I am an AI engineer and part-time researcher working on the reliability of language models (LMs). I am fortunate enough to have received the NSF CISE Graduate Fellowship (CSGrad4US) and am applying to CS PhD programs for the Fall 2027 cycle.
Research
I am most interested in the question of how to make LMs more verifiably aligned in unverifiable domains. My most recent research takes a game theoretic approach towards identifying reliable LM training signals in cases where ground truth is unavailable, though I have also explored this via traditional RAG and RL-alignment work in the past. Towards this question, I believe policy, law, and morality are excellent testbeds, given their inherent ambiguity and real-world applicability.
Dayjob
I am currently an AI engineer within the R&D department at Five Strand Technologies, where I work on rapid prototyping for better anti-money laundering, on-chain analytics, and federal compliance.
Some things I've done in the past:
- AI Governance: Contributed to GPAI hazard taxonomies aimed at policymakers in the CEN-CENELEC JTC 21, the committee drafting technical standards for the EU AI Act.
- Federal: Worked on automated NLP/text analytics platforms for the U.S. Department of Defense (NSIN) and the United States Navy.
- Industry: Worked on customer analytics at Adobe and loan-process analytics at PNC Financial Services.
Personal
Beyond my professional and academic interests, I am an avid fan of all things gamified problem-solving: board games, escape rooms, speed puzzling, and murder mysteries. I also enjoy rucking and games prototyping.