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PhD Candidate (TCS Fellow), CSE, IIT Kharagpur Researcher and Project Manager, L3S Research Center, LUH Address: 212, Appelstraße 4, Hannover, Germany Email: last_name first_name [at] gmail [dot] com CV : here |
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About MeI am a PhD scholar (TCS research fellow) in the department of Computer Science and Engineering at IIT Kharagpur, India, and a researcher at the L3S research center in Leibniz Universität Hannover. I work under the supervision of Prof. Niloy Ganguly. I have worked in areas like machine learning, information retrieval, recommender systems, and allocation mechanisms. My current research interests fall in bias & fairness aspects of algorithmic systems. Broadly my works try to answer questions like how to bring fairness and ethics into algorithmic systems.Currently, I am a part of Complex Networks Research Group at IIT Kharagpur and also the L3S Research Center at LUH. Prior to this, I have completed my bachelor's degree (B. Tech.) from IIT Jodhpur, and also briefly worked as a supply chain and operations planning consultant at Steelwedge Software (now a part of E2open LLC.). ☆ My Homestate: Odisha ☆I am from the state of Odisha located on the eastern coast of India. Odisha is known for its ancient temples, dense jungles, serene beaches, sublime arts, and much more. If you are planning for a vacation, Odisha can be your next destination. Here is a small video on some attractions of Odisha. You can find more details on the official site of Odisha Tourism.✰ News ✰▹ Feb'24: Giving a talk on "Algorithmic Fairness in Two-Sided Settings" at Yahoo Research.▹ Jan'24: Book chapter released "Algorithmic Fairness in Multi-stakeholder Platforms", in Ethics in Artificial Intelligence: Bias, Fairness and Beyond. Springer Nature, Singapore. ▹ Aug'23: Finished my PhD thesis titled "Algorithmic Fairness in Two-Sided Settings" at IIT Kharagpur. ▹ Sept'22: Giving a talk on an impact-oriented research agenda for fair ranking (paper, slides) at the workshop on Artificial Intelligence, Causality and Personalized Medicine AICPM-2022. ▹ June'22: Giving a talk on fair ranking (paper, slides) at the ACM Conference on FAccT-2022. ▹ Apr'22: Giving a talk on fair virtual conference scheduling (paper, slides) at the Web Conference WWW-2022. ▹ Apr'22: Position paper on interdisciplinary perspectives on AI regulations got accepted at the AAAI/ACM AIES Conference AIES-2022. ▹ Apr'22: Position paper on the state of fairness in ranking and recommendation got accepted at the FAccT conference FAccT-2022. ▹ Jan'22: Paper on fairness in virtual conference scheduling got accepted at the web conference WWW-2022. ▹ Oct'21: NoBIAS and NL4XAI are organizing European AI Regulation Week from 5 to 8 October 2021. ▹ Sept'21: The first NoBIAS Summer School with exciting keynotes and lectures starts on 20th Sept 2021. Any one can register and attend. ▹ June'21: Giving a talk on "Bridging Machine Learning and Mechanism Design towards Algorithmic Fairness" (slides) at L3S, LUH. ▹ June'21: Joined as a researcher in NoBIAS at L3S, LUH. ▹ Jan'21: Serving as a PC member of RecSys-2021. ▹ Dec'20: Paper (link) accepted at FAccT-2021 (formerly FAT*). ▹ Dec'20: Interesting talks lined up at IndoML-2020. ▹ Nov'20: Volunteering at Indian Symposium on Machine Learning (IndoML). ▹ Nov'20: Giving a talk on exposure bias at FILA-2020 in December'20. ▹ Oct'20: Student poster (arXiv link) accepted at AAAI-2021. ▹ Oct'20: Reviewing for Information Processing and Management (IPM) journal. ▹ Sept'20: Giving a talk on pandemic-aware local recommendation (paper, slides, video) at RecSys-2020. ▹ Sept'20: Reviewing for WWW-2021. ▹ Aug'20: Discussing SIGIR-20 paper “Controlling Fairness and Bias in Dynamic Learning-to-Rank” by Morik et al. in our CNeRG reading group (slides). ▹ Aug'20: Serving as a PC member of AAAI-2021. ▹ July'20: Paper (link) on pandemic-aware local recommendation got accepted at RecSys-2020. ▹ June'20: Giving my PhD registration seminar (slides) on two-sided fairness at IIT Kharagpur. ▹ Apr'20: Giving a talk on fairness in recommendation (paper, slides) at WWW-2020. ▹ Feb'20: Discussing ICML-18 paper “Delayed Impact of Fair Machine Learning.”, by Liu et al. in our CNeRG reading group. ▹ Feb'20: Giving a talk on incremental fairness in platform updates (paper, slides) at AAAI-2020. ▹ Feb'20: Giving a talk on fairness in recommendations (slides) at Goldman Sachs headquarters in New York, USA. ▹ Jan'20: Paper on two-sided fairness in recommendation (paper) got accepted at WWW-2020. |