Publications
Harsh Parikh, Rachael K Ross, Elizabeth Stuart, and Kara E Rudolph. Who are we missing?: A principled approach to characterizing the underrepresented population. Journal of the American Statistical Association, 2025
David Arbour*, Harsh Parikh*, Bijan Niknam, Elizabeth Stuart, Kara Rudolph, and Avi Feller. Regularizing extrapolation in causal inference. arXiv:2509.17180, 2025 Accepted AISTATS
Harsh Parikh, Trang Quynh Nguyen, Elizabeth A Stuart, Kara E Rudolph, and Caleb H Miles. A cautionary tale on integrating studies with disparate outcome measures for causal inference. arXiv:2505.11014, 2025 Accepted NeurIPS
Quinn Lanners, Cynthia Rudin, Alexander Volfovsky, and Harsh Parikh. Data fusion for partial identification of causal effects. arXiv:2505.24296, 2025 Accepted NeurIPS
Harsh Parikh*, Marco Morucci*, Vittorio Orlandi*, Sudeepa Roy, Cynthia Rudin, and Alexander Volfovsky. A double machine learning approach to combining experimental and observational data. Observational Studies, 2025
Emily K Johnson, Harsh Parikh, Kim Rose Olsen, Angela Y Chang, and Liza Sopina. Breast cancer and income loss in Denmark: heterogeneous outcomes and longitudinal effects. Nature Communications, 2025
Carly L Brantner, Trang Quynh Nguyen, Harsh Parikh, Congwen Zhao, Hwanhee Hong, and Elizabeth A Stuart. Precision mental health: predicting heterogeneous treatment effects for depression through data integration. Journal of the Royal Statistical Society Series C, 2025
Seyedeh Baharan Khatami, Harsh Parikh, Haowei Chen, Sudeepa Roy, and Babak Salimi. Graph machine learning based doubly robust estimator for network causal effects. AISTATS, 258:4366–4374, 2025
Harsh Parikh*, Quinn Lanners*, Zade Akras, Sahar F Zafar, M Brandon Westover, Cynthia Rudin, and Alexander Volfovsky. Estimating trustworthy and safe optimal treatment regimes. AISTATS, 2024
Srikar Katta, Harsh Parikh, Cynthia Rudin, and Alexander Volfovsky. Interpretable causal inference for analyzing wearable, sensor, and distributional data. AISTATS, 2024 Early Career Paper Award, Biometrics JSM
Harsh Parikh, Carlos Varjao, Louise Xu, and Eric Tchetgen Tchetgen. Validating causal inference methods. ICML, pages 17346–17358, 2022
Babak Salimi, Harsh Parikh, Moe Kayali, Lise Getoor, Sudeepa Roy, and Dan Suciu. Causal relational learning. ACM SIGMOD, pages 241–256, 2020
Quinn Lanners, Harsh Parikh, Alexander Volfovsky, Cynthia Rudin, and David Page. Variable importance matching for causal inference. UAI, pages 1174–1184, 2023
Melody Y Huang and Harsh Parikh. Towards generalizing inferences from trials to target populations. Harvard Data Science Review, 6(4), 2024
Harsh Parikh, Alexander Volfovsky, and Cynthia Rudin. MALTS: Matching After Learning to Stretch. Journal of Machine Learning Research, 23(240), 2022
Harsh Parikh*, Kentaro Hoffman*, Haoqi Sun*, Sahar F Zafar, Wendong Ge, Jin Jing, Lin Liu, Jimeng Sun, Aaron Struck, Alexander Volfovsky, Cynthia Rudin, and M Brandon Westover. Effects of epileptiform activity on discharge outcome in critically ill patients in the USA. The Lancet Digital Health, 2023
Harsh Parikh, Haoqi Sun, Rajesh Amerineni, Eric Rosenthal, Alexander Volfovsky, Cynthia Rudin, M Brandon Westover, and Sahar F Zafar. How many patients do you need? Investigating trial designs for anti-seizure treatment. Annals of Clinical and Translational Neurology, 2024
Harsh Parikh, Cynthia Rudin, and Alexander Volfovsky. An application of Matching After Learning To Stretch (MALTS). Observational Studies, 5:118–130, 2019
Sarul Malik, Harsh Parikh, Neil Shah, Sneh Anand, and Shalini Gupta. Non-invasive platform to estimate fasting blood glucose levels from salivary electrochemical parameters. Healthcare Technology Letters, 6(4):87–91, 2019
Shayoni Dutta, Spandan Madan, Harsh Parikh, and Durai Sundar. An ensemble micro neural network approach for elucidating interactions between zinc finger proteins and their target DNA. BMC Genomics, 17(13):97–107, 2016
Harsh Parikh, Apoorvi Singh, Annangarachari Krishnamachari, and Kushal Shah. Computational prediction of origin of replication in bacterial genomes using correlated entropy measure (CEM). Biosystems, 128:19–25, 2015
Harsh Parikh. Synthetic controls as balancing scores. ICLR 2023, Tiny Papers, 2023
Sarul Malik, Shalini Gupta, Harsh Parikh, and Sneh Anand. Gargling affect on salivary electrochemical parameters to predict blood glucose. ICCTICT, pages 603–606, IEEE, 2016
Honors & Awards
2024Future Leader in Data Science and AI, Michigan Institute for Data & AI in Society
2024Selected for Building Future Faculty Program, North Carolina State University
2023Outstanding PhD Dissertation Award, Dept. of Computer Science, Duke University
2023Uncertainty in Artificial Intelligence Conference Travel Award
2022Finalist, Two Sigma PhD Fellowship
2022International Conference on Machine Learning Conference Travel Award
2022Certificate in College Teaching, Duke University
2020–22Amazon Graduate Research Fellowship
2020Invited Talk, IIT Gandhinagar "Sabarmati Young Researcher's Seminar Series"
2016–18Duke Economics Master's Scholar Award, Duke University
2016Runner's Up, Global Healthcare Summit (Non-invasive blood glucose sensor)
2013–14Charpak (Student Exchange) French Government Scholarship, University of Lorraine
2013Summer Undergraduate Research Award (UROP), IIT Delhi
2011–12IIT Delhi Semester Merit Award
2012Runner's Up, CanSat USA by AAS, AIAA, JPL, NASA, NRL
2009–11Manish Bhatt Scholarship, Excellence in Computer Science