Dr. R.S. Milton

cse_miltonProfessor
Dr. R. S. Milton, B.E. (Hons), M.E., Ph.D.

Email: miltonrs@ssn.edu.in

Dr. R. S. Miltonis a professor of Computer Science and Engineering at SSN since January 2010. He has been teaching for 26 years. He received his B.E. degree with Honors in Electronics and Communication Engineering from  Thiagarajar College of Engineering, Maduari and M.E. in Computer Science and Engineering from College of Engineering Guindy, and Ph.D. in Information and Communication Engineering  (Rough Set Theory and Relational Learning), from Anna University , Chennai. He worked in Madras Christian College, Chennai, from 1993 to 2010. He is a ember of the Machine Learning Research Group of SSN and his research interests His research interests include Statistical Relational Learning, Natural Language Processing, and Computer Science Education.

 Publications

1. Leo Raju, Milton R S and Sakthiyanandan S. Energy Optimization of Solar Micro-grid using Multi Agent Reinforcement Learning, Applied Mechanics and Materials, Vol. 787, pp 843-847, 2015.

2. Leo Raju, Milton R S, Swetha Suresh and Sibi Sankar. Reinforcement Learning in Adaptive Control of Power System Generation, International Conference on Information and Communication Technologies (ICICT 2014), Cochin, December 2014.

3. Leo Raju, Sibi Sankar and Milton R S. Distributed Optimization of Solar Micro-grid using Multi Agent Reinforcement Learning, International Conference on Information and Communication Technologies (ICICT 2014), Cochin, December 2014.

4. Leo Raju, Milton R S and Sibi Sankar. Reinforcement Learning for Optimal Energy Management of a Solar micro-grid, IEEE Global Humanitarian Technology Conference (IEEE GHTC –SAS 2014), Trivandrum, September 2014.

5. Vaishnavi V, Saritha M and Milton R S. Paraphrase Identification in Short Texts using Grammar Patterns, Third International Conference on Recent Trends in Information Technology, MIT Chennai, 2013.

6. Ravidhaa K, Radha Meena S and Milton R S. Evaluation of Semantic Role Labeling Based on Lexical Features Using Conditional Random Fields and Support Vector Machine, Third International Conference on Recent Trends in Information Technology, MIT Chennai, 2013.

7. Arvind Krishnaa J, Srikrishnan S, Vishal Gautham V, Milton R S, A Canvas-Based Presentation Tool Using Scalable Vector Graphics, Technology for Education (T4E), IIIT Hyderabad, 2012.

8. Ragendhu and Milton R S. Diagrammatic Reasoning in Computer Programming, Technology for Education (T4E), IITM Chennai, 2011.

9. Latha Karthigaa M and Milton R S. Securing Multi-Application Smart Cards Using an Unassailable Brand New Cryptosystem, In Saranya, Saravankumar, editors, International Conference on Computer Communication and Informatcs 2011, pp 55-58, Coimbatore, India, Jan 2011.

10. Sivasakthi M, Rajendran R and Milton R S, The Role of Creative Thinking in Teaching and Learning Computer Programming, 12th National Conference on Developing School Psychology in India, Pondycherry Psychology Association, Puducherry, January 2010.

11. Milton R S. ICT Intervention in Teaching: Prospects and Challenges, International Conference on Quality Teachers Education and Information Communication Technology, 2006, St Christopher College for Education, Chennai, 2006.

12. Milton R S, Uma Maheswari V and Siromoney A. Studies on Rough Sets in Multiple Tables. In Slezak D, Wang G, Szczuka M, Duentsch I, and Yao Y, editors, The Tenth International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC 2005), pp 263–272. Springer-Verlag, 2005.

13. Milton R S, Uma Maheswari V and Siromoney A. Probability Measures for Prediction in Multi–Table Infomation Systems. In Pal S, Bandyopadhyay S and Biswas S, editors, First International Conference, Pattern Recognition and Machine Intelligence 2005, pp 738–743. Springer-Verlag, 2005.

14. Milton R S, Uma Maheswari V and Siromoney A. Rough Sets and Relational Learning. Volume 3100 of Lecture Notes in Computer Science, pp 321–337. Springer-Verlag, 2004.

15. Milton R S, Uma Maheswari V and Siromoney A. Rough Relational Learning in Predictive Toxicology. In Proceedings of the International Workshop on Knowledge Discovery in Biomedicine (KDBM 2004), PRICAI-2004, pp 78–88, 2004.

16. Milton R S, Uma Maheswari V and Siromoney A. The Variable Precision Rough Set Inductive Logic Programming Model — A Statistical Relational Learning perspective. In SRL2003 IJCAI Workshop on Learning Statistical Models from Relational Data, pp 87–91, 2003.