I’m a postdoctoral research fellow at the University of Michigan Weinberg Institute for Cognitive Science working at the intersection of natural language processing (NLP) and cognitive science. My research leverages insights from how humans learn and reason with language to better understand the capabilities of AI language models and improve their effectiveness in downstream assistive applications. I also appraise the broader impacts of these models and other research trends to inform NLP practice and policy. I organize and volunteer for Queer in AI and Macomb Science Olympiad to promote diversity and opportunity in STEM.
2024, University of Michigan
Dissertation: Coherent Physical Commonsense Reasoning in Foundational Language Models
Advisor: Dr. Joyce Chai
2021, University of Michigan
2018, Lawrence Technological University
Research publications, preprints, and any associated presentation materials. * indicates equal contribution.
Other talks and guest lectures.
Courses I've instructed. If you want to learn more, feel free to send me an email!
Instructor of Record, University of Michigan
Non-computer science introductory course for large language models (LLMs) co-led with Andrew McInnerney. Topics include language modeling (from early rule-based and statistical approaches to modern LLMs), machine learning and deep learning basics, and the applications and implications of LLMs.
Weinberg Institute for Cognitive ScienceGraduate Student Instructor, University of Michigan
Graduate introductory NLP course led by Joyce Chai. Topics include syntax, semantics, discourse, deep learning for NLP, large language models, and their applications in information extraction, machine translation, and dialogue systems.
Electrical Engineering and Computer Science (EECS)Graduate Student Instructor, University of Michigan
Graduate introductory NLP course led by Joyce Chai. Topics include syntax, semantics, discourse, deep learning for NLP, large language models, and their applications in information extraction, machine translation, and dialogue systems.
Electrical Engineering and Computer Science (EECS)Graduate Student Instructor, University of Michigan
Graduate introductory NLP course led by Joyce Chai. Topics include syntax, semantics, discourse, deep learning for NLP, large language models, and their applications in information extraction, machine translation, and dialogue systems.
Electrical Engineering and Computer Science (EECS)Professional appointments in industry.
Applied Scientist Intern
Natural Understanding, Teachable AI team (remote). Completed a self-contained research project on multi-hop reasoning advised by mentors Qiaozi Gao and Govind Thattai.
Sunnyvale, CA, USAApplied Scientist Intern
Natural Understanding, Teachable AI team (remote). Completed a self-contained research project on embodied instruction following advised by mentor Qiaozi Gao.
Sunnyvale, CA, USAJunior .NET Developer and Data Analyst
Used C#, VB.NET, and .SQL to create and maintain company databases, warehouse management applications, telemetric data stream processors, and big data visualizations.
Warren, MI, USAJunior Programmer
Used Visual C# to build and modify user interfaces for automotive assembly machines including fluid fill and alignment.
Roseville, MI, USATechnical Assistant
Authored and prepared technical manuals for automotive assembly machines. Synthesized schematic diagrams of fluid and electric circuits with input from subject matter experts.
Roseville, MI, USAUnpublished course projects and side projects. Ask me about them if you're interested!
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