Current Research Interests

• Multi-armed Bandits

• Recommender systems

• Fair and Interpretable machine learning algorithms

• Personalized Pricing

Research Team

Ph.D. Students

• Shivam Gupta (PMRF Fellow)--Working on fair clustering algorithms

• Napendra Singh Rajput--Working on Fair resource allocation

• Subham Pokhriyal--Finishing his coursework

• Shradha Sharma--Finishing her coursework

Current M.tech. Students

• Sumeet Gupta--working on Human-in-the-loop setting

Past M.tech. Students

• Vishal Chaudhary--Worked on Interpretable Clustering

• Kirandeep Kaur--Worked on fair federated recommender systems

• Boroju Arthik--Worked on demand response in smart grids

Manuscripts Under Preparation/Submission

• Shivam Gupta, Kirandeep Kaur, Shweta Jain. EqBal-RS: Mitigating Popularity Bias in Recommender Systems.

• Shrikant Saxena, Shweta Jain. Exploring and Mitigating Gender Bias in Book Recommendation System with Explicit Feedback. 

Journal Publications

• Shivam Gupta, Ganesh Ghalme, Narayanan C Krishnan, Shweta Jain.  Efficient Algorithms for Fair Clustering with a New Fairness Notion. Data Mining Knowledge Discovery (2023). https://doi.org/10.1007/s10618-023-00928-6 

• Ganesh Ghalme, Swapnil Dhamal, Shweta Jain, Sujit Gujar, Y. Narahari. Ballooning Multi-armed Bandits. Artificial Intelligence, 296, 103485. 

Paper Url: https://arxiv.org/abs/2001.10055

• Satyanath Bhat, Shweta Jain, Sujit Gujar, Yadati Narahari. An optimal bidimensional multi-armed bandit auction for multi-unit procurement, Annals of Mathematics and Artificial Intelligence, Volume 85, Issue 1, pp 1-19, 2019.

Paper Url: https://link.springer.com/content/pdf/10.1007/s10472-018-9611-0.pdf 

• Shweta Jain, Sujit Gujar, Satyanath Bhat, Onno Zoeter, Y. Narahari. A quality assuring, cost optimal multi-armed bandit mechanism for expertsourcing, Artificial Intelligence, Volume 254, pp 44-63, 2018.

Paper Url: https://www.sciencedirect.com/science/article/pii/S000437021730125X

• Shweta Jain, Satyanath Bhat, Ganesh Ghalme, Divya Padmanabhan, Y. Narahari. Mechanisms with Learning for Stochastic Multi-armed Bandit Problems, Indian Journal of Pure and Applied Mathematics, Volume 47, Issue 2, pp 229-272, June 2016.

Paper Url: https://link.springer.com/article/10.1007/s13226-016-0186-3

Conference Publications

• Sanjay Chandelkar, Shweta Jain, and Sujit Gujar. A Novel Demand Response Model and Method for Peak Reduction in Smart Grids -- PowerTAC accepted in IJCAI 2023. 

• Sagalpreet Singh, Shweta Jain, Shashi Shekhar Jha. On Subset Selection of Multiple Humans To Improve Human-AI Team Accuracy accepted as full paper in AAMAS 2023. 

• Napendra Solanki, Shweta Jain, and Suman Banerjee. Fairness Driven Efficient Algorithms for Sequenced Group Trip Planning Query Problem accepted as full paper in AAMAS 2023. 

• Sanjay Chandelkar, Boroju Arthik, Sujit Gujar, and Shweta Jain. A Novel Demand Response Model and Method for Peak Reduction in Smart Grids — PowerTAC got accepted as extended abstract in AAMAS 2023. 

• Shivam Gupta, Ganesh Ghalme, Narayanan C. Krishnan, Shweta Jain. Group Fair Clustering Revisited — Notions and Efficient Algorithm got accepted as extended abstract in AAMAS 2023. 

• Shantanu Das, Swapnil Dhamal, Ganesh Ghalme, Shweta Jain, Sujit Gujar. Individual Fairness in Feature-Based Pricing for Monopoly Markets. Accepted to the 38th Conference on Uncertainty in Artificial Intelligence (UAI 2022) 

• D Das, Shweta Jain, S. Gujar 2021. Budgeted Combinatorial Multiarmed Bandits. Accepted to Autonomous Agents and Multi-Agent systems, AAMAS 2021. 

• Akansha Singh, Meghana Reddy, Sujit Gujar, Shweta Jain. Designing Bounded min-Knapsack Bandits Algorithm for Sustainable Demand Response. Accepted as a full paper in the 18th Pacific Rim International Conference on Artificial Intelligence, 2021

• Kumar Abhishek, Shweta Jain, Sujit Gujar. Designing Truthful Contextual Multi-armed Bandits based Sponsored Search Auctions. AAMAS 2020--Extended Abstract. 

Full version: https://arxiv.org/abs/2002.11349 

• Ganesh Ghalme, Swapnil Dhamal, Shweta Jain, Sujit Gujar, Y. Narahari. Ballooning Multi-armed Bandits. AAMAS 2020--Extended Abstract. 

Full version: https://arxiv.org/abs/2001.10055

• Shweta Jain, Sujit Gujar. "A Mulitarmed Bandit Based Incentive Mechanism for a Subset Selection of Customers for Demand Response in Smart Grids". Accepted in Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-2020).

• Siddharth Barman, Ganesh Ghalme, Shweta Jain, Pooja Kulkarni, Shivika Narang. “Fair Division of Indivisible Goods amongst Strategic Agents”, Proceedings of the 2019 International Conference on Autonomous Agents and Multi-Agent Systems, AAMAS’19.

Paper Url: https://dl.acm.org/citation.cfm?id=3306127.3331927

• Ganesh Ghalme, Sujit Gujar, Amleshwar Kumar, Shweta Jain, Y. Narahari. "Design of Coalition Resistant Credit Score Functions for  Online Discussion Forums", Proceedings of the 2018 International Conference on Autonomous Agents and Multi-Agent Systems, AAMAS’18.

Paper Url: https://dl.acm.org/citation.cfm?id=3237383.3237404

• Aritra Chaterjee, Ganesh Ghalme, Shweta Jain, Rohit Vaish, Y. Narahari. “On Thompson Sampling for Stochastic Sleeping Multi-armed Bandits Problem with Adversarial Availability”,  International Conference on Uncertainty in Artificial Intelligences, UAI’17.

Paper Url: http://auai.org/uai2017/proceedings/papers/180.pdf

• Ganesh Ghalme, Shweta Jain, Sujit Gujar, Y. Narahari. “Thompson Sampling Based Mechanisms for Stochastic Multi-Armed Bandit Problems”, Proceedings of the 2017 International Conference on Autonomous Agents and Multi-Agent Systems, AAMAS’17, pp 87--95.

Paper Url: http://www.ifaamas.org/Proceedings/aamas2017/pdfs/p87.pdf

• Shweta Jain, Ganesh Ghalme, Satyanath Bhat, Sujit Gujar, Y. Narahari. “A Deterministic MAB Mechanism for Crowdsourcing with Logarithmic Regret and Immediate Payments”, Proceedings of the 2016 International Conference on Autonomous Agents and Multi-Agent Systems, AAMAS’16, pp 86-94. 

Paper Url: https://dl.acm.org/citation.cfm?id=2936924.2936941

• Satyanath Bhat, Divya Padmanabhan, Shweta Jain, Y. Narahari. “A Truthful Mechanism with Bipartite Learning for Online Crowdsourcing”, Proceeding of the 2016 International Conference on Autonomous Agents and Multi-Agent Systems, AAMAS’16, pp 1385-1386. 

Paper Url: http://www.ifaamas.org/Proceedings/aamas2016/pdfs/p1385.pdf

• Arpita Biswas, Shweta Jain, Debmalya Mandal, Y. Narahari. “A Truthful  Budget Feasible Multi-Armed Bandit Mechanism for Crowdsourcing Time Critical Tasks”, Proceeding of the 2015 International Conference on Autonomous Agents and Multi-Agent Systems, AAMAS’15, pp 1101-1109. 

Paper Url: https://dl.acm.org/citation.cfm?id=2773291

• Satyanath Bhat, Shweta Jain, Sujit Gujar, Y. Narahari. “An Optimal Bidimensional Multi-armed Bandit Auction for Multi-unit Procurement”, Proceeding of the 2015 International Conference on Autonomous Agents and Multi-Agent Systems, AAMAS’15, pp 1789-1790. 

Paper Url: http://www.ifaamas.org/Proceedings/aamas2015/aamas/p1789.pdf

• Shweta Jain, Sujit Gujar, Onno Zoeter, Y. Narahari. “A Quality Assuring Multi-Armed-Bandit Crowdsourcing Mechanism with Incentive Compatible Learning”, Thirteenth International Conference on Autonomous Agents and Multi-Agent Systems, AAMAS’14, pp 1609-1610.

Paper Url: https://dl.acm.org/citation.cfm?id=2616086

• Shweta Jain, Balakrishnan Narayanaswamy, Y. Narahari. “A Multiarmed Bandit Incentive Mechanism for Crowdsourcing Demand Response in Smart Grids”, Proceedings of Twenty-Eighth {AAAI} Conference on Artificial Intelligence, AAAI’14, pp 721-727.

Paper Url:  https://www.aaai.org/ocs/index.php/AAAI/AAAI14/paper/view/8355

• Shweta Jain, Balakrishnan Narayanaswamy, Y. Narahari, Saiful A Hussain, Voo Nyuk Yoong. “Constrained Tatonnement for Fast and Incentive Compatible Distributed Demand Management in Smart Grids”, Proceedings of the fourth international conference on Future energy systems, e-Energy'13, 125-136, 2013.  

Paper Url: https://dl.acm.org/citation.cfm?doid=2487166.2487180