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Talks and Presentation Slides

28th April 2022, "Fair Virtual Conference Scheduling" at WWW-2022.

11th Feb 2022, "Multistakeholder Fairness" at TCS Research Cafe.

20th Nov 2021, "Towards Safety and Sustainability: Designing Local Recommendations for Post-pandemic World" at India HCI 2021 Showcase.

25th June 2021, "Bridging Machine Learning and Mechanism Design towards Algorithmic Fairness" at L3S, LUH.

22nd Sept 2020, “Designing Local Recommendations for Post-pandemic World”, at RecSys 2020.

27th Aug 2020, CNeRG Reading Group Discussion on “Controlling Fairness and Bias in Dynamic Learning-to-Rank” by Morik et al. at SIGIR 2020.

10th June 2020, Fairness in Two-Sided Platforms, PhD Registration Seminar, IIT Kharagpur.

23rd Apr 2020, FairRec: Two-Sided Fairness for Personalized Recommendations in Two-Sided Platforms, The Web Conference 2020 (WWW-2020), Taipei, Taiwan.

27th Feb 2020, CNeRG Reading group presentation: “Delayed Impact of Fair Machine Learning.”, by Liu et al. in ICML. 2018.

11th Feb 2020, Incremental Fairness in Two-Sided Market Platforms, Thirty-Fourth AAAI Conference on AI, AAAI-2020, Hilton Midtown, New York, USA.

7th Feb 2020, Two-Sided Fairness in Recommendation, Headquarters, Goldman Sachs, Financial District, New York, USA.

18th July 2019, Introduction to IR and Basic IR Tools, Information Retrieval Class, IIT Kharagpur.

4th July 2019, CNeRG Reading Group, “Fairness-Aware Ranking in Search & Recommendation Systems with Application to LinkedIn Talent Search” by Geyik et al. in KDD 2019.

14th April 2019, FATES on The Web (WWW), “Exposure Bias in Two-Sided Platforms: The Role of Location-Based Searches”.

2nd December 2018, CNeRG Retreat 2018, Chandipur, Odisha, “Equality of Voice: Towards Fair Representation in Crowdsourced Top-K Recommendations” in FAT* 2019

12th July 2018, CNeRG Reading Group, “Unlearn What You Have Learned: Adaptive Crowd Teaching with Exponentially Decayed Memory Learners” by Zhou et al. in KDD 2018.

13th April 2018, Intelligent Systems, “Recommendation Independence” by Kamishima et al. in FAT* 2018.