About Me

I am a PhD candidate at NYU Courant Institute of Mathematical Sciences, CILVR group, advised by Rajesh Ranganath and Thomas Wies. I work on causal inference, deep generative models, and machine learning for health. I’m also a part of the STAT research group at the NYU Center for Data Science.

In fall 2024, I will start looking for postdoc positions + jobs for summer/fall 2025. Feel free to reach out about this!

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News

(Summer-Fall 2024) student researcher at Google DeepMind NYC with Will Grathwohl!
(July 2024) accepted to ECCV 2024: Scalable Interpolant Transformers! With Nanye Willis Ma, Michael Albergo, Nick Boffi, Eric Vanden-Eijnden, and Saining Xie.
(Spring 2024) honored to receive the Henning Biermann Prize for teaching by a PhD student at NYU Courant!
(Spring 2024) accepted to ICML 2024: What’s the score? Automated Denoising Score Matching for Nonlinear Diffusions ! with Raghav Singhal and Rajesh Ranganath.
(Spring 2024) accepted to ICML 2024 (spotlight paper): Stochastic interpolants with data-dependent couplings ! with Michael Albergo, Nick Boffi, Rajesh Ranganath, and Eric Vanden-Eijnden! This work is on choosing data-dependent base distributions for continuous-time flows!
(Spring 2024) accepted to ICML 2024: probabilistic forecasting with stochastic interpolants and Föllmer processes! with Yifan Chen, Mengjian Hua, Michael S. Albergo, Nicholas M. Boffi, and Eric Vanden-Eijnden.

(Spring 2024) accepted to European Heart Journal, Acute Cardiovascular Care: A dynamic risk score for early prediction of cardiogenic shock using machine learning Also available on arxiv.

(Feb 2024) accepted to Journals of the American College of Cardiology, Clinical Electrophysiology: QTNet: Predicting Drug-Induced QT Prolongation with Artificial Intelligence-Enabled Electrocardiograms

(Fall 2023) taking part @ Flatiron Institute’s upcoming second workshop on Measure Transport, Sampling, and Diffusions!

(Fall 2023) lecture on diffusions + flows @ NYU course, Inference and Representations

(Fall 2023) talk on diffusions + flows @ Decisions, Risk and Operations ML reading group at Columbia, organized by Hongseok Namkoong!
(Summer 2023) We are running the second iteration of the workshop on Spurious Correlations, Invariance, and Stability at ICML 2023!
(Spring 2023) accepted to ICLR 2023: Where to Diffuse, How to Diffuse, and How to Get Back: Automated Learning for Multivariate Diffusions

(Fall 2022) lecture on diffusions @ Yann LeCun’s deep learning course at NYU!

(Fall 2022) talk on diffusions @ the Flatiron Institute’s workshop on Sampling, Transport, and Diffusions!
(Summer 2022) excited to be co-organizing the ICML Workshop on Spurious Correlations, Invariance, and Stability!
(Summer 2022) accepted to Machine Learning for Healthcare 2022: Survival Mixture Density Networks
(Summer 2022) glad to continue at Apple Health AI for the summer!
(Spring 2022) accepted to CLeaR (Causal Learning and Reasoning) 2022: Learning Invariant Representations with Missing Data (full version)
(Fall 2021) accepted to NeurIPS 2021 DistShift Workshop: Learning Invariant Representations with Missing Data Work done as part of my internship at Apple Health AI.
(Fall 2021) selected as a recipient of the NeurIPS 2021 Outstanding Reviewer Award. Glad to be a part of it!
(Fall 2021) accepted to NeurIPS 2021: Inverse-Weighted Survival Games
(Summer 2021) working with Apple’s Health AI team this summer supervised by Andy Miller and team!

(Spring 2021) accepted to ICML 2021: Understanding Failures in Out-of-Distribution Detection with Deep Generative Models (full version)
(Spring 2021) accepted to RobustML workshop @ ICLR 2021 Understanding Out-of-Distribution Detection with Deep Generative Models
(Fall 2020) I qualified! Upgrade from Student to Candidate.
(Fall 2020) after some time away from harvard cs, happy to help out Prof Nada Amin with the harvard AI/PL seminar
(Fall 2020) the deep learning course I TA’ed in spring 2020 for Yann LeCun and Alfredo Canziani is now up on Alf’s github page, check out all of Alf’s wonderful teaching materials and thanks to students for your notetaking
(Fall 2020) accepted to NeurIPS 2020: X-CAL: Explicit Calibration for Survival Analysis
(Summer 2019) I’m working in Emtiyaz Khan’s Approximate Bayesian Inference group at RIKEN AIP in Tokyo!
(2018) MacCracken Fellow, NYU Graduate School of Arts and Sciences, Five years of PhD funding.

mentoring

Abhipsha Das (Master’s Thesis at NYU, 2024, on diffusions for text)
Shraddha Jain (current Master’s student, 2024, research on VAEs)
Nina Mortensen (Masters Thesis at NYU, 2024, research on VAEs, now at Fauna Robotics)
Kyle Adams (Undergradate from University of Florida, 2022, research on survival analysis, now a math phd at UF)
mentor for Women in Data Science Datathon, Cambridge, 2021.

Courses I’ve TA’ed/TF’ed:

NYU, CSCI-GA.2565: Machine Learning. Prof: Rajesh Ranganath. Spring 2022.
NYU, CSCI-GA.2565: Machine Learning. Prof: Rajesh Ranganath. Spring 2021.
NYU, CSCI-GA.2572: Deep Learning. Prof: Yann LeCun. Spring 2020.
NYU, CSCI-GA.2565: Machine Learning. Prof: Rajesh Ranganath. Fall 2019.
Harvard, CS 181: Machine Learning. Profs: Finale Doshi-Velez and David Parkes. Spring 2021.
Harvard, CS 252: Programming Languages and Artificial Intelligence. Prof: Nada Amin. Fall 2020.
Harvard, CS 181: Machine Learning. Prof: Finale Doshi-Velez. Spring 2018.
Harvard, CS 281: Advanced Machine Learning. Prof: Sasha Rush. Fall 2017.
Harvard, CS 121: Intro to Theoretical CS. Profs: Boaz Barak and Salil Vadhan. Fall 2017.
Harvard, CS 181: Machine Learning. Profs: David Parkes and Sasha Rush. Spring 2017.
Harvard, CS 61: Systems Programming and Machine Organization. Profs: Margo Seltzer and Eddie Kohler. Fall 2016.

Conferences I usually review for

NeurIPS
ICML
ICLR
AAAI
AISTATS
CLeaR
misc workshops

In a previous life

I was a research assistant and teaching fellow in the computer science department at Harvard SEAS. I am still an on/off TF for the harvard undergrad ML course. Between Harvard and NYU, I worked with the CoCoSci group at MIT BCS. Previous to that, I studied music composition, improvisation, and theory at New England Conservatory with Anthony Coleman, Stratis Minakakis and Ran Blake. I am still involved with music and rehearse with Gamelan Kusuma Laras a classical Javanese ensemble that performs the repetoire of the courts of Central Java.