My Profile

Ruizhi (Ray) Liao | 廖睿智

PhD student at CSAIL/EECS, MIT

I am a computer science PhD student at MIT, advised by Polina Golland. I study machine learning and develop computational tools driven by clinical problems. I'm excited about ubiquitous computing and its potential to advance health care. My PhD research has been supported by Merrill Lynch Fellowship and Siebel Fellowship.

I received my bachelor's degree from Tsinghua University in 2015. During my undergraduate study, I have been lucky to work with professors Weibei Dou (Tsinghua), Hongen Liao (Tsinghua), and Lauren O'Donnell (BWH, HMS). I interned at Oculus Research (now Facebook Reality Labs) in the summer of 2017.


Massachusetts Institute of Technology2015 - 2021 (expected)
Ph.D. student

Tsinghua University2011 - 2015

Publications [Google Scholar]

R. Liao, D. Moyer, M. Cha, K. Quigley, S. Berkowitz, S. Horng, P. Golland, W. Wells
Multimodal Representation Learning via Maximization of Local Mutual Information.
International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021.

R. Liao, D. Moyer, P. Golland, W. Wells
DEMI: Discriminative Estimator of Mutual Information.
[PDF] [code]

G. Chauhan*, R. Liao*, W. Wells, J. Andreas, X. Wang, S. Berkowitz, S. Horng, P. Szolovits, P. Golland
Joint Modeling of Chest Radiographs and Radiology Reports for Pulmonary Edema Assessment.
International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2020. (* indicates equal contributions.)
[PDF] [code] [oral presentation] [MIT News]

S. Horng*, R. Liao*, X. Wang, S. Dalal, P. Golland, S. Berkowitz
Deep Learning to Quantify Pulmonary Edema in Chest Radiographs.
Radiology: Artificial Intelligence. (* indicates equal contributions.)

R. Liao, J. Rubin, G. Lam, S. Berkowitz, S. Dalal, W. Wells, S. Horng, P. Golland
Semi-supervised Learning for Quantification of Pulmonary Edema in Chest X-Ray Images.

R. Liao, E. Turk, M. Zhang, J. Luo, E. Adalsteinsson, E. Grant, P. Golland
Temporal Registration in Application to In-utero MRI Time Series.
[PDF] [code]

R. Liao, L. Ning, Z. Chen, L. Rigolo, S. Gong, O. Pasternak, A. Golby, Y. Rathi, L. O'Donnell
Performance of Unscented Kalman Filter Tractography in Edema: Analysis of The Two-tensor Model.
NeuroImage: Clinical.

M. Zhang, R. Liao, A. Dalca, E. Turk, J. Luo, E. Grant, P. Golland
Frequency Diffeomorphisms for Efficient Image Registration.
International Conference on Information Processing in Medical Imaging (IPMI), 2017 (Oral presentation).

R. Liao, E. Turk, M. Zhang, J. Luo, E. Grant, E. Adalsteinsson, P. Golland
Temporal Registration in In-Utero Volumetric MRI Time Series.
International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2016.
[PDF] [code] [video] [MIT News]

R. Liao, W. Dou, M. Zhang, H. Chen, S. Li
A Framework for Mapping Scalable Human Brain Anatomical Networks via Diffusion MRI.
IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), 2016 (Oral presentation).

F. Chen, R. Liao, H. Liao
Fast Registration of Intraoperative Ultrasound and Preoperative MR Images Based on Calibrations of 2D and 3D Ultrasound Probes.
World Congress on Medical Physics and Biomedical Engineering, 2015.


Email: ruizhi [at]