Hyewon Jeong 

Medical Doctor, M.S. in Computer Science

Brief Bio

Hello! I am a third-year Ph.D. Student at CSAIL, LIDS, IMES, RLE, and EECS at MIT under the supervision of Prof. Marzyeh Ghassemi and Prof. Collin Stultz. I have recently completed a master's in Computer Science at KAIST MLAI Lab (School of Computing at KAIST), doing research on Machine Learning for Health (under the guidance of prof. Sung Ju Hwang). Prior to studying at KAIST, I received a Medical Doctor (M.D.) degree from Yonsei University College of Medicine and studied Biological Sciences at KAIST.

Research Interest

I am broadly interested in Machine Learning for Healthcare, especially in representation learning for time series, signals, and image data. I am interested in fairness/robustness, representational learning, and causal inference.

As I was once a neuroscientist (did research under the guidance of prof. Seung-Hee Lee and prof. JaeJin Kim), I still have an interest in neuroscience as general: specifically its extension to the clinical field, neuro-inspired AI, and AI-inspired neuroscience. 

Past Research Interest: I used to do research in synthetic and systems biology, and I am proud that was served as a Team leader of the KAIST-Korea team of iGEM 2012 (We are the first team from Korea who won Gold prize from iGEM! This was done under the guidance of prof. Byung Kwan Cho). While in medical school, I used to be in wet lab, doing cancer cell research! I cultured spherical cell called Glioblastoma and did research on stemness, invasiveness of the cancer stem cell (Check out my paper, which was done under the guidance of prof. Seok-Gu Kang). 

News (2021~ onward)

2023. 12.10. I am serving as Research Roundtables Chair for ML4H 2023 co-located with NeurIPS 2023!

2023.11.02. We are presenting a work on Robust and fair time-to-event analysis for predicting cancer-associated Venous Thromboembolism (VTE) in ASHG 2023

2023.10.28. An abstract on event-based contrastive learning was accepted to UniReps NeurIPS Workshop!

2023.07.18. A paper on developing ML models and identifying predictive features for Fetal Alcohol Syndrome (FAS) was published in JMIR!

2023.07.11. A paper on Deep Metric Learning for Hemodynamics inference has been accepted to MLHC! See you there in New York! 

2022.10.21  Two papers have been accepted as Spotlight Posters in NeurIPS Workshops!

2022.07.22Happy to announce that I was invited to give a talk to Stanford MedAI Journal Club

2022.03.01.  A paper on Real-Time seizure detection (co-first author-ed) has been accepted to ACM CHIL 2022

2021. 09. 09.  I am starting my Ph.D. studies at MIT EECS with a  fellowship from JClinic! So excited to be in the Cambridge area again :D

2021. 02. 19.  I graduated from the School of Computing, KAIST with a Master of Science degree :)

2021. 02. 15.  I joined  AITRICS as a Medical Researcher! 


2021- Massachusetts Institute of Technology Ph.D. Student, EECS Cambridge, MA, USA

2019 – 2021          Korea Advanced Institute of Science and Technology (KAIST)  M.S. Candidate, School of Computing Daejeon, Republic of Korea

2015 – 2019  Yonsei University                                                         Medical Doctor, College of Medicine Seoul, Republic of Korea  

2009 – 2015  Korea Advanced Institute of Science and Technology (KAIST)   Bachelor of Science in Biological Sciences, Cum Laude Daejeon, Republic of  Korea 

2007 – 2009  Gwangju Science High School                                        Gwangju, Republic of Korea