I work at the intersection of computer science, neuroscience, and cognitive science.

Full-time (industry): Senior Applied AI Scientist at Thomson Reuters, building agentic AI for legal research. Interested in developing the best technologies to build trustworthy intelligent systems.

Part-time (academia): Research Scientist with Mariya Toneva's BrAIN group at the Max Planck Institute for Software Systems. Interested in the computational underpinnings of intelligent behavior, particularly the use of memory and attention.

Previously I spent 5 years as a AI/ML Research Scientist at Intel in the Brain-Inspired Computing Lab. Highlights: collaborating with academics to work on NeuroAI with language models (starting in 2019), and work on LLM code generation for high-performance computing systems (2024).

• 10/2025: NeurIPS, accepted. Using in-context learning in LLMs to understand associative learning in humans.
• 10/2025: PsyArxiv, preprinted. Large-scale analysis of false memory in free recall of narratives.
• 02/2025: arXiv, preprinted. Position piece on how episodic memory can advance research on LLM agents.

• 12/2024: Workshop on Attributing Model Behavior at Scale, NeurIPS. Poster on optimizing vector similarity search and retrieval for retrieval augmented generation (RAG) systems
• 11/2024: Intel tech demo. Video demonstrating custom-built RAG application relying on the open-source Intel Scalable Vector Search library for fast data retrieval
• 08/2023: KDD (Knowledge Discovery & Data Mining). Served as an invited discussion panelist at LLM Day [website]