Sundar Rengasamy
QualificationDr. Sundar Rengasamy is currently working as an Assistant Professor in IT systems and Analytics at Indian Institute of Management (IIM) Jammu. Before joining IIM Jammu, he worked as an Assistant Professor at GITAM School of Business Bengaluru. He received his Doctoral degree in Machine Learning from National Institute of Technology, Tiruchirappalli. He also holds an M.E. degree in Industrial Engineering from College of Engineering Guindy, Chennai. He was awarded a silver medal for obtaining the second highest CGPA in M.E.
His research interests are Machine Learning algorithms, Optimization Techniques, and Data Analytics and their applications in the management field. He has published research articles in International Journals like Applied Soft Computing, Swarm and Evolutionary Computation, Engineering applications in Artificial Intelligence, and Defense Science Journal.
- Ph.D. – National Institute of Technology, Tiruchirappalli.
- M.E. (Industrial Engineering) – College of Engineering Guindy, Anna University, Chennai.
- B.E. (Mechanical Engineering) – Government College of Engineering, Tirunelveli.
- IIM Jammu (Current Employer)
- GITAM School of Business Bengaluru (Ex-Employer)
- CETHAR Limited, Tiruchirappalli (Ex-Employer)
- R, S. & M, P. (2022). K-means Laplacian clustering revisited. Engineering applications of Artificial Intelligence, 107(1), (SCI/SSCI/ESCI,Scopus), DOI : https://doi.org/10.1016/j.engappai.2021.104535
- R, S. & M, P. (2021). PSO Based data clustering with a different perception. Swarm and Evolutionary Computation, 64(1), (SCI/SSCI/ESCI,Scopus), DOI : https://doi.org/10.1016/j.swevo.2021.100895
- Viswanathan, H. K., M, P., R, S. & Vilvanathan, L. (2020). A modified boosted support vector machine to rate banks. Benchmarking, 28(1), (ABDC,SCI/SSCI/ESCI,Scopus), DOI : https://doi.org/10.1108/BIJ-01-2020-0006
- R, S. & M, P. (2019). Performance enhanced Boosted SVM for Imbalance datasets. Applied Soft Computing, 83(1), (SCI/SSCI/ESCI,Scopus), DOI : https://doi.org/10.1016/j.asoc.2019.105601
- K, P. P., M, R., R, S. & R, B. (2018). Multi-objective optimisation of multi-robot task allocation with precedence constraints. Defence Science Journal, 68(2), (SCI/SSCI/ESCI,Scopus), DOI : https://doi.org/10.14429/dsj.68.11187
- Machine Learning Techniques
- Business Analytics
- Data Science
- Business Research Methods
- Operations Research
- Advanced Operations Research
- Endowment Award for Best performance in Academics, DoIE, Anna University Chennai.