Satyaki Roy, Ph.D. Assistant Professor, Mathematical Sciences Contact 301 Sparkman DriveShelby CenterRoom 201NHuntsville, AL 35899 Campus Map 256.824.6879sr0215@uah.edu Biography Satyaki Roy is currently an Assistant Professor of Biostatistics in the Department of Mathematical Sciences. He obtained his Ph.D. in Computer Science from Missouri University of Science and Technology, USA, specializing in the application of graph theory for biological network modeling. Subsequently, he served as a postdoctoral research associate in the Department of Genetics at the University of North Carolina, USA, where he contributed to the development of machine learning-based disease inference models. Dr. Roy's research resides at the intersection of machine learning and statistical modeling, epidemiology, and network theory. His work is dedicated to constructing computational tools that address pivotal questions in public health. Curriculum Vitae https://scholar.google.com/citations?hl=en&user=1LqaiF4AAAAJ&view_op=list_works&sortby=pubdate. Education Doctoral Studies, Missouri University of Sciences and Technology, 2019 Masters of Science in Computer Science, St. Xavier's College, Kolkata, West Bengal, India, 2014 Honors & Awards College of Engineering and Computing (CEC) Dean’s Ph.D. Scholar Award 2019, Missouri University of Science and Technology in recognition of his scholarship excellence, academic success, and service contribution to Missouri University of Science and Technology Academic Achievement Award 2014–19 from Department of Computer Science at Missouri University of Science and Technology Expertise Machine & statistical learning, bioinfor- matics, genomics, epidemiology, network theory, algorithms, and IoT Recent Publications S. Roy, N. Ghosh, N. Uplavikar, & P. Ghosh (2023). Towards a Unified Pandemic Management Architecture: Survey, Challenges, and Future Directions. ACM Computing Surveys, 56(2), 1-32. S. Roy, P. Bose, & P. Ghosh. (2022). Curbing pandemic through evolutionary algorithm-based priority aware mobility scheduling. IEEE Transactions on Intelligent Transportation Systems, 24(4), 3759-3768. S. Roy, S. Sheikh, & T. Furey (2021). A machine learning approach identifies 5-ASA and ulcerative colitis as being linked with higher COVID-19 mortality in patients with IBD. Scientific reports, 11(1), 16522. S. Roy, P. Biswas, and P. Ghosh. "Quantifying mobility and mixing propensity in the spatiotemporal context of a pandemic spread." IEEE Transactions on Emerging Topics in Computational Intelligence 5.3 (2021): 321-331. S. Roy and P. Ghosh. "Factors affecting COVID-19 infected and death rates inform lockdown-related policymaking." PloS one 15.10 (2020): e0241165. S. Roy, P. Ghosh, D. Barua, & S. K. Das. (2020). Motifs enable communication efficiency andfault-tolerance in transcriptional networks. Scientific reports, 10(1), 9628. S. Roy, M. Raj, P. Ghosh & S. K. Das (2017, May). Role of motifs in topological robustness ofgene regulatory networks. In 2017 IEEE International Conference on Communications (ICC) (pp. 1-6). IEEE.