Magentic, Nov. 2025 - Present
Founding AI Engineer
• Introduced Magentic's first agent and lead the ongoing development of its architecture, validating design choices through experimentation against eval suites built from real procurement data
• Continuously improving system reliability through an iterative loop combining hillclimbing, feedback integration, and model routing as new data and edge cases emerge
• Embedding human-in-the-loop design throughout, balancing agent autonomy with oversight to match the risk profile of procurement and supply chain stakeholders
• Continuously improving system reliability through an iterative loop combining hillclimbing, feedback integration, and model routing as new data and edge cases emerge
• Embedding human-in-the-loop design throughout, balancing agent autonomy with oversight to match the risk profile of procurement and supply chain stakeholders
Dynamo AI, Nov. 2024 - Oct. 2025
ML Research Scientist
• Led the research team developing agentic red-team evaluations for LLMs, targeting custom safety specifications in conversational and tool-using agents
• Designed automated pipelines to increase adversarial coverage and behavioral diversity across evaluation scenarios
• Contributed to core research efforts, including a first-author paper on the robustness of LLM safety judges and a medical benchmarking hallucination paper
• Designed automated pipelines to increase adversarial coverage and behavioral diversity across evaluation scenarios
• Contributed to core research efforts, including a first-author paper on the robustness of LLM safety judges and a medical benchmarking hallucination paper
Five, Dec. 2022 - Jun. 2023
Research Scientist Intern
Worked on efficient methods to perform zero-shot and weakly-supervised referring image segmentation (i.e., segmenting an object in an image that is referred in a natural language sentence), achieving new state-of-the-art performance in the field.
Five, Jun. 2021 - Sep. 2021
Research Scientist Intern
Extended the certified robustness technique of randomized smoothing from isotropic ℓp balls to anisotropic certificates through a simplified Lipschitz analysis-based framework.
Five, Sep. 2018 - Sep. 2020
Research Engineer
• Led the development of safe and scalable optimization-based motion planning algorithms, working in a team with research scientists and software engineers
• Published and presented research work developed at top tier conferences and journals within the robotics community, as well as to non-technical audiences
• Wrote and reviewed research and development code, ensuring CI with other tools within the company
• Published and presented research work developed at top tier conferences and journals within the robotics community, as well as to non-technical audiences
• Wrote and reviewed research and development code, ensuring CI with other tools within the company