Contact Information
347 Illini Hall
1409 W Green
M/C 382
Urbana, IL 61801
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.
Research Interests
Applied Mathematics, financial engineering, big data, traffic, precision agriculture, Internet of Things
Additional Campus Affiliations
Professor, Industrial and Enterprise Systems Engineering
Professor, Mathematics
Director of Graduate Admissions, Mathematics
Professor, Statistics
Professor, Biomedical and Translational Sciences
Professor, Center for Digital Agriculture, National Center for Supercomputing Applications (NCSA)
External Links
Recent Publications
Alkurdi, A., He, M., Cerna, J., Clore, J., Sowers, R., Hsiao-Wecksler, E. T., & Hernandez, M. E. (2025). Extending Anxiety Detection from Multimodal Wearables in Controlled Conditions to Real-World Environments. Sensors, 25(4), Article 1241. https://doi.org/10.3390/s25041241
Alkurdi, A., Clore, J., Sowers, R., Hsiao-Wecksler, E. T., & Hernandez, M. E. (2025). Resilience of Machine Learning Models in Anxiety Detection: Assessing the Impact of Gaussian Noise on Wearable Sensors. Applied Sciences (Switzerland), 15(1), Article 88. https://doi.org/10.3390/app15010088
He, M., Cerna, J., Alkurdi, A., Dogan, A., Zhao, J., Clore, J. L., Sowers, R. B., Hsiao-Wecksler, E. T., & Hernandez, M. E. (2024). Physical, Social and Cognitive Stressor Identification using Electrocardiography-derived Features and Machine Learning from a Wearable Device. In 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024 - Proceedings (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC53108.2024.10782654
Kaur, R., Motl, R. W., Sowers, R., & Hernandez, M. E. (2023). A Vision-Based Framework for Predicting Multiple Sclerosis and Parkinson's Disease Gait Dysfunctions - A Deep Learning Approach. IEEE Journal of Biomedical and Health Informatics, 27(1), 190-201. https://doi.org/10.1109/JBHI.2022.3208077
Kaur, R., Levy, J., Motl, R. W., Sowers, R., & Hernandez, M. E. (2023). Deep Learning for Multiple Sclerosis Differentiation Using Multi-Stride Dynamics in Gait. IEEE Transactions on Biomedical Engineering, 70(7), 2181-2192. https://doi.org/10.1109/TBME.2023.3238680