research themes

data science and natural language processing toward critical informatics applications

trustworthy & interpretable machine learning

Responsible deployment of machine learning systems warrants careful consideration of potential failure modes and other limitations, such as hallucinations, opacity, and misalignment. Toward this end, recent work has examined uncertainty quantification (ICLR ‘26, arXiv ‘26) and obfuscated evil twin prompting (EMNLP ‘25, EMNLP ‘24) in large language models.

  1. SENECA: Small-Sample Discrete Entropy Estimation via Self-Consistent Missing Mass (Preprint 2026)
  2. Estimating Semantic Alphabet Size for LLM Uncertainty Quantification (ICLR 2026)
  3. Demystifying optimized prompts in language models (EMNLP 2025)
  4. Prompts have evil twins (EMNLP 2024)

public health data science & biomedical informatics

  1. Network analysis of U.S. non-fatal opioid-involved overdose journeys, 2018–2023 (Appl. Netw. Sci. 2024)
  2. cosasi: Graph Diffusion Source Inference in Python (JOSS 2022)
  3. Surveillance nanotechnology for multi-organ cancer metastases (Nature BME 2017)

applications in logistics & engineering

  1. Large Language Model Agents as Prognostics and Health Management Copilots (PHM 2024)
  2. Modeling the Operational Feasibility of Synfuel from Seawater (Preprint 2023)
  3. Modeling Fuel Replenishment Logistics and Impacts of Alternative Synthetic Fuels (I/ITSEC 2022)