School of Computer Science,
Carnegie Mellon University
6601 Gates Hillman Center
chiragn at cs dot cmu dot edu
I am on the Job Market for 2023
I am a PhD Candidate in the School of Computer Science at Carnegie Mellon University. I am part of the Auton Lab and advised by Prof. Artur Dubrawski. I graduated with a Masters from the same department before starting the PhD.
I am interested in challenges of applying Data Science and Machine Learning in cardiovascular health, especially around censored outcomes and counterfactuals.
I have previously worked with Prof. Katherine Heller at Google's Brain and Responsible AI Teams.
During my PhD, I have worked as a Summer Associate in Prof. Manuela Veloso's new AI Research Team within the Corporate and Investment Banking division of J.P. Morgan. I also spent a summer working with Kush R. Varshney and others at IBM Research's Thomas J. Watson Research Centre as a Science for Social Good Fellow.
I try to be a good citizen of the School of Computer Science by serving on the Dean's PhD Students Advisory Committee and co-chairing the SCS Dec/5.
Counterfactual Phenotyping with Censored Time-to-Events
Chirag Nagpal, Mononito Goswami, Keith Dufendach and Artur Dubrawski.
KDD - ACM Conference on Knowledge Discovery and Data Mining 2022
Deep Cox Mixtures for Survival Regression.
Chirag Nagpal, Steve Yadlowsky, Negar Rostamzadeh and Katherine Heller.
MLHC - Machine Learning for Healthcare Conference 2021
Interpretable Subgroup Discovery in Treatment Effect Estimation with Application to Opioid Prescribing Guidelines.
Chirag Nagpal, Dennis Wei, Bhanukiran Vinzamuri, M. Shekhar, S. E. Berger, S. Das and Kush Varshney.
CHIL - ACM Conference on Health, Inference and Learning 2020 (Spotlight Presentation)
[pdf] [code] [notebook]
Deep Survival Machines: Fully Parametric Survival Regression and Representation Learning for Censored Data with Competing Risks.
Chirag Nagpal, Xinyu Li, and Artur Dubrawski.
JBHI - IEEE Journal of Biomedical and Health Informatics
(and) NeurIPS Machine Learning for Health Workshop 2019 (Spotlight Presentation, top 3% of over 300 papers)
[pdf] [talk] [code]
Dynamically Personalized Detection of Hemorrhage.
Chirag Nagpal, Xinyu Li, Michael Pinsky, and Artur Dubrawski.
MLHC - Machine Learning for Healthcare Conference 2019
auton-survival: an open-source package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Event Data
Chirag Nagpal, Willa Potosnak and Artur Dubrawski.
MLHC - Machine Learning for Healthcare 2022
[tech-report] [official-blog] [code]
Deep Parametric Time-to-Event Regression with Time-Varying Covariates
Chirag Nagpal, Vincent Jeanselme and Artur Dubrawski.
AAAI Spring Symposium on Survival Prediction 2021
Bayesian Consensus: Consensus Estimates from Miscalibrated Instruments under Heteroscedastic Noise.
Chirag Nagpal, Robert E. Tillman, Prashant P. Reddy, and Manuela M. Veloso.
NeurIPS Robust AI in Financial Services Workshop 2019
An Entity Resolution Approach to Isolate Instances of Human Trafficking Online.
Chirag Nagpal, Kyle Miller, Benedikt Boecking, and Artur Dubrawski.
Bloomberg Data for Good Exchange 2017
Novel Machine Learning Technique Defines Patients Who Benefit from Off-Pump CABG
STS Coronary '22 [pdf]
Phenogrouping of hemorrhagic trauma patients using latent variable machine learning.
ISICEM '22 [pdf]
Accuracy of identifying venous thromboembolism by administrative coding compared to manual review.
|2020||NeurIPS Machine Learning for Health Workshop (ML4H)|
|2020||Neural Information Processing Systems (NeuRIPS)|
|2020||ACL Student Research Workshop (ACL-SRW)|
|2020 || Machine Learning for Healthcare Conference (MLHC)|
|2020|| ICLR ML in Real-Life Workshop (ML-IRL)
|2020|| ACM Conference on Health, Inference and Learning (CHIL)|
|2019|| NeurIPS Machine Learning for Health Workshop (ML4H)|
10-708 Probabilistic Graphical Models, Fall 2020
TAing for Prof. Pradeep Ravikumar
11-761/661 Language and Statistics, Fall 2019
TAing for Prof. Bhiksha Raj
I'm a dormant member of the W3VC, the Carnegie Tech Radio Club; In my past life, I used to make (hack?) stuff.
I enjoy Equitation, playing the Guitar, and Trivia and Quiz contests.
Here's a [list] of all the places I lived in before coming to Pittsburgh.