Faculty

Professor Srikrishnan Divakaran is a Computational Data Scientist with over 25 years of research and teaching experience, complemented by over five years of industry experience in computing and finance with leading international companies. He has taught a wide range of courses in Computer Science and related disciplines, such as Combinatorial Optimisation, Bioinformatics/Computational Biology, and Data Science. His research focuses on designing, analysing, and modelling algorithms for optimisation problems with applications in Computational Biology, Combinatorial Optimisation, and Data Science.

Professor Divakaran is a Theoretical Computer Scientist with research interests in designing and analysing algorithms for problems with applications in Computational Biology, Combinatorial Optimisation, and Data Science.

In Data Science, Professor Divakaran’s research is in the design and analysis of (i) Decision Tree (DT) based methods for problems in Sports Data Analytics (SDA), (ii) Image Registration (IR) algorithms in medical imaging, and (iii) Machine Learning (ML) and Deep Neural Network (DNN) based models for Atmospheric Correction (AC). In Computational Biology, Professor Divakaran’s research is focused on the development and analysis of approximation algorithms and heuristics for Sequence Alignment and Construction of Phylogenetic and Evolutionary Trees. In Combinatorial Optimisation, Professor Divakaran’s research focuses on constructing and analysing approximation algorithms for resource allocation problems.

• Sharma, S., Divakaran, S., Kaya, T. et al. Athletic signature: predicting the next game lineup in collegiate basketball. Neural Computing & Applications 36, 21761–21780 (2024). https://doi.org/10.1007/s00521-024-10383-z
• Shah, M., Raval, M. S., Divakaran, S., Dhar, D., and Parmar, H. (2023). SAAC-Net: Deep neural network-based model for atmospheric correction in remote sensing. International Journal of Remote Sensing, 44(23), 7365–7389. https://doi.org/10.1080/01431161.2023.2282407
• Sharma, S. U., Divakaran, S., Kaya, T., and Raval, M. (2022). A hybrid approach for interpretable game performance prediction in basketball. In 2022 International Joint Conference on Neural Networks (IJCNN) (pp. 01-08). IEEE. https://doi.org/10.1109/IJCNN55064.2022.9892583
• Divakaran, S., Saks, M. An Online Algorithm for a Problem in Scheduling with Set-ups and Release Times. Algorithmica 60, 301–315 (2011). https://doi.org/10.1007/s00453-009-9337-9
• Srikrishnan Divakaran, Approximation algorithms for constrained generalized tree alignment problem, Discrete Applied Mathematics, Volume 157, Issue 7, 2009, Pages 1407-1422, ISSN 0166-218X, https://doi.org/10.1016/j.dam.2008.10.009.
• Srikrishnan Divakaran, Michael Saks, Approximation algorithms for problems in scheduling with set-ups, Discrete Applied Mathematics, Volume 156, Issue 5, 2008, Pages 719-729, ISSN 0166-218X, https://doi.org/10.1016/j.dam.2007.08.010.
• Rangarajan, M., Divakaran, S., Nguyen, T., and Iftode, L. (1999, June 25). Multi-threaded HLRC DSM. 1st Workshop on Software Distributed Shared Memory, Rhodes, Greece.
• Divakaran, S., and Saks, M. (2000). An online scheduling problem with job set-ups. Center for Discrete Mathematics & Theoretical Computer Science.

• Discrete Mathematics
• Design and Analysis of Algorithms
• Network and Combinatorial Optimisation
• Foundations of Data Science
• Introduction to Computational Thinking