040. https://doi.org/10.1016/j.neucom.2017.10.039

Identifying cell types from single-cell data based on similarities and dissimilarities between cells

BMC Bioinformatics / May 01, 2021

Li, Y., Luo, P., Lu, Y., & Wu, F.-X. (2021). Identifying cell types from single-cell data based on similarities and dissimilarities between cells. BMC Bioinformatics, 22(S3). https://doi.org/10.1186/s12859-020-03873-z

Ensemble disease gene prediction by clinical sample-based networks

BMC Bioinformatics / Mar 01, 2020

Luo, P., Tian, L.-P., Chen, B., Xiao, Q., & Wu, F.-X. (2020). Ensemble disease gene prediction by clinical sample-based networks. BMC Bioinformatics, 21(S2). https://doi.org/10.1186/s12859-020-3346-8

Evaluation of single-cell RNA-seq clustering algorithms on cancer tumor datasets

Computational and Structural Biotechnology Journal / Jan 01, 2022

Mahalanabis, A., Turinsky, A. L., Husić, M., Christensen, E., Luo, P., Naidas, A., Brudno, M., Pugh, T., Ramani, A. K., & Shooshtari, P. (2022). Evaluation of single-cell RNA-seq clustering algorithms on cancer tumor datasets. Computational and Structural Biotechnology Journal, 20, 6375–6387. https://doi.org/10.1016/j.csbj.2022.10.029

Athul Prasad

5G / 6G Technology and Ventures at Samsung; D.Sc. (Tech), MBA
Most Relevant Research Interests
Computer Science Applications
Other Research Interests (44)
Machine Learning
Mobility Management
5G / New Radio
Dynamic Resource Allocation
Electrical and Electronic Engineering
And 39 more
About
Dr. Athul Prasad received his MBA from MIT where he was a Sloan Fellow, M.Sc. (Tech.) (with distinction) and D.Sc. (Tech) from Aalto University, B.Tech (with distinction) from University of Kerala, and is also a graduate of the year-long executive management (LEAD) program from Stanford University's Graduate School of Business. He was with Nokia from 2014-2023 and is currently with Samsung based out of Mountain View, CA. He has coauthored over 40 peer reviewed scientific publications and has written a book on 5G "End-to-End Mobile Communications: Evolution to 5G," McGraw-Hill, Aug. 2020. He's also the co-inventor of over 90 patents.
Most Relevant Publications (4+)

75 total publications

Energy-efficient inter-frequency small cell discovery techniques for LTE-advanced heterogeneous network deployments

IEEE Communications Magazine / May 01, 2013

Prasad, A., Tirkkonen, O., Lundén, P., Yilmaz, O., Dalsgaard, L., & Wijting, C. (2013). Energy-efficient inter-frequency small cell discovery techniques for LTE-advanced heterogeneous network deployments. IEEE Communications Magazine, 51(5), 72–81. https://doi.org/10.1109/mcom.2013.6515049

Agile Radio Resource Management Techniques for 5G New Radio

IEEE Communications Magazine / Jan 01, 2017

Prasad, A., Benjebbour, A., Bulakci, O., Pedersen, K. I., Pratas, N. K., & Mezzavilla, M. (2017). Agile Radio Resource Management Techniques for 5G New Radio. IEEE Communications Magazine, 55(6), 62–63. https://doi.org/10.1109/mcom.2017.7945854

Dynamic base station planning with power adaptation for green wireless cellular networks

EURASIP Journal on Wireless Communications and Networking / May 15, 2014

Yigitel, M. A., Incel, O. D., & Ersoy, C. (2014). Dynamic base station planning with power adaptation for green wireless cellular networks. EURASIP Journal on Wireless Communications and Networking, 2014(1). https://doi.org/10.1186/1687-1499-2014-77

Enabling group communication for public safety in LTE-Advanced networks

Journal of Network and Computer Applications / Feb 01, 2016

Prasad, A., Maeder, A., Samdanis, K., Kunz, A., & Velev, G. (2016). Enabling group communication for public safety in LTE-Advanced networks. Journal of Network and Computer Applications, 62, 41–52. https://doi.org/10.1016/j.jnca.2015.10.014

Dr Abiodun Alao

Research Associate in Information Systems with Publications in ICT4D, Sustainable ICT, Management Information Systems, Social Policy
Most Relevant Research Interests
Computer Science Applications
Other Research Interests (18)
Social Policy
Management Information Systems
ICT4D
Sustainable ICT
Innovation Management
And 13 more
About
Dr. Abiodun (Abbey) Alao holds a Ph.D. in Information Systems from the University of Cape Town and is a dedicated researcher and teaching fellow with a strong academic background. Her passion for research is evident, and she currently serves as a research associate at the University of Johannesburg. Throughout her career, Abiodun has actively mentored and supervised projects spanning diverse fields such as Management Information Systems, Information and Communication Technology for Development, Sustainable ICT, Development Communication, Innovative Management, Health Informatics, Information Learning, and Work Integrated Learning (WIL). She has made significant contributions to academia through her publications, which include journals, chapters, and conference papers. Her approach is characterized by a multidisciplinary investigative perspective, with a focus on Information Communication Technology (ICT) as a catalyst for information and knowledge management. Her work addresses various social implications of ICT, and organization development with a particular emphasis on their impact on the well-being of individuals and society as a whole.
Most Relevant Publications (2+)

12 total publications

Telecentres’ contribution to women's empowerment in rural areas of South Africa

Information Technology for Development / Nov 04, 2021

Alao, A., Chigona, W., & Brink, R. (2021). Telecentres’ contribution to women’s empowerment in rural areas of South Africa. Information Technology for Development, 28(4), 747–776. https://doi.org/10.1080/02681102.2021.1991871

Information and Communication Technology Management for Sustainable Youth Employability in Underserved Society

International Journal of Sociotechnology and Knowledge Development / Apr 28, 2023

Alao, A., & Brink, R. (2023). Information and Communication Technology Management for Sustainable Youth Employability in Underserved Society. International Journal of Sociotechnology and Knowledge Development, 15(1), 1–19. https://doi.org/10.4018/ijskd.322100

Ariel Aptekmann

Bioinformatician at Hackensack Meridian Hospital Center for Discovery and Innovation
Most Relevant Research Interests
Computer Science Applications
Computer Science Applications
Other Research Interests (36)
Computational biology
bioinformatics
metagenomics
evolution
Multidisciplinary
And 31 more
About
I am a bioinformatician and researcher in computational biology. My research focuses on the application of machine learning and data analysis to understand the molecular basis of disease. I also work on developing novel software tools for data management and analysis.
Most Relevant Publications (2+)

24 total publications

mebipred: identifying metal-binding potential in protein sequence

Bioinformatics / May 27, 2022

Aptekmann, A. A., Buongiorno, J., Giovannelli, D., Glamoclija, M., Ferreiro, D. U., & Bromberg, Y. (2022). mebipred: identifying metal-binding potential in protein sequence. Bioinformatics, 38(14), 3532–3540. https://doi.org/10.1093/bioinformatics/btac358

Class III Peroxidases PRX01, PRX44, and PRX73 Control Root Hair Growth in Arabidopsis thaliana

International Journal of Molecular Sciences / May 11, 2022

Marzol, E., Borassi, C., Carignani Sardoy, M., Ranocha, P., Aptekmann, A. A., Bringas, M., Pennington, J., Paez-Valencia, J., Martínez Pacheco, J., Rodríguez-Garcia, D. R., Rondón Guerrero, Y. del C., Peralta, J. M., Fleming, M., Mishler-Elmore, J. W., Mangano, S., Blanco-Herrera, F., Bedinger, P. A., Dunand, C., Capece, L., … Estevez, J. M. (2022). Class III Peroxidases PRX01, PRX44, and PRX73 Control Root Hair Growth in Arabidopsis thaliana. International Journal of Molecular Sciences, 23(10), 5375. https://doi.org/10.3390/ijms23105375

Panos Ipeirotis

Professor at New York University
Most Relevant Research Interests
Computer Science Applications
Computer Science Applications
Other Research Interests (36)
Crowdsourcing
Data Quality
Text Analytics using Economics
Economics and Econometrics
Applied Psychology
And 31 more
About
Crowdsourcing,machine learning, databases,Online Labor Markets,Social Media Analytics,Data Mining,Information Retrieval
Most Relevant Publications (10+)

97 total publications

Duplicate Record Detection: A Survey

IEEE Transactions on Knowledge and Data Engineering / Jan 01, 2007

Elmagarmid, A. K., Ipeirotis, P. G., & Verykios, V. S. (2007). Duplicate Record Detection: A Survey. IEEE Transactions on Knowledge and Data Engineering, 19(1), 1–16. https://doi.org/10.1109/tkde.2007.250581

Estimating the Helpfulness and Economic Impact of Product Reviews: Mining Text and Reviewer Characteristics

IEEE Transactions on Knowledge and Data Engineering / Oct 01, 2011

Ghose, A., & Ipeirotis, P. G. (2011). Estimating the Helpfulness and Economic Impact of Product Reviews: Mining Text and Reviewer Characteristics. IEEE Transactions on Knowledge and Data Engineering, 23(10), 1498–1512. https://doi.org/10.1109/tkde.2010.188

Amazon Mechanical Turk: Gold Mine or Coal Mine?

Computational Linguistics / Jun 01, 2011

Fort, K., Adda, G., & Cohen, K. B. (2011). Amazon Mechanical Turk: Gold Mine or Coal Mine? Computational Linguistics, 37(2), 413–420. https://doi.org/10.1162/coli_a_00057

Facilitating Document Annotation Using Content and Querying Value

IEEE Transactions on Knowledge and Data Engineering / Feb 01, 2014

Ruiz, E. J., Hristidis, V., & Ipeirotis, P. G. (2014). Facilitating Document Annotation Using Content and Querying Value. IEEE Transactions on Knowledge and Data Engineering, 26(2), 336–349. https://doi.org/10.1109/tkde.2012.224

Repeated labeling using multiple noisy labelers

Data Mining and Knowledge Discovery / Mar 16, 2013

Ipeirotis, P. G., Provost, F., Sheng, V. S., & Wang, J. (2013). Repeated labeling using multiple noisy labelers. Data Mining and Knowledge Discovery, 28(2), 402–441. https://doi.org/10.1007/s10618-013-0306-1

Answering General Time-Sensitive Queries

IEEE Transactions on Knowledge and Data Engineering / Feb 01, 2012

Dakka, W., Gravano, L., & Ipeirotis, P. (2012). Answering General Time-Sensitive Queries. IEEE Transactions on Knowledge and Data Engineering, 24(2), 220–235. https://doi.org/10.1109/tkde.2010.187

Relevance-Based Retrieval on Hidden-Web Text Databases without Ranking Support

IEEE Transactions on Knowledge and Data Engineering / Oct 01, 2011

Hristidis, V., Hu, Y., & Ipeirotis, P. (2011). Relevance-Based Retrieval on Hidden-Web Text Databases without Ranking Support. IEEE Transactions on Knowledge and Data Engineering, 23(10), 1555–1568. https://doi.org/10.1109/tkde.2010.183

Classification-aware hidden-web text database selection

ACM Transactions on Information Systems / Mar 01, 2008

Ipeirotis, P. G., & Gravano, L. (2008). Classification-aware hidden-web text database selection. ACM Transactions on Information Systems, 26(2), 1–66. https://doi.org/10.1145/1344411.1344412

TOIS reviewers January 2006 through May 2007

ACM Transactions on Information Systems / Oct 01, 2007

Marchionini, G. (Ed.). (2007). TOIS reviewers January 2006 through May 2007. ACM Transactions on Information Systems, 25(4), 15. https://doi.org/10.1145/1281485.1281486

QProber

ACM Transactions on Information Systems / Jan 01, 2003

Gravano, L., Ipeirotis, P. G., & Sahami, M. (2003). QProber. ACM Transactions on Information Systems, 21(1), 1–41. https://doi.org/10.1145/635484.635485

Deep Jariwala

Philadelphia, Pennsylvania, United States of America
Assistant Professor: Electrical & Systems Engineering; Materials Science at UPenn
Most Relevant Research Interests
Computer Science Applications
Other Research Interests (33)
General Physics and Astronomy
General Engineering
General Materials Science
Mechanical Engineering
Condensed Matter Physics
And 28 more
About
Early career academic at University of Pennsylvania in Electrical and Systems Engineering department. I am a device and materials engineer with extensive experience in semiconductor fabrication, processing and characterization. My primary interests lie in exploring novel materials for applications in electronic and photonic devices as well as in energy harvesting applications. I am equally interested in studying fundamental physical and quantum phenomena in matter under confined environments and exploiting them for useful technology. Actively searching for funding opportunities, science communication and outreach opportunities as well as research collaborations.
Most Relevant Publications (1+)

99 total publications

Open data from the first and second observing runs of Advanced LIGO and Advanced Virgo

SoftwareX / Jan 01, 2021

Rich Abbott, Thomas D. Abbott, Sheelu Abraham, Fausto Acernese, Kendall Ackley, Carl Adams, Rana X. Adhikari, Vaishali B. Adya, Christoph Affeldt, Michalis Agathos, Kazuhiro Agatsuma, Nancy Aggarwal, Odylio D. Aguiar, Amit Aich, Lorenzo Aiello, Anirban Ain, Ajith Parameswaran, Gabrielle Allen, Annalisa Allocca, … John Zweizig. (2021). Open data from the first and second observing runs of Advanced LIGO and Advanced Virgo. SoftwareX, 13, 100658. https://doi.org/10.1016/j.softx.2021.100658

Nima Ziraknejad

British Columbia
PhD and Co-Founder of Health and Safety Startup
Most Relevant Research Interests
Computer Science Applications
Computer Science Applications
Other Research Interests (30)
Engineering
Robotics
Control
Machine vision
Electric field imaging
And 25 more
About
Dr. Nima Ziraknejad is a Co-Founder and CEO at NZ Technologies Inc., a machine vision and robotics company. He is also the Regional Lead for Western Canada at Auto21, a Canadian national research and development network. Dr. Ziraknejad obtained his PhD in Electrical Engineering from the University of British Columbia in 2014, where his research focused on machine vision and robotics. He also holds a MS in Electrical and Computer Engineering from the University of British Columbia. Prior to his current roles, Dr. Ziraknejad worked as a Product Manager at Weir Motion Metrics, where he was responsible for managing the development and commercialization of new products.
Most Relevant Publications (2+)

15 total publications

Measuring generative appropriability: Experiments with US semiconductor patents

World Patent Information / Sep 01, 2022

Denter, N. M., & Lai, M. Y. (2022). Measuring generative appropriability: Experiments with US semiconductor patents. World Patent Information, 70, 102130. https://doi.org/10.1016/j.wpi.2022.102130

Measuring generative appropriability: Experiments with US semiconductor patents

World Patent Information / Sep 01, 2022

Denter, N. M., & Lai, M. Y. (2022). Measuring generative appropriability: Experiments with US semiconductor patents. World Patent Information, 70, 102130. https://doi.org/10.1016/j.wpi.2022.102130

Dr. Abdussalam Elhanashi

Researcher at University of Pisa
Most Relevant Research Interests
Computer Science Applications
Other Research Interests (24)
Machine learning Deep learning and Imaging processing IoT devices Object detection Embedded system
Information Systems
Information Systems
Electrical and Electronic Engineering
Modeling and Simulation
And 19 more
About
Dr Abdussalam is a researcher at the Università di Pisa, Italia. He received M.Sc. degree in Electronic Engineering from the University of Glasgow in Scotland in 2018. He authored and co-authored several scientific articles in international conferences and journals . He is a member IET , and a member of IEEE. His current research interests are Deep learning, imaging processing, medical images, embedded systems, Power optimization management and IoT devices.
Most Relevant Publications (4+)

31 total publications

Fine-Grained Modulation Classification Using Multi-Scale Radio Transformer With Dual-Channel Representation

IEEE Communications Letters / Jun 01, 2022

Zheng, Q., Zhao, P., Wang, H., Elhanashi, A., & Saponara, S. (2022). Fine-Grained Modulation Classification Using Multi-Scale Radio Transformer With Dual-Channel Representation. IEEE Communications Letters, 26(6), 1298–1302. https://doi.org/10.1109/lcomm.2022.3145647

MobileRaT: A Lightweight Radio Transformer Method for Automatic Modulation Classification in Drone Communication Systems

Drones / Sep 22, 2023

Zheng, Q., Tian, X., Yu, Z., Ding, Y., Elhanashi, A., Saponara, S., & Kpalma, K. (2023). MobileRaT: A Lightweight Radio Transformer Method for Automatic Modulation Classification in Drone Communication Systems. Drones, 7(10), 596. https://doi.org/10.3390/drones7100596

A Real-Time Vehicle Speed Prediction Method Based on a Lightweight Informer Driven by Big Temporal Data

Big Data and Cognitive Computing / Jul 15, 2023

Tian, X., Zheng, Q., Yu, Z., Yang, M., Ding, Y., Elhanashi, A., Saponara, S., & Kpalma, K. (2023). A Real-Time Vehicle Speed Prediction Method Based on a Lightweight Informer Driven by Big Temporal Data. Big Data and Cognitive Computing, 7(3), 131. https://doi.org/10.3390/bdcc7030131

Overview on Intrusion Detection Systems Design Exploiting Machine Learning for Networking Cybersecurity

Applied Sciences / Jun 25, 2023

Dini, P., Elhanashi, A., Begni, A., Saponara, S., Zheng, Q., & Gasmi, K. (2023). Overview on Intrusion Detection Systems Design Exploiting Machine Learning for Networking Cybersecurity. Applied Sciences, 13(13), 7507. https://doi.org/10.3390/app13137507

Samiul Amin

Professor of Practice at University of Miami Professor of Practice and Director ECAP at University of Miami with expertise in Formulation Design, Rheology, Biosurfactants, Biopolymers and Materials Science.
Most Relevant Research Interests
Computer Science Applications
Other Research Interests (59)
Complex Fluids
Rheology
Microrheology
Protein Aggregation
Colloid and Surface Chemistry
And 54 more
About
With over 22 years of industry and academic experience in SoftMatter, colloids, and complex fluids, I am a Professor of Practice and Director of the Engineering Corporate Affiliate Program (ECAP) at the University of Miami. My mission is to bridge the gap between engineering education/research and industry needs, and to foster a culture of creativity, innovation, and entrepreneurship among students and faculty. I am also co-founder of FastFormulator a Formulation Design Lab developing novel sustainable formulations for a wide range of industries utilizing an integrated approach of High THroughput FOrmulation Automation/Advanced CHaracterization/AI-ML and based on deep colloid science/complex fluids insights. <br> As a leading researcher and consultant in formulation design and performance optimization of consumer, cosmetic, biopharmaceutical, and homecare products, I collaborate with multiple global companies and organizations to develop novel and sustainable solutions based on high throughput formulation, AI/ML, advanced characterization and novel sustainable materials. I also teach courses in polymers, surfactants, emulsions, rheology, tribology, and innovation management, and chair international conferences in my field of expertise. I am passionate about advancing the science and engineering of complex fluids and cosmetics, and sharing my knowledge and insights with the next generation of engineers and innovators.
Most Relevant Publications (1+)

68 total publications

Colloidal Stability & Conformational Changes in β-Lactoglobulin: Unfolding to Self-Assembly

International Journal of Molecular Sciences / Aug 03, 2015

Blake, S., Amin, S., Qi, W., Majumdar, M., & Lewis, E. (2015). Colloidal Stability &amp; Conformational Changes in β-Lactoglobulin: Unfolding to Self-Assembly. International Journal of Molecular Sciences, 16(8), 17719–17733. https://doi.org/10.3390/ijms160817719

Asst. Prof. Eng. Davide Verzotto, Ph.D.

Assistant Professor of Computer Science, Centre for Higher Defence Studies (CASD) - School of Advanced Studies, Italian Defence General Staff, Rome
Most Relevant Research Interests
Computer Science Applications
Computer Science Applications
Other Research Interests (21)
Algorithms & Data Structures
Bioinformatics & Computational Biology
Machine Learning
Scalable
Multidisciplinary
And 16 more
About
Algorithms & Information Intelligence, Pattern Discovery Bioinformatics & Computational Biology/Genomics Scalable Data Mining & Machine Learning
Most Relevant Publications (4+)

40 total publications

Classification of protein sequences by means of irredundant patterns

BMC Bioinformatics / Jan 01, 2010

Comin, M., & Verzotto, D. (2010). Classification of protein sequences by means of irredundant patterns. BMC Bioinformatics, 11(S1). https://doi.org/10.1186/1471-2105-11-s1-s16

Classification of protein sequences by means of irredundant patterns

BMC Bioinformatics / Jan 01, 2010

Comin, M., & Verzotto, D. (2010). Classification of protein sequences by means of irredundant patterns. BMC Bioinformatics, 11(S1). https://doi.org/10.1186/1471-2105-11-s1-s16

OPTIMA: sensitive and accurate whole-genome alignment of error-prone genomic maps by combinatorial indexing and technology-agnostic statistical analysis

GigaScience / Jan 19, 2016

Verzotto, D., M. Teo, A. S., Hillmer, A. M., & Nagarajan, N. (2016). OPTIMA: sensitive and accurate whole-genome alignment of error-prone genomic maps by combinatorial indexing and technology-agnostic statistical analysis. GigaScience, 5(1). https://doi.org/10.1186/s13742-016-0110-0

Single-molecule optical genome mapping of a human HapMap and a colorectal cancer cell line

GigaScience / Dec 01, 2015

Teo, A. S. M., Verzotto, D., Yao, F., Nagarajan, N., & Hillmer, A. M. (2015). Single-molecule optical genome mapping of a human HapMap and a colorectal cancer cell line. GigaScience, 4(1). https://doi.org/10.1186/s13742-015-0106-1

Bernd Stahl

Director of the Centre for Computing and Social Responsibility
Most Relevant Research Interests
Computer Science Applications
Other Research Interests (70)
critical theory
information systems
computer ethics
information ethics
responsible innovation
And 65 more
Most Relevant Publications (16+)

145 total publications

Ethics of healthcare robotics: Towards responsible research and innovation

Robotics and Autonomous Systems / Dec 01, 2016

Stahl, B. C., & Coeckelbergh, M. (2016). Ethics of healthcare robotics: Towards responsible research and innovation. Robotics and Autonomous Systems, 86, 152–161. https://doi.org/10.1016/j.robot.2016.08.018

Technology, capabilities and critical perspectives: what can critical theory contribute to Sen’s capability approach?

Ethics and Information Technology / Jan 19, 2011

Zheng, Y., & Stahl, B. C. (2011). Technology, capabilities and critical perspectives: what can critical theory contribute to Sen’s capability approach? Ethics and Information Technology, 13(2), 69–80. https://doi.org/10.1007/s10676-011-9264-8

Morality, Ethics, and Reflection: A Categorization of Normative IS Research

Journal of the Association for Information Systems / Aug 01, 2012

Stahl, B. (2012). Morality, Ethics, and Reflection: A Categorization of Normative IS Research. Journal of the Association for Information Systems, 13(8), 636–656. https://doi.org/10.17705/1jais.00304

Interaction and Transformation on Social Media: The Case of Twitter Campaigns

Social Media + Society / Jan 01, 2018

Housley, W., Webb, H., Williams, M., Procter, R., Edwards, A., Jirotka, M., Burnap, P., Stahl, B. C., Rana, O., & Williams, M. (2018). Interaction and Transformation on Social Media: The Case of Twitter Campaigns. Social Media + Society, 4(1), 205630511775072. https://doi.org/10.1177/2056305117750721

ETHICS, Morality and Critique: An Essay on Enid Mumford¡¯s Socio-Technical Approach

Journal of the Association for Information Systems / Sep 01, 2007

Stahl, B. (2007). ETHICS, Morality and Critique: An Essay on Enid Mumford¡¯s Socio-Technical Approach. Journal of the Association for Information Systems, 8(9), 479–490. https://doi.org/10.17705/1jais.00138

Responsibility for Information Assurance and Privacy

Journal of Organizational and End User Computing / Jul 01, 2004

Stahl, B. C. (2004). Responsibility for Information Assurance and Privacy. Journal of Organizational and End User Computing, 16(3), 59–77. https://doi.org/10.4018/joeuc.2004070104

Responsible Data Governance of Neuroscience Big Data

Frontiers in Neuroinformatics / Apr 24, 2019

Fothergill, B. T., Knight, W., Stahl, B. C., & Ulnicane, I. (2019). Responsible Data Governance of Neuroscience Big Data. Frontiers in Neuroinformatics, 13. https://doi.org/10.3389/fninf.2019.00028

On Quality and Communication: The Relevance of Critical Theory to Health Informatics

Journal of the Association for Information Systems / Mar 01, 2011

Shaw, M., & Stahl, B. (2011). On Quality and Communication: The Relevance of Critical Theory to Health Informatics. Journal of the Association for Information Systems, 12(3), 255–273. https://doi.org/10.17705/1jais.00261

Emerging technologies as the next pandemic?

Ethics and Information Technology / Sep 14, 2020

Stahl, B. C. (2020). Emerging technologies as the next pandemic? Ethics and Information Technology, 23(S1), 135–137. https://doi.org/10.1007/s10676-020-09551-1

Digital Wildfires

ACM Transactions on Information Systems / Apr 20, 2016

Webb, H., Burnap, P., Procter, R., Rana, O., Stahl, B. C., Williams, M., Housley, W., Edwards, A., & Jirotka, M. (2016). Digital Wildfires. ACM Transactions on Information Systems, 34(3), 1–23. https://doi.org/10.1145/2893478

Responsible Innovation

ITNOW / Aug 14, 2014

Stahl, B. C., Jirotka, M., Eden, G., Timmermans, J., & Hartswood, M. (2014). Responsible Innovation. ITNOW, 56(3), 20–22. https://doi.org/10.1093/itnow/bwu068

Developing an Instrument for E-Public Services’ Acceptance Using Confirmatory Factor Analysis

Journal of Organizational and End User Computing / Jul 01, 2012

Alzahrani, A., Stahl, B. C., & Prior, M. (2012). Developing an Instrument for E-Public Services’ Acceptance Using Confirmatory Factor Analysis. Journal of Organizational and End User Computing, 24(3), 18–44. https://doi.org/10.4018/joeuc.2012070102

Discourses on information ethics: The claim to universality

Ethics and Information Technology / Sep 01, 2008

Stahl, B. C. (2008). Discourses on information ethics: The claim to universality. Ethics and Information Technology, 10(2–3), 97–108. https://doi.org/10.1007/s10676-008-9171-9

Exploring the relationships between pedagogy, ethics and technology: building a framework for strategy development

Technology, Pedagogy and Education / Mar 01, 2007

Jefferies, P., Carsten‐Stahl, B., & McRobb, S. (2007). Exploring the relationships between pedagogy, ethics and technology: building a framework for strategy development. Technology, Pedagogy and Education, 16(1), 111–126. https://doi.org/10.1080/14759390601168122

Emancipation in cross-cultural IS research: The fine line between relativism and dictatorship of the intellectual

Ethics and Information Technology / Oct 28, 2006

Stahl, B. C. (2006). Emancipation in cross-cultural IS research: The fine line between relativism and dictatorship of the intellectual. Ethics and Information Technology, 8(3), 97–108. https://doi.org/10.1007/s10676-006-9118-y

Responsible computers? A case for ascribing quasi-responsibility to computers independent of personhood or agency

Ethics and Information Technology / Oct 25, 2006

Stahl, B. C. (2006). Responsible computers? A case for ascribing quasi-responsibility to computers independent of personhood or agency. Ethics and Information Technology, 8(4), 205–213. https://doi.org/10.1007/s10676-006-9112-4

Ramy Ayoub

Marketer, Digital transformation expert, Entrepreneur with a passion for sustainability, and Driven by innovation & creativity that make an impact.
Most Relevant Research Interests
Computer Science Applications
Computer Science Applications
Other Research Interests (25)
Marketing
Branding
Hospitality
Library and Information Sciences
Process Chemistry and Technology
And 20 more
About
Ramy Ayoub is a marketing professional, entrepreneur, and digital transformation expert. In 2007, he founded the Red Sea Academy for Tourism & Entertainment Services, which quickly became a trusted provider of entertainment services for over 20 upscale hotel groups in the EMEA region. Throughout his career, Ramy has consistently demonstrated his marketing prowess, managing operations and serving as a marketing consultant for leading branding activation campaigns globally for art & cultural festivals, hotels, and regional companies. He has a proven track record of generating remarkable results and has helped many organizations achieve their business goals through effective marketing strategies. Ramy‘s exceptional skills and marketing acumen have earned him a reputation as a thought leader in the industry. He is passionate about helping businesses adapt to the rapidly changing digital landscape and has played a key role in driving digital transformation across various sectors. Ramy possesses a rare mix of strategic marketing acumen with excellent leadership, change management, and business process abilities. He has worked with key stakeholders to maximize external relationships with the government and allies to attract fresh business opportunities. Ramy has demonstrated a track record of developing creative marketing strategies and solutions that enable multiple successes through multi-channel sales-driven and customer-centric activities. He has also maximized profitability through sponsorships, loyalty programs, and partnerships with local and international entities. Ramy Ayoub has a proven track record of leading cross-functional teams to support effective communication and result-driven revenue growth Throughout his career with Hilton Hotels, IHG, Sun International Hotels & Casinos, Port Ghalib Resort, UNWTO, Porto Marina, Porto El Soukhna, Jaz Hotels Group, Thomas Cook, TUI Group, TEZ Tours, Odeon Tours, Vodafone Group, Zain Telecom, Raya Telecom, FTV, Ministry Of Sound, Red Bull, Heineken, Bitburger Beer, Al Ahram Beverages, OBOUR LAND, Domty and much more…
Most Relevant Publications (4+)

18 total publications

US Patent History

World Patent Information / Mar 01, 2007

US Patent History. (2007). World Patent Information, 29(1), 67. https://doi.org/10.1016/j.wpi.2006.10.007

US Patent History

World Patent Information / Mar 01, 2007

US Patent History. (2007). World Patent Information, 29(1), 67. https://doi.org/10.1016/j.wpi.2006.10.007

Centenary patent – US 1,000,000

World Patent Information / Sep 01, 2011

Adams, S. R. (2011). Centenary patent – US 1,000,000. World Patent Information, 33(3), 269–274. https://doi.org/10.1016/j.wpi.2011.03.001

Smart card system to track student nutrition

Card Technology Today / Mar 01, 2006

Smart card system to track student nutrition. (2006). Card Technology Today, 18(3), 6–7. https://doi.org/10.1016/s0965-2590(06)70462-5

Sina Soleymani

Ph.D., Postdoctoral Research Fellow, Harvard University
Most Relevant Research Interests
Computer Science Applications
Computer Science Applications
Other Research Interests (16)
Graphene
Metasurfaces
Solar Sails
Parity-Time Symmetric Photonics
Non-Hermitian Photonics
And 11 more
Most Relevant Publications (2+)

12 total publications

Surface Plasmon Polaritons Propagation Along Armchair and Zigzag Single-Wall Carbon Nanotubes With Different Radii

IEEE Transactions on Nanotechnology / Mar 01, 2017

Soleymani, S., & Golmohammadi, S. (2017). Surface Plasmon Polaritons Propagation Along Armchair and Zigzag Single-Wall Carbon Nanotubes With Different Radii. IEEE Transactions on Nanotechnology, 16(2), 307–314. https://doi.org/10.1109/tnano.2017.2663841

Subwavelength Coupling of Surface Plasmon Polaritons Along Parallel Armchair Single-Wall Carbon Nanotubes

IEEE Transactions on Nanotechnology / Nov 01, 2018

Soleymani, S., & Golmohammadi, S. (2018). Subwavelength Coupling of Surface Plasmon Polaritons Along Parallel Armchair Single-Wall Carbon Nanotubes. IEEE Transactions on Nanotechnology, 17(6), 1159–1164. https://doi.org/10.1109/tnano.2018.2855721

Dr. Sandeep Aashish

Assistant Professor, Indian Institute of Technology Patna
Most Relevant Research Interests
Computer Science Applications
Other Research Interests (8)
Theoretical physics
Physics and Astronomy (miscellaneous)
Engineering (miscellaneous)
General Physics and Astronomy
Astronomy and Astrophysics
And 3 more
Most Relevant Publications (1+)

15 total publications

Automatic Test Data Generation-Achieving Optimality Using Ant-Behaviour

International Journal of Information and Education Technology / Jan 01, 2016

Agarwal, S., Gupta, S., & Sabharwal, N. (2016). Automatic Test Data Generation-Achieving Optimality Using Ant-Behaviour. International Journal of Information and Education Technology, 6(2), 117–121. https://doi.org/10.7763/ijiet.2016.v6.669

Hendrik Wolff

Professor, London School of Economics
Most Relevant Research Interests
Computer Science Applications
Other Research Interests (25)
Economics and Econometrics
Economics and Econometrics
Agricultural and Biological Sciences (miscellaneous)
Management, Monitoring, Policy and Law
Nature and Landscape Conservation
And 20 more
About
Hendrik Wolff is Professor of Environmental Economics at The London School of Economics and Political Science (LSE). * Hendrik's main research is in environmental economics, working at the intersection of transportation, air pollution, energy and health. This includes the economic causes and consequences of air pollution; the ”value of time;” the impact of energy conservation policies on electricity consumption; cost benefit analysis of the clean air act and its effects on health; the interactions between climate, local prices, wages and “quality of life; and the economics of Daylight Saving Time. He also developed new econometric estimators for large supply and demand systems that are used in agriculture and energy. He has conducted research projects in Ecuador, Germany, Mexico, Australia, Bangladesh, Ghana, England, Chile and the United States. Hendrik is a Faculty Affiliate of the UW Center for Studies in Demography and Ecology, an IZA Research Fellow, and a CESIfo Research Network Affiliate. He was a visiting professor at Resources for the Future, as well as at LMU Munich, University of Cologne and at IZA, Bonn. * Hendrik’s work has impact on both academia and policy. He won the 2009 Ralph C d’Arge and Allen V. Kneese Award for Outstanding Publication, which is awarded annually for the Best Paper in Environmental and Resource Economics. His research has led to important policy changes by the United Nations and the World Bank on the measurement of indices (the Human Development Index (HDI) and the Ease of Doing Business Index). His work is discussed on television (e.g., ABC News) and international media (e.g., The Economist, The Wall Street Journal). He has successfully obtained external funding from organizations such as the NSF, as well as CSSS and the Royalty Research Fund. In addition, he has been the chair for PhD students and Honors students, many of whom have won multiple awards. The job placements of Hendrik’s students are detailed in his CV. He has also consulted for the U.S. Department of Energy and for the President of the World Bank on important policy issues related to his research. * Hendrik is the director of [SelfDrivingCities.com](https://www.selfdrivingcities.com/) a research lab that connects academic researchers, government, and industry in the urban mobility space
Most Relevant Publications (1+)

37 total publications

Imposing Curvature and Monotonicity on Flexible Functional Forms: An Efficient Regional Approach

Computational Economics / May 14, 2010

Wolff, H., Heckelei, T., & Mittelhammer, R. C. (2010). Imposing Curvature and Monotonicity on Flexible Functional Forms: An Efficient Regional Approach. Computational Economics, 36(4), 309–339. https://doi.org/10.1007/s10614-010-9215-1

Kayvan Najarian

Professor of Comp Med and Bioinf, Emergency Med, and Electrical and Comp Engineering
Most Relevant Research Interests
Computer Science Applications
Other Research Interests (40)
biomedical inforamtics
bioinformatics
singal processing
image processing
machine learning
And 35 more
Most Relevant Publications (7+)

108 total publications

ReDMark: Framework for residual diffusion watermarking based on deep networks

Expert Systems with Applications / May 01, 2020

Ahmadi, M., Norouzi, A., Karimi, N., Samavi, S., & Emami, A. (2020). ReDMark: Framework for residual diffusion watermarking based on deep networks. Expert Systems with Applications, 146, 113157. https://doi.org/10.1016/j.eswa.2019.113157

Extraction of skin lesions from non-dermoscopic images for surgical excision of melanoma

International Journal of Computer Assisted Radiology and Surgery / Mar 24, 2017

Jafari, M. H., Nasr-Esfahani, E., Karimi, N., Soroushmehr, S. M. R., Samavi, S., & Najarian, K. (2017). Extraction of skin lesions from non-dermoscopic images for surgical excision of melanoma. International Journal of Computer Assisted Radiology and Surgery, 12(6), 1021–1030. https://doi.org/10.1007/s11548-017-1567-8

Automated ventricular systems segmentation in brain CT images by combining low-level segmentation and high-level template matching

BMC Medical Informatics and Decision Making / Nov 03, 2009

Chen, W., Smith, R., Ji, S.-Y., Ward, K. R., & Najarian, K. (2009). Automated ventricular systems segmentation in brain CT images by combining low-level segmentation and high-level template matching. BMC Medical Informatics and Decision Making, 9(S1). https://doi.org/10.1186/1472-6947-9-s1-s4

Accounting for Label Uncertainty in Machine Learning for Detection of Acute Respiratory Distress Syndrome

IEEE Journal of Biomedical and Health Informatics / Jan 01, 2019

Reamaroon, N., Sjoding, M. W., Lin, K., Iwashyna, T. J., & Najarian, K. (2019). Accounting for Label Uncertainty in Machine Learning for Detection of Acute Respiratory Distress Syndrome. IEEE Journal of Biomedical and Health Informatics, 23(1), 407–415. https://doi.org/10.1109/jbhi.2018.2810820

A comparative analysis of multi-level computer-assisted decision making systems for traumatic injuries

BMC Medical Informatics and Decision Making / Jan 14, 2009

Ji, S.-Y., Smith, R., Huynh, T., & Najarian, K. (2009). A comparative analysis of multi-level computer-assisted decision making systems for traumatic injuries. BMC Medical Informatics and Decision Making, 9(1). https://doi.org/10.1186/1472-6947-9-2

Private naive bayes classification of personal biomedical data: Application in cancer data analysis

Computers in Biology and Medicine / Feb 01, 2019

Wood, A., Shpilrain, V., Najarian, K., & Kahrobaei, D. (2019). Private naive bayes classification of personal biomedical data: Application in cancer data analysis. Computers in Biology and Medicine, 105, 144–150. https://doi.org/10.1016/j.compbiomed.2018.11.018

Non-linear dynamical signal characterization for prediction of defibrillation success through machine learning

BMC Medical Informatics and Decision Making / Oct 15, 2012

Shandilya, S., Ward, K., Kurz, M., & Najarian, K. (2012). Non-linear dynamical signal characterization for prediction of defibrillation success through machine learning. BMC Medical Informatics and Decision Making, 12(1). https://doi.org/10.1186/1472-6947-12-116

Bianca Trinkenreich

Research Scientist in Human Factors on Software Engineering, Ph.D.
Most Relevant Research Interests
Computer Science Applications
Other Research Interests (11)
Software Engineering
Open Source Software
Measurement
IT Services
GQM+Strategies
And 6 more
Most Relevant Publications (2+)

32 total publications

SINIS: A GQM+Strategies-based approach for identifying goals, strategies and indicators for IT services

Information and Software Technology / Aug 01, 2018

Trinkenreich, B., Santos, G., & Barcellos, M. P. (2018). SINIS: A GQM+Strategies-based approach for identifying goals, strategies and indicators for IT services. Information and Software Technology, 100, 147–164. https://doi.org/10.1016/j.infsof.2018.04.006

Being a Mentor in open source projects

Journal of Internet Services and Applications / Sep 09, 2021

Steinmacher, I., Balali, S., Trinkenreich, B., Guizani, M., Izquierdo-Cortazar, D., Cuevas Zambrano, G. G., Gerosa, M. A., & Sarma, A. (2021). Being a Mentor in open source projects. Journal of Internet Services and Applications, 12(1). https://doi.org/10.1186/s13174-021-00140-z

Paul Schrater

University of Minnesota
Most Relevant Research Interests
Computer Science Applications
Other Research Interests (45)
Artificial Intelligence
Computational Psychology
Cognitive Science
General Neuroscience
Multidisciplinary
And 40 more
Most Relevant Publications (1+)

96 total publications

Spatial contextual classification and prediction models for mining geospatial data

IEEE Transactions on Multimedia / Jun 01, 2002

Shekhar, S., Schrater, P. R., Vatsavai, R. R., Weili Wu, & Chawla, S. (2002). Spatial contextual classification and prediction models for mining geospatial data. IEEE Transactions on Multimedia, 4(2), 174–188. https://doi.org/10.1109/tmm.2002.1017732

Daniel Greenfield

Ph.D. candidate (anticipated Mar 2023) in Biophysics with a focus on quantitative techniques in biomedicine
Most Relevant Research Interests
Computer Science Applications
Other Research Interests (13)
Machine Learning
Medical Devices
Drug Discovery
Edge Computing
Biomedical Optics
And 8 more
Most Relevant Publications (1+)

10 total publications

Wireless Wearable Sensor Paired With Machine Learning for the Quantification of Tissue Oxygenation

IEEE Internet of Things Journal / Dec 15, 2021

Cascales, J. P., Greenfield, D. A., Roussakis, E., Witthauer, L., Li, X., Goss, A., & Evans, C. L. (2021). Wireless Wearable Sensor Paired With Machine Learning for the Quantification of Tissue Oxygenation. IEEE Internet of Things Journal, 8(24), 17557–17567. https://doi.org/10.1109/jiot.2021.3081044

Upavan Gupta, Ph.D.

Analytics Consulting, Data Science, Risk and Prospecting Models, Credit, Mortgage, Property, and Rental Data Expert
Most Relevant Research Interests
Computer Science Applications
Other Research Interests (16)
Game theory
multi-metric optimization
risk minimization
fuzzy logic
stochastic and linear programming
And 11 more
Most Relevant Publications (2+)

12 total publications

A Game Theoretic Approach for Simultaneous Compaction and Equipartitioning of Spatial Data Sets

IEEE Transactions on Knowledge and Data Engineering / Apr 01, 2010

Gupta, U., & Ranganathan, N. (2010). A Game Theoretic Approach for Simultaneous Compaction and Equipartitioning of Spatial Data Sets. IEEE Transactions on Knowledge and Data Engineering, 22(4), 465–478. https://doi.org/10.1109/tkde.2009.110

Variation-aware multimetric optimization during gate sizing

ACM Transactions on Design Automation of Electronic Systems / Aug 01, 2009

Ranganathan, N., Gupta, U., & Mahalingam, V. (2009). Variation-aware multimetric optimization during gate sizing. ACM Transactions on Design Automation of Electronic Systems, 14(4), 1–30. https://doi.org/10.1145/1562514.1562522

Jonathan Tamir

Most Relevant Research Interests
Computer Science Applications
Other Research Interests (11)
Signal processing
machine learning
magnetic resonance imaging
biomedical imaging
clinical translation
And 6 more
Most Relevant Publications (1+)

5 total publications

Memory-Efficient Learning for Large-Scale Computational Imaging

IEEE Transactions on Computational Imaging / Jan 01, 2020

Kellman, M., Zhang, K., Markley, E., Tamir, J., Bostan, E., Lustig, M., & Waller, L. (2020). Memory-Efficient Learning for Large-Scale Computational Imaging. IEEE Transactions on Computational Imaging, 6, 1403–1414. https://doi.org/10.1109/tci.2020.3025735

Vartika Bisht

Univeristy of Utrecht
Most Relevant Research Interests
Computer Science Applications
Computer Science Applications
Other Research Interests (10)
Bioinformatics
General Medicine
General Medicine
Inorganic Chemistry
Organic Chemistry
And 5 more
Most Relevant Publications (2+)

14 total publications

Integration of the Microbiome, Metabolome and Transcriptomics Data Identified Novel Metabolic Pathway Regulation in Colorectal Cancer

International Journal of Molecular Sciences / May 28, 2021

Bisht, V., Nash, K., Xu, Y., Agarwal, P., Bosch, S., Gkoutos, G. V., & Acharjee, A. (2021). Integration of the Microbiome, Metabolome and Transcriptomics Data Identified Novel Metabolic Pathway Regulation in Colorectal Cancer. International Journal of Molecular Sciences, 22(11), 5763. https://doi.org/10.3390/ijms22115763

NFnetFu: A novel workflow for microbiome data fusion

Computers in Biology and Medicine / Aug 01, 2021

Bisht, V., Acharjee, A., & Gkoutos, G. V. (2021). NFnetFu: A novel workflow for microbiome data fusion. Computers in Biology and Medicine, 135, 104556. https://doi.org/10.1016/j.compbiomed.2021.104556

John Joe

Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK
Most Relevant Research Interests
Computer Science Applications
Other Research Interests (73)
microbiology
systems biology
genetics
quantum biology
Genetics
And 68 more
Most Relevant Publications (2+)

95 total publications

MUFINS: multi-formalism interaction network simulator

npj Systems Biology and Applications / Nov 17, 2016

Wu, H., von Kamp, A., Leoncikas, V., Mori, W., Sahin, N., Gevorgyan, A., Linley, C., Grabowski, M., Mannan, A. A., Stoy, N., Stewart, G. R., Ward, L. T., Lewis, D. J. M., Sroka, J., Matsuno, H., Klamt, S., Westerhoff, H. V., McFadden, J., Plant, N. J., & Kierzek, A. M. (2016). MUFINS: multi-formalism interaction network simulator. Npj Systems Biology and Applications, 2(1). https://doi.org/10.1038/npjsba.2016.32

Acorn: A grid computing system for constraint based modeling and visualization of the genome scale metabolic reaction networks via a web interface

BMC Bioinformatics / May 24, 2011

Sroka, J., Bieniasz-Krzywiec, Ł., Gwóźdź, S., Leniowski, D., Łącki, J., Markowski, M., Avignone-Rossa, C., Bushell, M. E., McFadden, J., & Kierzek, A. M. (2011). Acorn: A grid computing system for constraint based modeling and visualization of the genome scale metabolic reaction networks via a web interface. BMC Bioinformatics, 12(1). https://doi.org/10.1186/1471-2105-12-196

Example computer science applications projects

How can companies collaborate more effectively with researchers, experts, and thought leaders to make progress on computer science applications?

Optimizing Supply Chain Management

An academic researcher in Computer Science Applications can help companies optimize their supply chain management processes. By analyzing data and applying algorithms, they can identify bottlenecks, streamline operations, and reduce costs. They can also develop predictive models to forecast demand and optimize inventory management, ensuring efficient and timely delivery of products.

Enhancing Cybersecurity Measures

Collaborating with a Computer Science Applications researcher can enhance a company's cybersecurity measures. They can analyze the company's existing security infrastructure, identify vulnerabilities, and develop robust solutions to protect against cyber threats. Researchers can also develop advanced encryption algorithms and implement secure authentication systems to safeguard sensitive data and prevent unauthorized access.

Implementing Machine Learning for Personalized Recommendations

By collaborating with an academic researcher in Computer Science Applications, companies can implement machine learning algorithms for personalized recommendations. Researchers can analyze customer data, identify patterns, and develop recommendation systems that provide personalized product suggestions, improving customer satisfaction and driving sales. These algorithms can also be used for targeted marketing campaigns, increasing customer engagement and retention.

Developing Natural Language Processing Applications

Academic researchers in Computer Science Applications can help companies develop natural language processing applications. They can build chatbots and virtual assistants that can understand and respond to customer queries, improving customer support and reducing response time. Researchers can also develop sentiment analysis algorithms to analyze customer feedback and sentiment on social media, helping companies understand customer preferences and improve their products and services.

Optimizing Data Analysis and Visualization

Collaborating with a Computer Science Applications researcher can optimize a company's data analysis and visualization processes. Researchers can develop algorithms and tools to process and analyze large datasets, extract meaningful insights, and visualize data in a clear and intuitive manner. This can help companies make data-driven decisions, identify trends, and uncover hidden patterns, leading to improved business strategies and outcomes.