Flint Water Crisis: Data-Driven Risk Assessment Via Residential Water Testing. - Jacob D. Abernethy; Cyrus Anderson; Chengyu Dai; Arya Farahi; Linh Nguyen; Adam Rauh; Eric M. Schwartz; Wenbo Shen; Guangsha Shi; Jonathan C. Stroud; Xinyu Tan; Jared Webb; et al. (CoRR, 2016)

A Data Science Approach to Understanding Residential Water Contamination in Flint. - Alex Chojnacki; Chengyu Dai; Arya Farahi; Guangsha Shi; Jared Webb; Daniel T. Zhang; Jacob D. Abernethy; Eric M. Schwartz (KDD, 2017)

Driving with Data: Modeling and Forecasting Vehicle Fleet Maintenance in Detroit. - Josh Gardner 001; Danai Koutra; Jawad Mroueh; Victor Pang; Arya Farahi; Sam Krassenstein; Jared Webb (CoRR, 2017)

The Michigan Data Science Team: A Data Science Education Program with Significant Social Impact. - Arya Farahi; Jonathan C. Stroud (DSW, 2018)

ActiveRemediation: The Search for Lead Pipes in Flint, Michigan. - Jacob D. Abernethy; Alex Chojnacki; Arya Farahi; Eric M. Schwartz; Jared Webb (KDD, 2018)

Driving with Data in the Motor City: Understanding and Predicting Fleet Maintenance Patterns. - Josh Gardner 001; Jawad Mroueh; Natalia Jenuwine; Noah Weaverdyck; Samuel Krassenstein; Arya Farahi; Danai Koutra (DSAA, 2020)

Driving with Data in the Motor City: Mining and Modeling Vehicle Fleet Maintenance Data. - Josh Gardner 001; Jawad Mroueh; Natalia Jenuwine; Noah Weaverdyck; Samuel Krassenstein; Arya Farahi; Danai Koutra (CoRR, 2020)

TATTER: A hypothesis testing tool for multi-dimensional data. - Arya Farahi; Yang Chen 063 (Astron. Comput., 2021)

TAME Pain: Trustworthy AssessMEnt of Pain from Speech and Audio for the Empowerment of Patients. - Eike Schneiders; Jennifer Williams 001; Arya Farahi; Tina Seabrooke; Ganesh Vigneswaran; John Robert Bautista; Liz Dowthwaite; Anna-Maria Piskopani (TAS, 2023)

C 2-GaMe: Classification of cluster galaxy membership with machine learning. - D. Farid; Han Aung; D. Nagai; Arya Farahi; E. Rozo (Astron. Comput., 2023)

U-trustworthy Models. Reliability, Competence, and Confidence in Decision-Making. - Ritwik Vashistha; Arya Farahi (AAAI, 2024)

Predicting Acute Pain Levels Implicitly from Vocal Features. - Jennifer Williams 001; Eike Schneiders; Henry Card; Tina Seabrooke; Beatrice Pakenham-Walsh; Tayyaba Azim; Lucy Valls-Reed; Ganesh Vigneswaran; John Robert Bautista; Rohan Chandra; Arya Farahi (INTERSPEECH, 2024)

Responsible MLOps Design Methodology for an Auditing System for AI-Based Clinical Decision Support Systems. - Pepita Barnard; John Robert Bautista; Aidan Dakhama; Arya Farahi; Kazim Laos; Anqi Liu; Héctor D. Menéndez 001 (ICTSS, 2024)

Insights from explainable AI in oesophageal cancer team decisions. - Navamayooran Thavanesan; Arya Farahi; Charlotte Parfitt; Zehor Belkhatir; Tayyaba Azim; Elvira Perez Vallejos; Zoë Walters; Sarvapali D. Ramchurn; Timothy J. Underwood; Ganesh Vigneswaran (Comput. Biol. Medicine, 2024)

U-Trustworthy Models.Reliability, Competence, and Confidence in Decision-Making. - Ritwik Vashistha; Arya Farahi (CoRR, 2024)

How DREAMS are made: Emulating Satellite Galaxy and Subhalo Populations with Diffusion Models and Point Clouds. - Tri Nguyen; Francisco Villaescusa-Navarro; Siddharth Mishra-Sharma; Carolina Cuesta-Lázaro; Paul Torrey; Arya Farahi; Alex M. Garcia; Jonah C. Rose; Stephanie O'Neil; Mark Vogelsberger; Xuejian Shen; Cian Roche; et al. (CoRR, 2024)

Fire and smoke digital twin - A computational framework for modeling fire incident outcomes. - Ryan Hardesty Lewis; Junfeng Jiao; Kijin Seong; Arya Farahi; Paul A. Navrátil; Nate Casebeer; Dev Niyogi (Comput. Environ. Urban Syst., 2024)

I-trustworthy Models. A framework for trustworthiness evaluation of probabilistic classifiers. - Ritwik Vashistha; Arya Farahi (AISTATS, 2025)