Raaz RSK Dwivedi
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Assistant Professor, Cornell Tech, Cornell University! My research interests are in the areas of causal inference, reinforcement learning, and distribution compression with applications in personalized decision-making and healthcare. If you are a PhD student or a postdoc at Cornell and interested in these topics, feel free to email me. I am also actively looking to recruit motivated and talented students applying to Cornell (see here). |
Ph. D. students
Brian Cho (3rd year ORIE, co-advised with Nathan Kallus)
Kyuseong Choi (4th year Stats, co-advised with Kengo Kato)
Albert Gong (2nd year CS, co-advised with Kilian Q. Weinberger)
News
Nov 2024: Honored to receive one of the Blackwell Rosenbluth Awards for contributions to Bayesian statistics, 2024!
Recent presentations:
July 18-19: Mini Workshop on Individualized Decisions, Simons/UC Berkeley!
Aug 7, 10:30 AM-12:00 PM ET Joint Statistical Meeting (JSM), Portland!
Aug 13, 4:20-6:00 PM ET, Parallel 1, Room 196: ESIF Economics and AI+ML Meeting, Cornell, Ithaca!
Oct 20-23: Informs, Seattle!
Recent preprints and publications:
Dec 2024: On adaptivity and minimax optimality of two-sided nearest neighbors, joint work with Tathagata Sadhukhan and Manit Paul, up on arxiv!
Oct 2024: Distributional matrix completion via nearest neighbors in the Wasserstein space, joint work with Jacob Feitelberg, Kyuseong Choi, and Anish Agarwal, up on arxiv!
Oct 2024: Learning counterfactual distributions via kernel nearest neighbors, joint work with Kyuseong Choi, Jacob Feitelberg, and Anish Agarwal, up on arxiv!
Sep 2024: Supervised Kernel Thinning, accepted at NeurIPS 2024!
May 2024: Debiased Distribution Compression, joint work with Lingxiao Li and Lester Mackey accepted at ICML 2024!
Apr 2024: Kernel Thinning, joint work with Lester Mackey accepted at JMLR!
Mar 2024: ‘‘Did we personalize? Assessing personalization by an online reinforcement learning algorithm using resampling’’, joint work with Susobhan Ghosh, Raphael Kim, Prasidh Chhabria, Predrag Klasjna, Peng Liao, Kelly Zhang, and Susan Murphy, accepted in Machine Learning Journal!
Feb 2024: ‘‘Doubly Robust Inference in Causal Latent Factor Models’’, joint work with Alberto Abadie, Anish Agarwal, and Abhin Shah up on arxiv!
Selected presentations
Integrating Double Robustness Into Causal Latent Factor Models || TALK Video || slides
2024: Columbia Stats, MIT ORC, Online Causal Inference Seminar, Cornell Weil (Tom Ten Have)
From HeartSteps To HeartBeats: Personalized Decison-making || TALK Video || animated slides | slides ||
2023: Cornell ORIE Industry Summit, AI CS, Stats & DS, CAM, Yale Stats & DS, Gatsby UCL, Stanford GSB OIT Group, UW Madison Stats, UIUC CS, Wharton Stats, UCLA Stats; 2022: Cornell ORIE, Cornell Tech ORIE, Rutgers Stats, Stanford EE (ISL), UC Berkeley EECS (BLISS)
Counterfactual Inference
In Sequential Experiments || preprint 1, preprint 2 | slides | poster ||
With Unobserved Confounding || preprint 3 | slides | poster ||
2023: ACM-FCRC, Informs APS, NESS, ACIC, MIT, IIM-A; 2022: NeurIPS, Cornell YRW, RSS, Informs, IMS, ACIC, SCM Princeton, Simons, MIT, Harvard
Distribution Compression
For Integration: Kernel Thinning And Compress || TALK Video || COLT (KT), ICLR 1 (GKT), ICLR 2 (Compress) | slides ||
For Hypothesis Testing: Compress Then Test || AISTATS (CTT) | slides | poster ||
2024: KAUST, 2023: JSM, MCM, AISTATS, MIT; 2022: RSS, SIAM, MSRI, JSM, ICLR, AABI, Harvard
Selected Other Topics/Talks
Non-asymptotic Guarantees For High-Dimensional Sampling || JMLR (MALA) | JMLR (HMC) | JMLR (Vaidya/John walks) | slides ||
Stable Discovery Of Interpretable Subgroups In Causal Studies || ISR | slides | poster ||
Revisiting Minimum Description Length Complexity In Overparameterized Models || preprint | slides | poster | video ||
Brief Bio
2021-2023: FODSI Postdoctoral Fellow, Harvard & MIT, co-advised by Prof. Susan Murphy & Prof. Devavrat Shah
2015-2021: Ph.D., EECS, UC Berkeley, co-advised by Prof. Martin Wainwright & Prof. Bin Yu (thesis)
2010-2014: B. Tech., EE, IIT Bombay, advised by Prof. Vivek Borkar (thesis)
Contact: Bloomberg 452, Roosevelt Island, New York City, dwivedi@cornell.edu, Google Scholar
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