Publications

I'm interested in how robots can learn structured, uncertainty-aware representations of the world and human intent through interaction and feedback.

* Equal Contribution† Equal Advising

Representative works are highlighted

Pre-Prints

An Exploratory Study of Bayesian Prompt Optimization for Test-Driven Code Generation with Large Language Models

S. Tomar, A. Deshwal, E. Villalovoz, M. Fazzini, H. Cai, J.R. Doppa

arXiv, 2025

Explores Bayesian optimization as a principled approach to automated prompt search for large language model–based code generation. Demonstrates sample-efficient improvements in functional correctness over strong prompting baselines on the HumanEval+ benchmark.

Paper

2023

Social Triangles and Aggressive Lines: Multi-Robot Formations Impact Navigation and Approach

A. Bacula, E. Villalovoz, D. Flynn, A. Mehta, H. Knight

International Conference on Intelligent Robots and Systems (IROS), 2023

Investigates how different multi-robot formations affect navigation and approach behaviors in social environments. Demonstrates the impact of formation geometry on human-robot interaction and navigation efficiency.

Paper