B.Tech Courses
CSO 101 Computer Programming
CSE 241 Artificial Intelligence

1. Sumit Kumar, Ruchir Gupta, K Lakshmanan, Vipin Maurya, A Game-Theoretic Approach for Increasing Resource Utilization in Edge Computing Enabled Internet of Things, IEEE Access 2022 (Available Online)

2. Rakesh Kumar, Amrita Chaturvedi, Lakshmanan Kailasam, An Unsupervised Software Fault Prediction Approach Using Threshold Derivation, IEEE Transactions on Reliability 71:2, 911-932, 2022

3.  Abhinav Sharma, K Lakshmanan, Ruchir Gupta, Atul Gupta, Stochastic Arrow-Hurwicz Algorithm for Path Selection and Rate Allocation in Self-Backhauled mmWave Networks, IEEE Communications Letters  26:3, 716-720, 2021

4. 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

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

6. AK Singh, Lakshmanan Kailasam, T Pradhan, D Gupta, Context-Aware Influential Nodes Tracking in Online Social Networks, 25th Pacific Asia Conference on Information Systems (PACIS)- Dubai, Proceedings. 177, 2021

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

8. 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

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

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

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

12. 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

13. 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.

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

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

16. 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

17. 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

18. 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

19. 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

20. 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

21. 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
 

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

1. Indian Knowledge Systems Center, IIT (BHU)  Co-PI, Math and Astronomy in India (Jyotiṣa) - Work on पाण्डुलिपि (2022, Ongoing)

2. Co-PI, NOKIA project on Learning for Radio Resource Management (2019, Ongoing)