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Dr. Lakshmanan Kailasam
Assistant Professor
Department of Computer Science and Engineering
91-542-716-5337 (O)
Area of Interest: 
Reinforcement Learning, Optimization

B.Tech Courses
CSO 101 Computer Programming

M.Tech Courses
CSE 523 Intelligent systems
Ph.D Courses
CS-7025 Selected Topics in Artificial Intelligence
CS-7001 Selected Topics in Machine Learning
CS-7021 Advanced Topics in Algorithms
CS-7013 Selected Topics in Social Network Analysis
CS-7008 Advanced Computational Mathematics

1. AK Singh, K Lakshmanan, PILHNB: Popularity, interests, location used hidden Naive Bayesian-based model for link prediction in dynamic social networks, Neurocomputing 461, 562-576, 2021

2. AK Singh, L Kailasam, Link prediction-based influence maximization in online social networks, Neurocomputing 453, 151-163, 2021

3. A Sharma, K Lakshmanan, R Gupta, A Gupta Multi-Time Scale Smoothed Functional With Nesterov’s Acceleration, IEEE Access 9, 113489-113499, 2021

4. A Kumar, SK Singh, K Lakshmanan, S Saxena, S Shrivastava A Novel Cloud-Assisted Secure Deep Feature Classification Framework for Cancer Histopathology Images, ACM Transactions on Internet Technology (TOIT) 21 (2), 1-22, 2021

5. A Sharma, R Gupta, K Lakshmanan, A Gupta Transition Based Discount Factor for Model Free Algorithms in Reinforcement Learning, Symmetry 13 (7), 1197, 2021

6. R Gupta, K Lakshmanan, A Sah, Beam alignment for mmWave using non-stationary bandits, IEEE Communications Letters, 24 (11), 2619-2622 2020.

7. B Mukhoty, R Gupta, K Lakshmanan, M Kumar, A parameter-free affinity based clustering, Applied Intelligence, pp. 1-14, 2020.

8. Abhinav Kumar, Sanjay Kumar Singh, Sonal Saxena, Amit Kumar Singh, Sameer Shrivastava, K Lakshmanan, Neeraj Kumar, Raj Kumar Singh, CoMHisP: A Novel Feature Extractor for Histopathological Image Classification Based on Fuzzy SVM With Within-Class Relative Density IEEE Transactions on Fuzzy Systems, 29 (1), 103-117, 2020

9. Abhinav Kumar, Sanjay Kumar Singh, Sonal Saxena, K.Lakshmanan, Arun Kumar Sangaiah, Himanshu Chauhan, Sameer Shrivastava and Raj Kumar Singh, Deep feature learning for histopathological image classification of canine mammary tumors and human breast cancer, Information Sciences Vol. 508, pp. 405-421, January 2020.

10. Phanideep Gampa, Satwik Kondamudi and K. Lakshmanan, A Tractable Algorithm for Finite-Horizon Continuous Reinforcement Learning, ICoIAS'2019 Singapore.

11. K. Lakshmanan, Accelerated Reinforcement Learning, IEEE INDICON 2017

12. K. Lakshmanan and S. Bhatnagar, Quasi-Newton Smoothed Functional Algorithms for Unconstrained and Constrained Simulation Optimization, Computational Optimization and Applications (COAP), Vol 66 Issue 3, pp. 533-556, 2017

13. S. Bhatnagar and Lakshmanan K., Multiscale Q-learning with Linear Function Approximation, Discrete Event Dynamic Systems (DEDS),  Vol 26, Issue 3, pp. 477-509, 2016

14. K. Lakshmanan, R. Ortner and D. Ryabko, Improved Regret Bounds for Undiscounted Continuous Reinforcement Learning, Proceedings of The 32nd International Conference on Machine Learning (ICML) pp. 524-532, 2015

15. K. Lakshmanan and S. Bhatnagar, An Online Convergent Constrained Q-learning Algorithm with Linear Function Approximation, Invited paper at 50th Annual Allerton Conference on Communication,Control, and Computing, pp. 400-405, 2012

16. S. Bhatnagar and Lakshmanan K., An Online Actor–Critic Algorithm with Function Approximation for Constrained Markov Decision Processes, Journal of Optimization Theory and Applications (JOTA), Vol 153, No. 3, pp. 688-708, 2012

17. K. Lakshmanan and S. Bhatnagar , Smoothed Functional and Quasi-Newton Algorithms for Routing in Multi-stage Queueing Networks with Constraints, Proceedings of Distributed Computing and Internet Technology (ICDCIT), LNCS Vol. 6536, pp. 175-186, 2011

Ph.D Computer Science and Automation, IISc Bangalore 2013
B.Tech CEG/AC Tech Anna University Chennai 2006
Post-Doc at IIT Bombay, University of Leoben, Austria and National University of Singapore