Work with thought leaders and academic experts in computational mathematics
Companies can greatly benefit from working with experts in Computational Mathematics. These researchers have a deep understanding of data analysis, optimization, and machine learning techniques. By collaborating with them, companies can enhance their decision-making processes, improve efficiency, and gain a competitive edge. Computational Mathematics experts can help companies solve complex problems, develop innovative algorithms, and optimize various processes. They can also assist in developing predictive models, improving risk management strategies, and identifying patterns and trends in large datasets. Overall, partnering with a Computational Mathematics researcher can lead to improved data-driven decision-making, increased productivity, and better business outcomes.
Experts on NotedSource with backgrounds in computational mathematics include Emmanouil Mentzakis, Edoardo Airoldi, Tim Osswald, Jeffrey Townsend, Ariel Aptekmann, Ping Luo, Panos Ipeirotis, Dr. Abdussalam Elhanashi, Asst. Prof. Eng. Davide Verzotto, Ph.D., Ernesto Lowy, Jonathan Tamir, and Niko Popitsch.
Emmanouil Mentzakis
Health Economist, Professor at City University of London
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Other Research Interests (35)
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Most Relevant Publications (1+)
46 total publications
Characterizing dynamic communication in online eating disorder communities: a multiplex network approach
Applied Network Science / Apr 17, 2019
Wang, T., Brede, M., Ianni, A., & Mentzakis, E. (2019). Characterizing dynamic communication in online eating disorder communities: a multiplex network approach. Applied Network Science, 4(1). https://doi.org/10.1007/s41109-019-0125-4
Edoardo Airoldi
Professor of Statistics & Data Science Temple University & PI, Harvard University
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Most Relevant Publications (2+)
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
A Network Analysis Model for Disambiguation of Names in Lists
Computational and Mathematical Organization Theory / Jul 01, 2005
Malin, B., Airoldi, E., & Carley, K. M. (2005). A Network Analysis Model for Disambiguation of Names in Lists. Computational and Mathematical Organization Theory, 11(2), 119–139. https://doi.org/10.1007/s10588-005-3940-3
Tim Osswald
Polymers Professor - University of Wisconsin
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117 total publications
Analysis of fiber damage mechanisms during processing of reinforced polymer melts
Engineering Analysis with Boundary Elements / Jul 01, 2002
Hernandez, J. P., Raush, T., Rios, A., Strauss, S., & Osswald, T. A. (2002). Analysis of fiber damage mechanisms during processing of reinforced polymer melts. Engineering Analysis with Boundary Elements, 26(7), 621–628. https://doi.org/10.1016/s0955-7997(02)00018-8
Jeffrey Townsend
Professor of Biostatistics and Ecology & Evolutionary Biology
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Most Relevant Publications (4+)
207 total publications
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
H-CLAP: hierarchical clustering within a linear array with an application in genetics
Statistical Applications in Genetics and Molecular Biology / Jan 01, 2015
Ghosh, S., & Townsend, J. P. (2015). H-CLAP: hierarchical clustering within a linear array with an application in genetics. Statistical Applications in Genetics and Molecular Biology, 14(2). https://doi.org/10.1515/sagmb-2013-0076
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
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
Ariel Aptekmann
Bioinformatician at Hackensack Meridian Hospital Center for Discovery and Innovation
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Other Research Interests (37)
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Most Relevant Publications (1+)
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
Ping Luo
Postdoctoral Researcher at Princess Margaret Cancer Centre with experience in deep learning
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Other Research Interests (26)
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Most Relevant Publications (1+)
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
Panos Ipeirotis
Professor at New York University
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Other Research Interests (37)
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Most Relevant Publications (1+)
97 total publications
Introduction to the Special Issue on EC’12
ACM Transactions on Economics and Computation / Mar 27, 2015
Leyton-Brown, K., & Ipeirotis, P. (Eds.). (2015). Introduction to the Special Issue on EC’12. ACM Transactions on Economics and Computation, 3(1), 1–2. https://doi.org/10.1145/2742678
Dr. Abdussalam Elhanashi
Researcher at University of Pisa
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Other Research Interests (24)
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Most Relevant Publications (1+)
31 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 (22)
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Most Relevant Publications (3+)
40 total publications
The Irredundant Class Method for Remote Homology Detection of Protein Sequences
Journal of Computational Biology / Dec 01, 2011
Comin, M., & Verzotto, D. (2011). The Irredundant Class Method for Remote Homology Detection of Protein Sequences. Journal of Computational Biology, 18(12), 1819–1829. https://doi.org/10.1089/cmb.2010.0171
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
Jonathan Tamir
Most Relevant Research Interests
Other Research Interests (11)
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
Example computational mathematics projects
How can companies collaborate more effectively with researchers, experts, and thought leaders to make progress on computational mathematics?
Optimizing Supply Chain Management
A Computational Mathematics expert can develop algorithms to optimize supply chain management, reducing costs and improving efficiency. By analyzing data on inventory levels, transportation routes, and demand patterns, they can identify bottlenecks and suggest strategies to streamline operations.
Predictive Maintenance in Manufacturing
By analyzing sensor data and historical maintenance records, a Computational Mathematics researcher can develop predictive models to identify potential equipment failures in manufacturing processes. This can help companies schedule maintenance activities proactively, minimizing downtime and reducing maintenance costs.
Fraud Detection in Financial Services
Using advanced machine learning techniques, a Computational Mathematics expert can develop models to detect fraudulent activities in financial transactions. By analyzing patterns and anomalies in large datasets, they can help financial institutions identify and prevent fraudulent transactions, protecting both the company and its customers.
Optimizing Energy Consumption
A Computational Mathematics researcher can analyze energy consumption data and develop optimization algorithms to minimize energy usage in various industries. This can lead to significant cost savings and environmental benefits by identifying energy-efficient practices and optimizing resource allocation.
Improving Healthcare Analytics
By analyzing healthcare data, including patient records, medical imaging, and genomic data, a Computational Mathematics expert can develop models to improve disease diagnosis, treatment planning, and patient outcomes. This can help healthcare companies provide personalized and effective care to their patients.