Hello, thanks for visiting.
I work on training machine learning models to learn from human behavior - specifically, how to improve recommendation and ranking systems by learning from user interactions.
I recently completed my PhD at the Information Retrieval Lab at the University of Amsterdam, supervised by Prof. Maarten de Rijke and Prof. Harrie Oosterhuis. My research focused on off-policy evaluation and learning for ranking and recommendations - methods that safely improve ranking systems by learning from logged user interactions.
During my PhD, I spent time at Meta AI working on some exciting applications of these ideas. In my final year, I joined the Modern Recommender Systems team in NYC, where I developed a reinforcement learning approach for fine-tuning text-to-image diffusion models. The previous year in London, I worked on off-policy learning for two-stage recommendation systems and mixture-of-experts architectures for video recommendations.
My research interests span machine learning, information retrieval, off-policy methods for ranking and contextual bandits, and reinforcement learning for post-training of foundation models.
Before my PhD, I was a data scientist at Flipkart in India, working on search ranking and query understanding. I earned my research master’s degree at IIIT-Hyderabad’s Search and Information Extraction Lab, supervised by Dr. Manish Gupta and Prof. Vasudeva Varma.
I’m actively pursuing full-time positions as a Research Scientist, Research Engineer, or Machine Learning Engineer starting ASAP. If my expertise matches your team’s needs, I’d love to connect. My profile: CV, Publications, or Google Scholar profile.
Updates:
2025
- [Oct] Successfully defended my PhD thesis on reinforcement learning for ranking and generative models.
- [Aug] Invited to talk about my work on RL for recommendation and diffusion models at LossFunk Bangalore. The slides are here.
- [June] Research paper from my first internship at Meta, “Towards Two-Stage Counterfactual Learning to Rank” got accepted at ICTIR 2025 (co-located with SIGIR).
- [March] The preprint of my work from the internship at Meta AI, NYC, “A Simple and Effective Reinforcement Learning Method for Text-to-Image Diffusion Fine-tuning” is available.
2024
- [October 2024] Presented my work on Safe Deployment for Counterfactual Learning-to-Rank at Expedia, London.
- [September 2024] Two papers on “A Simpler Alternative to Variational Regularized Counterfactual Risk Minimization”, and “Proximal Ranking Policy Optimization for Practical Safety in Counterfactual Learning to Rank” accepted at the CONSEQUENCES ‘24 workshop @RecSys.
- [September 2024] We released the tutorial recording on Recent Advancements in Unbiased Learning to Rank, previously presented at WSDM 2024, SIGIR 2023, and FIRE 2023.
- [August 2024] Joined Meta AI, New York as a research scientist intern for the summer. I’ll be working on reinforcement learning based fine-tuning for text-to-image diffusion models.
- [July 2024] Full paper on “Optimal Baseline Corrections for Off-policy Contextual Bandits” accepted at RecSys 2024, with an oral presentation.
- [July 2024] Full paper on “Practical and Robust Safety Guarantees for Advanced Counterfactual Learning to Rank” accepted at CIKM 2024.
- [May 2024] PC member for ICML 2024, ICLR 2024, SIGIR 2024, RecSys 2024, and ICTIR 2024.
- [May 2024] Arxiv preprint of our work on “Optimal Baseline Corrections for Off-policy Contextual Bandits” is available online here.
- [March 2024] Slidedeck from the WSDM tutorial on recent advancements in unbiased LTR is available here.
- [March 2024] I will be co-presenting a tutorial on recent advancements in unbiased LTR at the WSDM 2024 conference.
2023
- [Oct 2023] Tutorial proposal on recent advancements in unbiased learning to rank accepted at WSDM 2024, and FIRE 2023.
- [Sept 2023] Invited talk at ShareChat on Safe Unbiased Learning to Rank slides, video.
- [August 2023] Invited talk at Meta AI, New York on Safe Unbiased Learning to Rank.
- [July 2023] Visiting Meta AI London as Research Scientist Intern, working with the Modern Recommender Systems (MRS) team. I am currently working on off-policy learning for two staged recommender system.
- [July 2023] Two papers (extended abstracts) accepted at the CONSEQUENCES workshop, collocated with RecSys’23. First work is a SIGIR resubmission on safe unbiased LTR; second work is on examining & mitigating selection bias in preference elicitation for recommender system.
- [June 2023] Paper on “A Deep Generative Recommendation Method for Unbiased Learning from Implicit Feedback” got accepted at ICTIR’23, collocated with SIGIR’23.
- [May 2023] Paper on user return time prediction was accepted with the CRUM workshop at UMAP 2023. This was work done while at Flipkart, India.
- [April 2023] Tutorial proposal on recent advancements in unbiased learning-to-rank got accepted at SIGIR’23. I will be leading the tutorial discussion at the conference.
- [April 2023] One full paper on safe unbiased learning to rank accepted at SIGIR 2023.
- [Feb 2023] PC member for SIGIR’23, NeurIPS’23.
2021-2022
- [August 2022] Work on VAE-IPS got accepted at the CONSEQUENCES+REVEAL Workshop (as oral presentation) at RecSys’22.
- [June’21 - June’22] Reviewed for ACL, EMNLP, ICLR, ICML, NeuRIPS’22.
- [Sept’21 - Nov’21] TA for the Advanced Information Retrieval course.
- [May 2021] Reviewing for NeurIPS, EMNLP, ICLR 21.
- [April 2021] Joined IRLab, UvA as a PhD student
Pre-PhD
- [July 2020] PC Member for EACL’2020.
- [April 2020] Position paper accepted at ECNLP@ACL’20.
- [April 2020] Paper accepted at SIGIR’20.
- [April 2020] PC Member for EMNLP’20 (IE Track) & AACL-IJCNLP 2020 (IE + IR Track).
- [Dec. 2019] PC Member for WSDM’20 Workshop on State-based User Modelling.
- [Nov. 2019] Reviewing for ICML 2020. [Update as of March’20] - Couldn’t review papers due to bad health.
- [July 2019] Program Committee Member for ECIR 2020.
- [June 2019] Reviewing for a special edition “Learning from User Interaction” of Information Retrieval Journal (IRJ).
- [March 2019] Invited talk at Alumni Research Talks event organized at BITS, Pilani. I talked about “Information Retrieval from Social Media” slides.
- [Oct 2018] Serving as PC member for ECIR’19 and ML4H@NIPS’19.
- [July 2018] Joined Flipkart as Data Scientist with the Search team.
- [June 2018] Internship work @Conduent Labs on “Fake News Detection” got accepted at ASONAM’18 (Short Paper).
- [June 2018] Journal paper from my summer internship work @TRDDC, Pune got published at BMC Bioinformatics (Impact Factor: 2.448)
- [June 2018] Serving as PC Member for ICON 2018 and DTMBio 2018 @CIKM’18.
- [January 2018] Joined Conduent Labs, Bangalore ((previously known as Xerox Research Center India (XRCI)) as Research Intern with Manjira Sinha and Sandya Mannarswamy.
- [December 2017] Two papers accepted at ECIR 2018.
- [November 2017] Two papers accepted at NIPS 2017 Machine Learning for Health (ML4H) Workshop.
- [November 2017] Invited talk on “Deep Learning for Recommender Systems” at Thiagarajar College of Engineering (TCE) &, “Machine Learning & Information Retrieval Techniques for Adverse Drug Reaction Mention Extraction from Social Media” at Duke-NUS Medical School, Singapore.
- [September 2017] Two papers on Content-Based News Recommendation Systems were accepted at the ICDM workshop on Semantic Recommendation Systems (SeRECSys)
- [August 2017] Paper on ‘Semi-Supervised Recurrent Neural Network for Adverse Drug Reaction Mention Extraction’ got accepted at ACM 11th International Workshop on Data and Text Mining in Biomedical Informatics at CIKM 2017
- [July 2017] Paper on Knowledge Base integration with text classification pipeline got accepted at SIGIR workshop (KG4IR)
- [June 2017] Paper on Trust Prediction in Social Media using Neural Networks got accepted at ASONAM’17.
- [May 2017] Work on Hate Speech detection from social media covered in some leading publication houses in India. Source
- [April 2017] Got the Best Poster award at WWW’17 for work on Hate Speech Detection from social media.
- [Feb 2017] Poster paper accepted in WWW’17.
- [Feb 2017] Workshop paper accepted in WWW’17.
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