Seungwook Han
PHD Student at Massachusetts Institute of Technology
Cambridge, Massachusetts, United States
Summary
👤
Senior🎓
Top SchoolSeungwook Han is a PhD student at MIT CSAIL focused on generative modeling and representation learning, bringing eight years of research and engineering experience across academia and industry. He previously worked as a Research Software Engineer at IBM Research (MIT-IBM Watson AI Lab) and held research roles at Columbia and KIST, combining production-ready AI engineering with deep experimental skills. His background spans software internships and product management alongside early research at Yonsei, reflecting an ability to translate research ideas into practical systems. Based in Cambridge, he pairs a Columbia CS-Statistics foundation with PhD-level AI training, and his trajectory suggests strong competence in both model innovation and scalable implementation. Notably, his profile blends military intelligence analysis experience with advanced ML research, indicating disciplined analytical thinking and diverse problem-solving perspectives.
8 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD, Artificial Intelligence, Doctor of Philosophy - PhD, Artificial Intelligence at Massachusetts Institute of TechnologyBachelor of Arts (B.A.), Computer Science-Statistics, Bachelor of Arts (B.A.), Computer Science-Statistics at Columbia University in the City of New YorkHigh School Diploma, High School Diploma at Seoul International School
English, Korean, Spanish
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (30)
api8
api-documentation8
computer-graphics7
computer-vision6
nlp6
language-modeling6
openai-api6
deep-learning5
reinforcement-learning5
machine-learning5
chatgpt5
pytorch5
representation-learning4
llm4
transformer4
Programming languages (2)
Github contributions (5)
hanseungwook/BigGAN-PyTorch
May 2020 - Sep 2020
The author's officially unofficial PyTorch BigGAN implementation.
Contributions:244 pushes, 7 branches in 4 months
deep-learningpytorchbiggan
hanseungwook/cavia
Mar 2020 - Mar 2021
Code for "Fast Context Adaptation via Meta-Learning"
Contributions:228 pushes, 2 branches in 1 year
pytorchmeta-learningdeep-learningmetaadaptation
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