Raaz RSK Dwivedi
|
Assistant Professor, Cornell Tech, Cornell University!
Field Member: ORIE, CS, Stats, CAM
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).
|
News
Selected presentations
Counterfactual Inference
in sequential experiments || preprint 1, preprint 2 | slides | poster ||
and 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 || COLT (KT), ICLR 1 (GKT), ICLR 2 (Compress) | slides | video ||
for hypothesis testing, Compress then test || AISTATS (CTT) | slides | poster ||
2023: JSM, MCM, AISTATS, MIT; 2022: RSS, SIAM, MSRI, JSM, ICLR, AABI, Harvard
Goodpoints Repo
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: Rhodes 226 Ithaca, dwivedi@cornell.edu, Google Scholar
Fun Stat
|