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Career

· Researcher, MIT - Institute for Medical Engineering and Science
· Assistant Professor, New York University (NYU) - Courant Institute of Mathematical Sciences & Center for Data Science
· PhD Student, Princeton University
· Undergraduate Degree, Stanford University

Publications (274)

Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
International Conference on Machine Learning · 2009
2,701
cited
Black Box Variational Inference
International Conference on Artificial Intelligence and Statistics · 2013
1,206
cited
ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission
arXiv.org · 2019
1,148
cited
Automatic Differentiation Variational Inference
Journal of machine learning research · 2016
771
cited
Unsupervised learning of hierarchical representations with convolutional deep belief networks
Communications of the ACM · 2011
397
cited
Hierarchical Variational Models
International Conference on Machine Learning · 2015
352
cited
A Review of Challenges and Opportunities in Machine Learning for Health.
AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2018
331
cited
Automatic Variational Inference in Stan
Neural Information Processing Systems · 2015
242
cited
Hierarchical Implicit Models and Likelihood-Free Variational Inference
Neural Information Processing Systems · 2017
242
cited
Reproducibility in machine learning for health research: Still a ways to go
Science Translational Medicine · 2021
234
cited
Variational Sequential Monte Carlo
International Conference on Artificial Intelligence and Statistics · 2017
229
cited
Deep Survival Analysis
Machine Learning in Health Care · 2016
216
cited
The role of machine learning in clinical research: transforming the future of evidence generation
Trials · 2021
214
cited
The Variational Gaussian Process
International Conference on Learning Representations · 2015
190
cited
Offline RL Without Off-Policy Evaluation
Neural Information Processing Systems · 2021
184
cited
Support and Invertibility in Domain-Invariant Representations
International Conference on Artificial Intelligence and Statistics · 2019
172
cited
FastSHAP: Real-Time Shapley Value Estimation
International Conference on Learning Representations · 2021
167
cited
Deep Exponential Families
International Conference on Artificial Intelligence and Statistics · 2014
155
cited
Deep learning models for electrocardiograms are susceptible to adversarial attack
Nature Medicine · 2020
136
cited
Risk prediction for chronic kidney disease progression using heterogeneous electronic health record data and time series analysis
J. Am. Medical Informatics Assoc. · 2015
121
cited
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Rajesh Ranganath | Researcher Profile | Sotabase | Sotabase