Work with thought leaders and academic experts in theoretical computer science
Companies can greatly benefit from collaborating with experts in Theoretical Computer Science. These researchers have a deep understanding of algorithms, complexity theory, and cryptography, which can be applied to various industries. They can help companies optimize their processes, develop efficient algorithms, enhance data security, and solve complex computational problems. Additionally, their expertise can drive innovation, improve decision-making, and provide valuable insights for developing cutting-edge technologies. By working with Theoretical Computer Science researchers, companies can gain a competitive edge, improve efficiency, and achieve breakthrough solutions.
Experts on NotedSource with backgrounds in theoretical computer science include Edoardo Airoldi, Osaye Fadekemi, PhD, Athul Prasad, Suhang Wang, Mark Ryan, Dr. Abdussalam Elhanashi, Asst. Prof. Eng. Davide Verzotto, Ph.D., Kayvan Najarian, Bernd Stahl, Upavan Gupta, Ph.D., Marian Grendar, Ph.D., and Piotr Sobolewski.
Edoardo Airoldi
Professor of Statistics & Data Science Temple University & PI, Harvard University
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Other Research Interests (57)
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Most Relevant Publications (1+)
106 total publications
Scalable estimation strategies based on stochastic approximations: classical results and new insights
Statistics and Computing / Jun 11, 2015
Toulis, P., & Airoldi, E. M. (2015). Scalable estimation strategies based on stochastic approximations: classical results and new insights. Statistics and Computing, 25(4), 781–795. https://doi.org/10.1007/s11222-015-9560-y
Osaye Fadekemi, PhD
Assistant Professor of Mathematics at Alabama State University with expertise in Graph Theory and Network Modeling
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Other Research Interests (16)
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Most Relevant Publications (2+)
7 total publications
Average eccentricity,k -packing andk -domination in graphs
Discrete Mathematics / May 01, 2019
Dankelmann, P., & Osaye, F. J. (2019). Average eccentricity,<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll" id="d1e86" altimg="si36.gif"><mml:mi>k</mml:mi></mml:math>-packing and<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll" id="d1e91" altimg="si36.gif"><mml:mi>k</mml:mi></mml:math>-domination in graphs. Discrete Mathematics, 342(5), 1261–1274. https://doi.org/10.1016/j.disc.2019.01.004
The average eccentricity of a graph with prescribed girth
Discrete Mathematics / Dec 01, 2022
Osaye, F. J. (2022). The average eccentricity of a graph with prescribed girth. Discrete Mathematics, 345(12), 113066. https://doi.org/10.1016/j.disc.2022.113066
Athul Prasad
5G / 6G Technology and Ventures at Samsung; D.Sc. (Tech), MBA
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Other Research Interests (41)
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Most Relevant Publications (1+)
75 total publications
Quasi-universal k-regular sequences
Theoretical Computer Science / Nov 01, 2021
Honkala, J. (2021). Quasi-universal k-regular sequences. Theoretical Computer Science, 891, 84–89. https://doi.org/10.1016/j.tcs.2021.08.028
Suhang Wang
Professor at Pennsylvania State University
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Other Research Interests (28)
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Most Relevant Publications (6+)
92 total publications
Feature Selection
ACM Computing Surveys / Dec 06, 2017
Li, J., Cheng, K., Wang, S., Morstatter, F., Trevino, R. P., Tang, J., & Liu, H. (2017). Feature Selection. ACM Computing Surveys, 50(6), 1–45. https://doi.org/10.1145/3136625
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
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
Random-Forest-Inspired Neural Networks
ACM Transactions on Intelligent Systems and Technology / Oct 29, 2018
Wang, S., Aggarwal, C., & Liu, H. (2018). Random-Forest-Inspired Neural Networks. ACM Transactions on Intelligent Systems and Technology, 9(6), 1–25. https://doi.org/10.1145/3232230
Understanding and Identifying Rhetorical Questions in Social Media
ACM Transactions on Intelligent Systems and Technology / Jan 10, 2018
Ranganath, S., Hu, X., Tang, J., Wang, S., & Liu, H. (2018). Understanding and Identifying Rhetorical Questions in Social Media. ACM Transactions on Intelligent Systems and Technology, 9(2), 1–22. https://doi.org/10.1145/3108364
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
Mark Ryan
Digital Ethics Researcher at Wageningen Economic Research
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Other Research Interests (39)
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Most Relevant Publications (1+)
40 total publications
In defence of digital contact-tracing: human rights, South Korea and Covid-19
International Journal of Pervasive Computing and Communications / Aug 06, 2020
Ryan, M. (2020). In defence of digital contact-tracing: human rights, South Korea and Covid-19. International Journal of Pervasive Computing and Communications, 16(4), 383–407. https://doi.org/10.1108/ijpcc-07-2020-0081
Dr. Abdussalam Elhanashi
Researcher at University of Pisa
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Other Research Interests (23)
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Most Relevant Publications (1+)
28 total publications
An IoT System for Social Distancing and Emergency Management in Smart Cities Using Multi-Sensor Data
Algorithms / Oct 07, 2020
Fedele, R., & Merenda, M. (2020). An IoT System for Social Distancing and Emergency Management in Smart Cities Using Multi-Sensor Data. Algorithms, 13(10), 254. https://doi.org/10.3390/a13100254
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
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Other Research Interests (20)
About
Most Relevant Publications (2+)
40 total publications
Editorial: Special Issue on Algorithms for Sequence Analysis and Storage
Algorithms / Mar 25, 2014
Mäkinen, V. (2014). Editorial: Special Issue on Algorithms for Sequence Analysis and Storage. Algorithms, 7(1), 186–187. https://doi.org/10.3390/a7010186
Filtering Degenerate Patterns with Application to Protein Sequence Analysis
Algorithms / May 22, 2013
Comin, M., & Verzotto, D. (2013). Filtering Degenerate Patterns with Application to Protein Sequence Analysis. Algorithms, 6(2), 352–370. https://doi.org/10.3390/a6020352
Kayvan Najarian
Professor of Comp Med and Bioinf, Emergency Med, and Electrical and Comp Engineering
Most Relevant Research Interests
Other Research Interests (59)
Most Relevant Publications (1+)
106 total publications
Homomorphic Encryption for Machine Learning in Medicine and Bioinformatics
ACM Computing Surveys / Aug 25, 2020
Wood, A., Najarian, K., & Kahrobaei, D. (2020). Homomorphic Encryption for Machine Learning in Medicine and Bioinformatics. ACM Computing Surveys, 53(4), 1–35. https://doi.org/10.1145/3394658
Bernd Stahl
Director of the Centre for Computing and Social Responsibility
Most Relevant Research Interests
Other Research Interests (67)
Most Relevant Publications (3+)
145 total publications
The Ethics of Computing
ACM Computing Surveys / Feb 22, 2016
Stahl, B. C., Timmermans, J., & Mittelstadt, B. D. (2016). The Ethics of Computing. ACM Computing Surveys, 48(4), 1–38. https://doi.org/10.1145/2871196
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
Tomorrow’s ethics and today’s response: An investigation into the ways information systems professionals perceive and address emerging ethical issues
Information Systems Frontiers / Mar 29, 2014
Wakunuma, K. J., & Stahl, B. C. (2014). Tomorrow’s ethics and today’s response: An investigation into the ways information systems professionals perceive and address emerging ethical issues. Information Systems Frontiers, 16(3), 383–397. https://doi.org/10.1007/s10796-014-9490-9
Upavan Gupta, Ph.D.
Analytics Consulting, Data Science, Risk and Prospecting Models, Credit, Mortgage, Property, and Rental Data Expert
Most Relevant Research Interests
Other Research Interests (15)
Most Relevant Publications (1+)
12 total publications
Multievent Crisis Management Using Noncooperative Multistep Games
IEEE Transactions on Computers / May 01, 2007
Gupta, U., & Ranganathan, N. (2007). Multievent Crisis Management Using Noncooperative Multistep Games. IEEE Transactions on Computers, 56(5), 577–589. https://doi.org/10.1109/tc.2007.1023
Marian Grendar, Ph.D.
Most Relevant Research Interests
Other Research Interests (66)
Most Relevant Publications (1+)
117 total publications
The Pólya information divergence
Information Sciences / Nov 01, 2010
Grendár, M., & Niven, R. K. (2010). The Pólya information divergence. Information Sciences, 180(21), 4189–4194. https://doi.org/10.1016/j.ins.2010.06.031
Piotr Sobolewski
Most Relevant Research Interests
Other Research Interests (3)
Most Relevant Publications (1+)
2 total publications
SCR: simulated concept recurrence - a non-supervised tool for dealing with shifting concept
Expert Systems / Nov 22, 2013
Sobolewski, P., & Woźniak, M. (2013). SCR: simulated concept recurrence - a non-supervised tool for dealing with shifting concept. Expert Systems, 34(5), e12059. Portico. https://doi.org/10.1111/exsy.12059
Example theoretical computer science projects
How can companies collaborate more effectively with researchers, experts, and thought leaders to make progress on theoretical computer science?
Optimizing Supply Chain Management
A Theoretical Computer Science expert can develop algorithms to optimize supply chain management, reducing costs and improving efficiency. By analyzing complex data and considering various factors such as demand, inventory, and transportation, they can create models that minimize delays, optimize routes, and streamline operations.
Enhancing Data Security
With their knowledge of cryptography and data encryption, Theoretical Computer Science researchers can help companies enhance their data security measures. They can develop robust encryption algorithms, design secure communication protocols, and identify vulnerabilities in existing systems to prevent data breaches and unauthorized access.
Machine Learning and AI
Theoretical Computer Science experts can contribute to the development of machine learning and AI algorithms. They can design efficient algorithms for training models, improve the accuracy of predictions, and optimize computational resources. Their expertise can help companies leverage the power of AI to automate processes, make data-driven decisions, and improve customer experiences.
Optimizing Financial Trading Strategies
By applying algorithms and mathematical models, Theoretical Computer Science researchers can optimize financial trading strategies. They can analyze market data, identify patterns, and develop algorithms that maximize returns and minimize risks. Their expertise can help companies make informed investment decisions and achieve better financial outcomes.
Solving Complex Computational Problems
Theoretical Computer Science experts excel in solving complex computational problems. They can develop algorithms and mathematical models to tackle challenges in various domains, such as optimization, scheduling, and network design. By collaborating with them, companies can find innovative solutions to their most challenging problems.