Contact Information
Department of Mathematics
377 Altgeld Hall, MC-382
1409 W. Green Street, Urbana, IL 61801
Professor & Associate Head of Undergraduate Programs
Department of Industrial and Enterprise Systems Engineering
104C Transportation Building
Research Areas
Biography
My interests are in various applied problems which have impact. My formal training is in electrical engineering and applied mathematics. I find that some of the more interesting problems I have worked on have come from looking at the real world with a strongly quantitative toolset. Along the way, I have spent time at a hedge fund and consulted for private industry and the U.S. Government. Finally, at the moment I am the associate head for undergraduate studies in the department of Industrial and Enterprise Systems Engineering.
Research Interests
Applied Mathematics, financial engineering, big data, traffic, precision agriculture, Internet of Things
Education
Ph.D. Maryland, 1991
Additional Campus Affiliations
Professor, Industrial and Enterprise Systems Engineering
Associate Head for Undergraduate Programs, Industrial and Enterprise Systems Engineering
Professor, Statistics
Professor, Center for Digital Agriculture, National Center for Supercomputing Applications (NCSA)
External Links
Recent Publications
Kaur, R., Schaye, C., Thompson, K., Yee, D. C., Zilz, R., Sreenivas, R. S., & Sowers, R. B. (2021). Machine learning and price-based load scheduling for an optimal IoT control in the smart and frugal home. Energy and AI, 3, [100042]. https://doi.org/10.1016/j.egyai.2020.100042
Carmody, D., & Sowers, R. (Accepted/In press). Topological Analysis of Traffic Pace via Persistent Homology. Journal of Physics: Complexity, 2(2), [025007]. https://doi.org/10.1088/2632-072X/abc96a
Hu, Y., Bishnoi, A., Kaur, R., Sowers, R., & Hernandez, M. E. (2020). Exploration of Machine Learning to Identify Community Dwelling Older Adults with Balance Dysfunction Using Short Duration Accelerometer Data. In 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society: Enabling Innovative Technologies for Global Healthcare, EMBC 2020 (pp. 812-815). [9175871] (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 2020-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC44109.2020.9175871
Kaur, R., Korolkov, M., Hernandez, M. E., & Sowers, R. (2020). Automatic Identification of Brain Independent Components in Electroencephalography Data Collected while Standing in a Virtually Immersive Environment - A Deep Learning-Based Approach. In 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society: Enabling Innovative Technologies for Global Healthcare, EMBC 2020 (pp. 95-98). [9175741] (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 2020-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC44109.2020.9175741
Kaur, R., Chen, Z., Motl, R., Hernandez, M. E., & Sowers, R. (Accepted/In press). Predicting Multiple Sclerosis from Gait Dynamics Using an Instrumented Treadmill – A Machine Learning Approach. IEEE Transactions on Biomedical Engineering. https://doi.org/10.1109/TBME.2020.3048142
