Summary
Kuk Jang is a postdoctoral researcher at the University of Pennsylvania with 11 years of experience advancing trustworthy AI for healthcare and robotics. He combines a strong foundation in ML and algorithm development with practical skills in Python-based deep learning to improve classification accuracy and motion prediction in real-world systems. Author of 30+ publications and a decorated researcher, he now focuses on generative AI (LLMs, VLMs, diffusion) with emphases on uncertainty quantification, multimodal learning, and compute-efficient methods for real-time deployment. His training spans PhD-level electrical and systems engineering, MA statistics at Wharton, and engineering degrees from Princeton and Brown, giving him both theoretical rigor and applied insight. Notably, he has translated academic research into applied projects throughout extended tenures at UPenn and KETI, making him adept at bridging lab advances and engineered systems. He is motivated to apply his research-driven engineering to build reliable, real-time AI solutions in safety-critical domains.
11 years of coding experience
3 years of employment as a software developer
Master of Arts - MA, Statistics, Master of Arts - MA, Statistics at The Wharton School
Master of Engineering, Electrical Engineering, Master of Engineering, Electrical Engineering at Princeton University
Bachelor of Science (BS), Computer Engineering, Bachelor of Science (BS), Computer Engineering at Brown University
Doctor of Philosophy (Ph.D.), Electrical and Systems Engineering, Doctor of Philosophy (Ph.D.), Electrical and Systems Engineering at University of Pennsylvania
Korean, English