Harsh Parikh

Harsh Parikh, Tyler McCormick, Emily K. Johnson, Leo Hickey, Megan L. Ranney, Bhramar Mukherjee. The epidemiology of artificial intelligence. Nature Health, 2026

Yilin Song, Dan M Kluger, Harsh Parikh, Tian Gu. Demystifying prediction powered inference. Harvard Data Science Review (accepted), 2026 co-senior/corresponding author

Harsh Parikh, Marco Morucci, Vittorio Orlandi, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky. A Double Machine Learning Approach for Combining Experimental and Observational Studies. Observational Studies, 2026

Yiran Wang, Alicia E Boyd, Lillian Rountree, Yi Ren, Kate Nyhan, Ruchit Nagar, Jackson Higginbottom, Megan L Ranney, Harsh Parikh, Bhramar Mukherjee. Ten core concepts for ensuring data equity in public health. JAMA Health Forum, 2026

David Arbour^*, Harsh Parikh^*, Bijan Niknam, Elizabeth Stuart, Kara Rudolph, Avi Feller. Regularizing extrapolation in causal inference. International Conference on Artificial Intelligence and Statistics (AISTATS), 2026 co-first author

Maxwell Salvatore, Yiran Wang, Preeti Syal, Brian Wahl, Harsh Parikh, Vishal Deo, Naveen Kumar Bhatraju, Kaushalya Jayaweera, Nisha Rana, Redoy Ranjan, Fyezah Jehan, Abdullah Yusuf, Karthik Adapa, Mona Duggal, Anurag Agrawal, Bhramar Mukherjee. The case for an integrated biobanking initiative in South Asia. The Lancet Regional Health-Southeast Asia 49, 2026

Carly L Brantner, Trang Quynh Nguyen, Harsh Parikh, Congwen Zhao, Hwanhee Hong, Elizabeth A Stuart. Precision mental health: predicting heterogeneous treatment effects for depression through data integration. Journal of the Royal Statistical Society Series C: Applied Statistics, 2026

Lillian Rountree, Harsh Parikh, Bhramar Mukherjee. Data (in) equities in data science: Dissecting systemic and systematic biases in pulse oximetry. The Canadian Journal of Statistics (accepted), 2026

Emily K Johnson, Harsh Parikh, Catherine K Ettman, Ge Ge, Liza Sopina, Angela Y Chang. Lasting Income Costs of Mental and Physical Illness. JAMA Health Forum, 2026

Harsh Parikh. Why are there many equally good models? An Anatomy of the Rashomon Effect. arXiv preprint arXiv:2601.06730, 2026

M McCauley, TM Westover, P Wynn, S Sartipi, N Turley, Z Akras, P Colin, Webb, Struck, Kim, Cheng, Sun, Houle, Rudin, Volfovsky, Harsh Parikh, Fernandes, Zafar, Westover. CICADAS: A simulation-based framework for randomized trial emulation in critical-care seizure treatment. Intelligence-Based Medicine 16, 100481, 2026

L Raymond-King, S McGrath, B Mukherjee, Y Wang, H Parikh, J Rothen, .... Frailty and low utilization of curative-intent surgical resection in non-metastatic pancreatic cancer. JNCI Cancer Spectrum, pkag078, 2026

Harsh Parikh, Gabriel Levin-Konigsberg, Nilesh Tripuraneni, Dhruv Madeka, Michael I. Jordan, Dean Foster, Dominique Perrault-Joncas, Alexander Volfovsky. Towards Optimal Estimators for Randomized Control Trials. arXiv preprint arXiv:2607.23254, 2026

E Johnson, C Ettman, H Parikh, L Sopina, G Ge, A Chang. The Experienced Burden of Disease In Denmark: A Comparison of the Economic and Social Effects of 15 Chronic Diseases. 2026 Annual Research Meeting, 2026

Harsh Parikh, Gabriel Levin-Konigsberg, Dominique Perrault-Joncas, Alexander Volfovsky. Mind the Sim-to-Real Gap & Think Like a Scientist. arXiv preprint arXiv:2605.21458, 2026

Camille DeSisto, Ranaivo Rasolofoson, Michelle Foley, Harsh Parikh. When Does Agroforestry Income Reduce Deforestation? Evidence from a Natural Experiment in Madagascar. arXiv preprint arXiv:2603.13706, 2026

Harsh Parikh, Gabriel Levin-Konigsberg, Dominique Perrault-Joncas, Alexander Volfovsky. TEA-Time: Transporting Effects Across Time. arXiv preprint arXiv:2603.07018, 2026

Qi Zhang, Harsh Parikh, Ashley Naimi, Razieh Nabi, Christopher Kim, Timothy Lash. Controllable Generative Sandbox for Causal Inference. Advances in Neural Information Processing Systems (NeurIPS), accepted, 2026

Bolun Liu, Sean McGrath, Yiren Hou, Elizabeth Stuart, Harsh Parikh. Characterizing Underrepresentation in Generalizing Causal Survival Estimates. Advances in Neural Information Processing Systems (NeurIPS), accepted, 2026

Grace V. Ringlein, Trang Q. Nguyen, Elizabeth A. Stuart, Harsh Parikh. Proximal causal inference through cross-proxy balancing. arXiv preprint arXiv:2609.38175, 2026

Harsh Parikh, Rachael K Ross, Elizabeth Stuart, Kara E Rudolph. Who Are We Missing?: A Principled Approach to Characterizing the Underrepresented Population. Journal of the American Statistical Association, 2025

Yiran Wang, Alicia E Boyd, Lillian Rountree, Yi Ren, Kate Nyhan, Ruchit Nagar, Jackson Higginbottom, Megan L Ranney, Harsh Parikh, Bhramar Mukherjee. Towards enhancing data equity in public health data science. arXiv preprint arXiv:2508.20301, 2025

Seyedeh Baharan Khatami, Harsh Parikh, Haowei Chen, Sudeepa Roy, Babak Salimi. Graph Machine Learning based Doubly Robust Estimator for Network Causal Effects. International Conference on Artificial Intelligence and Statistics (AISTATS), 2025

Quinn Lanners, Cynthia Rudin, Alexander Volfovsky, Harsh Parikh. Data fusion for partial identification of causal effects. Advances in Neural Information Processing Systems (NeurIPS), 2025

Harsh Parikh, Trang Quynh Nguyen, Elizabeth A Stuart, Kara E Rudolph, Caleb H Miles. A cautionary tale on integrating studies with disparate outcome measures for causal inference. Advances in Neural Information Processing Systems (NeurIPS), 2025

Grace V Ringlein, Trang Quynh Nguyen, Peter P Zandi, Elizabeth A Stuart, Harsh Parikh. Demystifying Proximal Causal Inference. arXiv preprint arXiv:2512.24413, 2025

Emily K Johnson, Harsh Parikh, Kim Rose Olsen, Angela Y Chang, Liza Sopina. Breast cancer and income loss in Denmark: heterogeneous outcomes and longitudinal effects. Nature Communications, 2025

C DeSisto, H Parikh, R Rasolofoson. Forest Conservation via Agroforestry: Causal Evidence from Vanilla Cultivation in Madagascar. AGU25, 2025

CFPM de Sousa, Harsh Parikh, JD Bradley, Elizabeth Stuart, C Hu. Representativeness and Generalizability of NCI-Funded Multi-Modality Randomized Clinical Trials (RCTs): A Case Study of Locally-Advanced Non-Small Cell Lung Cancer (LA-NSCLC …. International Journal of Radiation Oncology, Biology, Physics, 2025

Srikar Katta, Harsh Parikh, Cynthia Rudin, Alexander Volfovsky. Interpretable causal inference for analyzing wearable, sensor, and distributional data. International Conference on Artificial Intelligence and Statistics (AISTATS), 2024

Melody Y Huang, Harsh Parikh. Toward generalizing inferences from trials to target populations. Harvard Data Science Review, 2024

Harsh Parikh^*, Quinn M Lanners^*, Zade Akras, Sahar Zafar, M Brandon Westover, Cynthia Rudin, Alexander Volfovsky. Safe and interpretable estimation of optimal treatment regimes. International Conference on Artificial Intelligence and Statistics (AISTATS), 2024 co-first author

Harsh Parikh, Haoqi Sun, Rajesh Amerineni, Eric S Rosenthal, Alexander Volfovsky, Cynthia Rudin, M Brandon Westover, Sahar F Zafar. How many patients do you need? Investigating trial designs for anti‐seizure treatment in acute brain injury patients. Annals of Clinical and Translational Neurology, 2024

Harsh Parikh^*, Kentaro Hoffman^*, Haoqi Sun^*, Sahar F Zafar, Wendong Ge, Jin Jing, Lin Liu, Jimeng Sun, Aaron Struck, Alexander Volfovsky, Cynthia Rudin, M Brandon Westover. Effects of epileptiform activity on discharge outcome in critically ill patients in the USA: a retrospective cross-sectional study. The Lancet Digital Health, 2023 co-first author

Quinn Lanners, Harsh Parikh, Alexander Volfovsky, Cynthia Rudin, David Page. Variable importance matching for causal inference. Conference on Uncertainty in Artificial Intelligence (UAI), 2023

Harsh J Parikh. Causal inference for high-stakes decisions. Duke University, 2023

Harsh Parikh. Synthetic Control as Balancing Scores. International Conference on Learning Representations (ICLR), Tiny Papers, 2023

Harsh Parikh, Carlos Varjao, Louise Xu, Eric Tchetgen Tchetgen. Validating causal inference methods. International Conference on Machine Learning (ICML), 2022

Harsh Parikh, Alexander Volfovsky, Cynthia Rudin. MALTS: Matching After Learning to Stretch. Journal of Machine Learning Research, 2022

Haoning Jiang, Thomas Howell, Neha R Gupta, Vittorio Orlandi, Marco Morucci, Harsh Parikh, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky. AME: Interpretable Almost Exact Matching for Causal Inference. Advances in Neural Information Processing Systems (NeurIPS), Demonstrations Track, 2022

Amir Gilad, Harsh Parikh, Sudeepa Roy, Babak Salimi. Heterogeneous Treatment Effects in Social Networks. arXiv preprint arXiv:2105.10591, 2021

Babak Salimi, Harsh Parikh, Moe Kayali, Lise Getoor, Sudeepa Roy, Dan Suciu. Causal relational learning. Proceedings of the 2020 ACM SIGMOD international conference on management of …, 2020

Sarul Malik, Harsh Parikh, Neil Shah, Sneh Anand, Shalini Gupta. Non‐invasive platform to estimate fasting blood glucose levels from salivary electrochemical parameters. Healthcare Technology Letters, 2019

Harsh Parikh, Cynthia Rudin, Alexander Volfovsky. An Application of Matching After Learning To Stretch (MALTS). Observational Studies, 2019

H Parikh, K McQuiston, S Zhi. The impact of market conditions on active equity management. The Journal of Portfolio Management 44 (3), 89-101, 2018

Shayoni Dutta, Spandan Madan, Harsh Parikh, Durai Sundar. An ensemble micro neural network approach for elucidating interactions between zinc finger proteins and their target DNA. BMC Genomics, 2016

Sarul Malik, Shalini Gupta, Harsh Parikh, Sneh Anand. Gargling affect on salivary electrochemical parameters to predict blood glucose. IEEE International Conference on Computational Techniques in Information and Communication Technologies (ICCTICT), 2016

Harsh Parikh, Apoorvi Singh, Annangarachari Krishnamachari, Kushal Shah. Computational prediction of origin of replication in bacterial genomes using correlated entropy measure (CEM). Biosystems, 2015

Alok Shankar Mysore, Vikas S Yaligar, Imanol Arrieta Ibarra, Camelia Simoiu, Sharad Goel, Ramesh Arvind, Chiraag Sumanth, Arvind Srikantan, Bhargav HS, Mayank Pahadia, Tushar Dobha, Atif Ahmed, Mani Shankar, Himani Agarwal, Rajat Agarwal, Sai Anirudh-Kondaveeti, Shashank Arun-Gokhale, Aayush Attri, Arpita Chandra, Yogitha Chilukur, Sharath Dharmaji, Deepak Garg, Naman Gupta, Paras Gupta, Glincy Mary Jacob, Siddharth Jain, Shashank Joshi, Tarun Khajuria, Sameeksha Khillan, Sandeep Konam, Praveen Kumar-Kolla, Sahil Loomba, Rachit Madan, Akshansh Maharaja, Vidit Mathur, Bharat Munshi, Mohammed Nawazish, Venkata Neehar-Kurukunda, Venkat Nirmal-Gavarraju, Sonali Parashar, Harsh Parikh, Avinash Paritala, Amit Patil, Rahul Phatak, Mandar Pradhan, Abhilasha Ravichander, Krishna Sangeeth, Sreecharan Sankaranarayanan, Vibhor Sehgal, Ashrith Sheshan, Suprajha Shibiraj, Aditya Singh, Anjali Singh, Prashant Sinha, Pushkin Soni, Bipin Thomas, Kasyap Varma-Dattada, Sukanya Venkataraman, Pulkit Verma, Ishan Yelurwar. Investigating the" wisdom of crowds" at scale. Adjunct Proceedings of the 28th Annual ACM Symposium on User Interface …, 2015