Publications

Current projects

• My early focus with Professor Kuchibhotla has centered on inference under minimal assumptions in online settings. To demonstrate the utility of inference via his work, “Confidence Regions from Convex Hulls” (HulC), I ran simulations to compare HulC-based confidence intervals using stochastic gradient descent against traditional methods. We are drafting a paper on these results. As a member of CMU’s Statistical Machine Learning Reading Group, I presented our early results in February 2024 as well as proof sketches from Chen et al’s “Statistical Inference for Model Parameters in Stochastic Gradient Descent”.

• Disaster management using uncertainty quantification in reinforcement learning (AI Institute for Societal Decision Making at CMU), topic of 2024 summer research

Submitted papers and pre-prints

• (Pre-print) Meyer, M. J., Carter, S., Mordukhovich, I., McNeely, E., Malloy, E. J. “Model Selection in Variational Mixed Effects Models.” arXiv preprint arXiv:2206.04012 (2022).
• (Pre-print) Hersh J., Carter S. “Explainable AI Helps Bridge the AI Skills Gap: Evidence from a Large Bank.” Chapman University Digital Commons.
• “Modeling COVID-19 testing rates by occupation among U.S. adults.” Advanced Data Analysis Project (required for second-year PhD students in statistics at CMU), advised by Alex Reinhart and Robin Mejia.

Conferences

• “Will AI Accelerate the Intra-Firm Digital Divide? Evidence from a Field Experiment on How Managers use Explainable AI” (Presented by co-author Jonathan Hersh)
  • MIT Conference on Digital Experimentation (CODE) (11/10/2023)
  • Wharton/Columbia Management, Analytics and Data (MAD) (5/19/2023)
  • USC Artificial Intelligence in Management, AIM 2023 (3/16/2023) – Best PhD Student Paper Award
  • Statistical Challenges in E-Commerce Research (6/2022)
  • Global Conference on Innovations in Management and Business (2021)
  • INFORMS Conference on Information Systems & Technology (CIST) (2020)
• Predicting Delays at the Inter-American Development Bank Using R. R-Gov Conference (Lander Analytics and Georgetown University). recording (12/2020)
• How Are Ideas Spread at Your Organization? Analyze Its Citation Network. R-Gov Conference (Lander Analytics and Georgetown University). recording (11/2019)
• The IDB Loan Network: Assessing the Role of Impact Evaluations. Sunbelt 2019 (International Network for Social Network Analysis, Montreal). (6/2019) Check out the cool viz I made.