James J. Kim
MS in CS @ Cornell University
I’m a MS student in Computer Science at Cornell, broadly interested in automating and accelerating scientific discovery. I’m fortunate to work with Jennifer Sun.
In a previous life, I developed computational models of brain-behavior dynamics in substance use addiction with Amy Kuceyeski in the CoCo Lab, and worked on real-time acoustic sensing for hand pose tracking in wearable tech with Cheng Zhang in the SciFi Lab.
Happy to chat.
Education
Ph.D. in Computer Science
Cornell University
2026 - Present
Advised by Jennifer Sun
M.S. in Computer Science
Cornell University
2025 - 2027
Fully-funded research-based MS (cohort size—7 )
GPA: 4.0
B.A. in Computer Science, B.A. in Mathematics
Cornell University
2021 - 2025
Distinction in All Subjects
GPA: 3.9
Publications
Manuscript in progress, Poster presented at OHBM '25
CHI'24 (ACM Conference on Human Factors in Computing Systems)
Research Experience
Graduate Research Assistant, Sun Lab @ Cornell University
Jun 2025 - Present
Developing AI agents and LLMs for scientific workflows
Research Assistant, CoCo Lab @ Weill Cornell Medicine
Jan 2024 - Present
Researching future heavy alcohol-use prediction via fMRI/dMRI connectome-behavior mapping with Dr. Amy Kuceyeski. Supported by the Bowers CIS Undergraduate Research Experience (BURE) program (Jun 2024 – Aug 2024)
Research Assistant, SciFi Lab @ Cornell University
Aug 2023 - May 2024
Developed EchoWrist in the SciFi Lab under Dr. Cheng Zhang—a wrist-worn device using active acoustic sensing to estimate 3D hand poses; led user studies to optimize design and explore clinical applications (published in CHI’24)
Work Experience
LLM Research Software Engineer Intern, Naval Sea Systems Command (NAVSEA)
Jul 2025 - Aug 2025
Fine-tuned lightweight LLMs for military NLP applications on edge devices. Advised by Dr. Jeonghun Noh
Software Engineer Intern, Southern California Edison (SCE)
May 2023 - Aug 2023
Contributed to internal GPT and NEM Billing for 15M+ users across 430 cities, reducing call volume by 22K+/month. Won the intern expo (1st out of 95 projects)
Teaching Experience
Graduate Teaching Assistant for Deep Learning (CS 4/5782), Cornell University
January 2026 - Present
Profs. Kilian Weinberger & Wei-Chiu Ma
Spring ‘26
Head Graduate Teaching Assistant for Machine Learning (CS 3/5780), Cornell University
Aug 2025 - December 2025
Prof. John Thickstun
Fall ‘25
Course Consultant for Data Structures and Functional Programming (CS 3110), Cornell University
Jan 2024 - Jan 2025
Prof. Michael Clarkson
Spring ‘24, Fall ‘24 (Received CS Course Staff Exceptional Service Award in SP’24)
Academic Service
Logistical Coordinator – Symposium Series, MELBA Journal
2024
Organized MELBA symposiums showcasing leading research in ML and biomedical imaging, promoting open access to scientific knowledge