Twitter User Classification using Ambient Metadata. - Chirag Nagpal; Khushboo Singhal (CoRR, 2014)

An Entity Resolution Approach to Isolate Instances of Human Trafficking Online. - Chirag Nagpal; Kyle Miller 001; Benedikt Boecking; Artur Dubrawski (NUT@EMNLP, 2017)

Semi-Supervised Prediction of Comorbid Rare Conditions Using Medical Claims Data. - Chirag Nagpal; Kyle Miller 001; Tiffany Pellathy; Marilyn Hravnak; Gilles Clermont; Michael R. Pinsky; Artur Dubrawski (ICDM Workshops, 2017)

Preserving Intermediate Objectives: One Simple Trick to Improve Learning for Hierarchical Models. - Abhilasha Ravichander; Shruti Rijhwani; Rajat Kulshreshtha; Chirag Nagpal; Tadas Baltrusaitis; Louis-Philippe Morency (CoRR, 2017)

Dynamically Personalized Detection of Hemorrhage. - Chirag Nagpal; Xinyu Li; Michael R. Pinsky; Artur Dubrawski (MLHC, 2019)

Nonlinear Semi-Parametric Models for Survival Analysis. - Chirag Nagpal; Rohan Sangave; Amit Chahar; Parth Shah; Artur Dubrawski; Bhiksha Raj (CoRR, 2019)

Interpretable subgroup discovery in treatment effect estimation with application to opioid prescribing guidelines. - Chirag Nagpal; Dennis Wei; Bhanukiran Vinzamuri; Monica Shekhar; Sara E. Berger; Subhro Das; Kush R. Varshney (CHIL, 2020)

Latent Bayesian Inference for Robust Earnings Estimates. - Chirag Nagpal; Robert E. Tillman; Prashant P. Reddy; Manuela Veloso (CoRR, 2020)

Deep Cox Mixtures for Survival Regression. - Chirag Nagpal; Steve Yadlowsky; Negar Rostamzadeh; Katherine A. Heller (MLHC, 2021)

Deep Parametric Time-to-Event Regression with Time-Varying Covariates. - Chirag Nagpal; Vincent Jeanselme; Artur Dubrawski (SPACA, 2021)

Deep Survival Machines: Fully Parametric Survival Regression and Representation Learning for Censored Data With Competing Risks. - Chirag Nagpal; Xinyu Li; Artur Dubrawski (IEEE J. Biomed. Health Informatics, 2021)

Counterfactual Phenotyping with Censored Time-to-Events. - Chirag Nagpal; Mononito Goswami; Keith Dufendach; Artur Dubrawski (KDD, 2022)

auton-survival: an Open-Source Package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Event Data. - Chirag Nagpal; Willa Potosnak; Artur Dubrawski (MLHC, 2022)

Participatory Personalization in Classification. - Hailey Joren; Chirag Nagpal; Katherine A. Heller; Berk Ustun (NeurIPS, 2023)

Participatory Systems for Personalized Prediction. - Hailey James; Chirag Nagpal; Katherine A. Heller; Berk Ustun (CoRR, 2023)

Recovering Sparse and Interpretable Subgroups with Heterogeneous Treatment Effects with Censored Time-to-Event Outcomes. - Chirag Nagpal; Vedant Sanil; Artur Dubrawski (CoRR, 2023)

Helping or Herding? Reward Model Ensembles Mitigate but do not Eliminate Reward Hacking. - Jacob Eisenstein; Chirag Nagpal; Alekh Agarwal; Ahmad Beirami; Alex D'Amour; Dj Dvijotham; Adam Fisch; Katherine A. Heller; Stephen Pfohl; Deepak Ramachandran; Peter Shaw 004; Jonathan Berant (CoRR, 2023)

Leveraging Heterogeneity in Time-to-Event Predictions - Chirag Nagpal (2023)

The Case for Globalizing Fairness: A Mixed Methods Study on Colonialism, AI, and Health in Africa. - Mercy Nyamewaa Asiedu; Awa Dieng; Iskandar Haykel; Negar Rostamzadeh; Stephen Pfohl; Chirag Nagpal; Maria Nagawa; Abigail Oppong; Sanmi Koyejo; Katherine A. Heller (EAAMO, 2024)

Transforming and Combining Rewards for Aligning Large Language Models. - Zihao Wang; Chirag Nagpal; Jonathan Berant; Jacob Eisenstein; Alexander Nicholas D'Amour; Sanmi Koyejo; Victor Veitch (ICML, 2024)

Theoretical guarantees on the best-of-n alignment policy. - Ahmad Beirami; Alekh Agarwal; Jonathan Berant; Alexander D'Amour; Jacob Eisenstein; Chirag Nagpal; Ananda Theertha Suresh (CoRR, 2024)

Bias in Language Models: Beyond Trick Tests and Toward RUTEd Evaluation. - Kristian Lum; Jacy Reese Anthis; Chirag Nagpal; Alexander D'Amour (CoRR, 2024)

A Toolbox for Surfacing Health Equity Harms and Biases in Large Language Models. - Stephen R. Pfohl; Heather Cole-Lewis; Rory Sayres; Darlene Neal; Mercy Nyamewaa Asiedu; Awa Dieng; Nenad Tomasev; Qazi Mamunur Rashid; Shekoofeh Azizi; Negar Rostamzadeh; Liam G. McCoy; Leo Anthony Celi; et al. (CoRR, 2024)

Robust Preference Optimization through Reward Model Distillation. - Adam Fisch; Jacob Eisenstein; Vicky Zayats; Alekh Agarwal; Ahmad Beirami; Chirag Nagpal; Petet Shaw; Jonathan Berant (CoRR, 2024)

InfAlign: Inference-aware language model alignment. - Ananth Balashankar; Ziteng Sun; Jonathan Berant; Jacob Eisenstein; Michael Collins 001; Adrian Hutter; Jong Lee; Chirag Nagpal; Flavien Prost; Aradhana Sinha; Ananda Theertha Suresh; Ahmad Beirami (CoRR, 2024)

Bias in Language Models: Beyond Trick Tests and Towards RUTEd Evaluation. - Kristian Lum; Jacy Reese Anthis; Kevin Robinson; Chirag Nagpal; Alexander Nicholas D'Amour (ACL (1), 2025)

Speech Recognition with LLMs Adapted to Disordered Speech Using Reinforcement Learning. - Chirag Nagpal; Subhashini Venugopalan; Jimmy Tobin; Marilyn A. Ladewig; Katherine A. Heller; Katrin Tomanek (ICASSP, 2025)

Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning. - Amrith Setlur; Chirag Nagpal; Adam Fisch; Xinyang Geng; Jacob Eisenstein; Rishabh Agarwal; Alekh Agarwal; Jonathan Berant; Aviral Kumar (ICLR, 2025)

Robust Preference Optimization through Reward Model Distillation. - Adam Fisch; Jacob Eisenstein; Vicky Zayats; Alekh Agarwal; Ahmad Beirami; Chirag Nagpal; Peter Shaw 004; Jonathan Berant (Trans. Mach. Learn. Res., 2025)

Utility-inspired Reward Transformations Improve Reinforcement Learning Training of Language Models. - Roberto-Rafael Maura-Rivero; Chirag Nagpal; Roma Patel; Francesco Visin (CoRR, 2025)

EraseBench: Understanding The Ripple Effects of Concept Erasure Techniques. - Ibtihel Amara; Ahmed Imtiaz Humayun; Ivana Kajic; Zarana Parekh; Natalie Harris; Sarah Young; Chirag Nagpal; Najoung Kim; Junfeng He; Cristina Nader Vasconcelos; Deepak Ramachandran; Golnoosh Farnadi; et al. (CoRR, 2025)

Understanding challenges to the interpretation of disaggregated evaluations of algorithmic fairness. - Stephen R. Pfohl; Natalie Harris; Chirag Nagpal; David Madras; Vishwali Mhasawade; Olawale Salaudeen; Awa Dieng; Shannon Sequeira; Santiago Eduardo Arciniegas; Lillian Sung; Nnamdi Ezeanochie; Heather Cole-Lewis; et al. (CoRR, 2025)