Investigating the "Wisdom of Crowds" at Scale. - 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; et al. (UIST (Adjunct Volume), 2015)

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

Control of a Modular Multilevel Converter STATCOM under internal and external unbalances. - Georgios Tsolaridis; Epameinondas Kontos; Harsh Parikh; Ruben M. Sanchez-Loeches; Remus Teodorescu; Sanjay K. Chaudhary (IECON, 2016)

Causal Relational Learning. - Babak Salimi; Harsh Parikh; Moe Kayali; Lise Getoor; Sudeepa Roy 001; Dan Suciu (SIGMOD Conference, 2020)

Detecting Treatment Effect Modifiers in Social Networks. - Amir Gilad; Harsh Parikh; Babak Salimi; Sudeepa Roy 001 (CoRR, 2021)

Validating Causal Inference Methods. - Harsh Parikh; Carlos Varjao; Louise Xu; Eric Tchetgen Tchetgen (ICML, 2022)

Evaluating Causal Inference Methods. - Harsh Parikh; Carlos Varjao; Louise Xu; Eric Tchetgen Tchetgen (CoRR, 2022)

Why Interpretable Causal Inference is Important for High-Stakes Decision Making for Critically Ill Patients and How To Do It. - Harsh Parikh; Kentaro Hoffman; Haoqi Sun; Wendong Ge; Jin Jing; Rajesh Amerineni; Lin Liu; Jimeng Sun 001; Sahar Zafar; Aaron Struck; Alexander Volfovsky; Cynthia Rudin; et al. (CoRR, 2022)

Are Synthetic Control Weights Balancing Score? - Harsh Parikh (CoRR, 2022)

MALTS: Matching After Learning to Stretch. - Harsh Parikh; Cynthia Rudin; Alexander Volfovsky (J. Mach. Learn. Res., 2022)

Synthetic Controls as Balancing Scores. - Harsh Parikh (Tiny Papers @ ICLR, 2023)

Variable importance matching for causal inference. - Quinn Lanners; Harsh Parikh; Alexander Volfovsky; Cynthia Rudin; David Page (UAI, 2023)

From Feature Importance to Distance Metric: An Almost Exact Matching Approach for Causal Inference. - Quinn Lanners; Harsh Parikh; Alexander Volfovsky; Cynthia Rudin; David Page (CoRR, 2023)

A Double Machine Learning Approach to Combining Experimental and Observational Data. - Marco Morucci; Vittorio Orlandi; Harsh Parikh; Sudeepa Roy 001; Cynthia Rudin; Alexander Volfovsky (CoRR, 2023)

Estimating Trustworthy and Safe Optimal Treatment Regimes. - Harsh Parikh; Quinn Lanners; Zade Akras; Sahar F. Zafar; M. Brandon Westover; Cynthia Rudin; Alexander Volfovsky (CoRR, 2023)

Interpretable Causal Inference for Analyzing Wearable, Sensor, and Distributional Data. - Srikar Katta; Harsh Parikh; Cynthia Rudin; Alexander Volfovsky (AISTATS, 2024)

Safe and Interpretable Estimation of Optimal Treatment Regimes. - Harsh Parikh; Quinn Lanners; Zade Akras; Sahar Zafar; M. Brandon Westover; Cynthia Rudin; Alexander Volfovsky (AISTATS, 2024)

Who Are We Missing? A Principled Approach to Characterizing the Underrepresented Population. - Harsh Parikh; Rachael Ross; Elizabeth A. Stuart; Kara E. Rudolph (CoRR, 2024)

Towards Generalizing Inferences from Trials to Target Populations. - Melody Y. Huang; Sarah E. Robertson; Harsh Parikh (CoRR, 2024)

Graph Neural Network based Double Machine Learning Estimator of Network Causal Effects. - Seyedeh Baharan Khatami; Harsh Parikh; Haowei Chen; Sudeepa Roy 001; Babak Salimi (CoRR, 2024)

American sign language classification using deep learning. - Harsh Parikh; Nisarg Panchal; Vraj Patel 002; Ankit K. Sharma (Int. J. Biom., 2024)

Graph Machine Learning based Doubly Robust Estimator for Network Causal Effects. - Seyedeh Baharan Khatami; Harsh Parikh; Haowei Chen; Sudeepa Roy 001; Babak Salimi (AISTATS, 2025)

A Cautionary Tale on Integrating Studies with Disparate Outcome Measures for Causal Inference. - Harsh Parikh; Trang Quynh Nguyen; Elizabeth A. Stuart; Kara E. Rudolph; Caleb H. Miles (CoRR, 2025)

Data Fusion for Partial Identification of Causal Effects. - Quinn Lanners; Cynthia Rudin; Alexander Volfovsky; Harsh Parikh (CoRR, 2025)