Satyaki Roy, Ph.D.

Assistant Professor, Mathematical Sciences

Contact

301 Sparkman Drive
Shelby Center
Room 201N
Huntsville, AL 35899
Campus Map

256.824.6879
sr0215@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 and
    fault-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 of
    gene regulatory networks. In 2017 IEEE International Conference on Communications (ICC) (pp. 1-6). IEEE.