Shashank Gupta

Hello, thanks for visiting.

I am a final-year Ph.D. student at the IRLab, UvA, supervised by Prof. Maarten de Rijke and Prof. Harrie Oosterhuis. I am working on the problem of off-policy evaluation and learning from user interactions. I recently finished an internship at Meta AI, NYC with the modern recommender systems (MRS) team, where I worked on a novel reinforcement learning based fine-tuning for text-to-image diffusion models. During my third year of PhD, I interned at MetaAI, London with the modern recommender systems (MRS) team, where I worked on off-policy learning for two-stage recommendations and cold-start recommendations.

My primary areas of interest are: machine learning, information retrieval, off-policy evaluation and learning for ranking and contextual bandits.

Before joining the PhD, I worked as a data scientist with the search team at Flipkart Internet Pvt. Limited, India, where I contributed to various query understanding and product ranking projects. I completed my research masters at the Search and Information Extraction Lab SIEL, IIIT-Hyderabad, under the joint supervision of 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 in Summer 2025. If my expertise matches your team’s needs, I’d love to connect. My profile: CV, Publications, or Google Scholar profile.

Updates:

2025

  • [March] The preprint of my work from the internship at Meta AI, NYC is available here.

2024

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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