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Hemalatha Chandrashekhar

Data Science & Information Systems

Associate Professor

B.E., (ECE); Fellow (PhD), IIM Lucknow

Hemalatha Chandrashekhar has done her Fellow Program in Management (Ph.D) from the Indian Institute of Management (IIM), Lucknow in the area of Information Systems. Her bachelor’s degree (Electronics and Communication Engineering) was from Bharathiar University, Tamil Nadu. After the completion of her Ph.D, more than a decade ago, she joined academics and has served as a faculty in the area of Information Systems at IIM, Indore and at IIM, Ranchi, before joining IFMR, GSB in 2013. In the flagship programs across the three institutes, she has taught and continues to teach the core course – Management Information Systems (now renamed Information Systems for Business). She also offers a host of electives that includes Data Mining & Predictive Analytics, Machine Learning and Deep Learning & Natural Language Processing. Her research work has been in the area of Autonomous Agents, broadly examining the role of Agents in Product Recommendations and Automated Negotiations. She has presented her research work in national and international conferences. Her research papers have also been published in ranked international journals. Her current research interest is in the area of Data Science. She is an active member of the Analytics Hub at IFMR GSB and one of the major contributors in various hub activities that include running long duration weekend certificate programs in Business Analytics and Big Data for working executives, short duration training programs in Data Science for corporates and consultancy assignments from corporates that require analysis of large volumes of enterprise data.

  • Recommender Systems
  • Mechanism design and Agent design for E-Negotiations
  • Deep Learning models for Image Recognition
  • Deep Learning models for Sequence Data Modeling
  • Natural Language Processing
  • “Quickly Locating Efficient, Equitable Deals in Automated Negotiations under Two-sided Information Uncertainty”, Chandrashekhar, H. and Bhasker, B., Decision Support Systems, Vol. 52, No. 1 (2011) : 157-168
  • “Personalized Recommender System Using Entropy Based Collaborative Filtering Technique”, Chandrashekhar, H. and Bhasker, B., Journal of Electronic Commerce Research, Vol. 12, No. 3 (2011) : 214-237
  • “Demystifying the Analytic Hierarchy Process and the Analytic Network Process”, Chandrashekhar, H. and Kumar, S., Udyog Pragati, Vol. 32, No.3 (2008)
  • Chandrashekhar H., Bhasker B. (2009) Learning Agents in Automated Negotiations. In: Prasad S.K., Routray S., Khurana R., Sahni S. (eds) Information Systems, Technology and Management. ICISTM 2009. Communications in Computer and Information Science, vol 31. Springer, Berlin, Heidelberg
  • Chandrashekhar, H. and Bhasker, B., 2007, “Collaborative Filtering Based on the Entropy Measure” in Proceedings of the 9th IEEE International Conference on E-Commerce Technology and The 4th IEEE International Conference on Enterprise Computing, E-Commerce and E-Services, pp. 203-210
  • Chandrashekhar, H. and Bhasker, B., 2006, Collaborative Filtering Recommender Systems: Techniques to overcome Ratings Sparsity in Proceedings of the 4th AIMS International Conference on Management, pp. 608-616, IIM Indore 
  • Hemalatha Chandrashekhar, 2013, Agent Models in E-Commerce, LAMBERT Academic Publishing
  • Information Systems for Business, Data Mining and Predictive Analytics, Machine Learning, Deep Learning and Natural Language Processing
  • Analytics Support for COE – Apollo Tyres (2018)
  • After Market Potential Analytics – FL Smidth (2018)