Eunjeong Hwang is a PhD candidate in Computer Science at the University of British Columbia and an experienced researcher-engineer with eight years in industry and academia. Her work centers on conversational implicit cues and adaptive AI models, with recent internships and collaborations at Megagon Labs, OpenAI, Google DeepMind, MIT-IBM Watson AI Lab, and AI2. She blends hands-on engineering experience from roles at NAVER and IBM Korea with deep research in personalization, graph neural networks, and knowledge-grounded QA. Eunjeong has repeatedly contributed to short-term high-impact projects—such as an OpenAI red team fellowship that spun into follow-up work—and currently explores post-training methods for large language models. Fluent at navigating both production knowledge-base systems and cutting-edge research environments, she brings practical deployment sensibilities to theoretically driven problems. Based in Canada, she pairs a global academic background with a knack for turning nuanced conversational signals into adaptable ML systems.
8 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at The University of British Columbia
Master's degree, Computer Science, Master's degree, Computer Science at University of Massachusetts Amherst
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at Kwangwoon University
Exchange Student, Computer Science, Exchange Student, Computer Science at University of Nebraska at Kearney
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