Richard J. Chen

I am a Ph.D. Candidate advised by Faisal Mahmood at Harvard University, and also within Brigham and Women’s Hospital, Dana-Farber Cancer Institute, and the Broad Institute.

Prior to starting my Ph.D., I obtained my B.S/M.S. in Biomedical Engineering and Computer Science at Johns Hopkins University, where I worked with Nicholas Durr and Alan Yuille. I am fortunate to have also spent time working at worked at Apple Inc. in the Health Special Project and Applied Machine Learning Groups (with Belle Tseng and Andrew Trister), Microsoft Research in the BioML Group (with Rahul Gopalkrishnan), and at the National Institutes of Health in NIBIB (with Richard Leapman).

Research Highlights

Please feel free to contact me through email if you have any questions and interest in collaborating!

Recent News

Aug, 2021 Excited to announce that the preprint for PORPOISE, our Pathology-Omic Research Platform for Integrated Survival Estimation, is out (with its associated demo)!
Jul, 2021 Two papers, Patch-GCN and Multimodal Co-Attention Transformers (MCAT), were accepted into MICCAI 2021 and ICCV 2021 respectively.
Jun, 2021 Joined Microsoft Research as an PhD Research Intern, working with Rahul Gopalkrishnan in the BioML Group.
Jun, 2021 Passed my Qualifying Exam, and am now officially a PhD Candidate!

Select Publications

  1. Developing Measures of Cognitive Impairment in the Real World from Consumer-Grade Multimodal Sensor Streams
    Richard J. Chen, Filip Jankovic, Nikki Marinsek, Luca Foschini, Lampros Kourtis, Alessio Signorini, Melissa Pugh, Jie Shen, Roy Yaari, Vera Maljkovic, Marc Sunga, Han Hee Song, Hyun Joon Jung, Belle Tseng, and Andrew Trister
    In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining 2019
    Oral Presentation & Best Paper Runner-Up
  2. Pathomic Fusion: An Integrated Framework for Fusing Histopathology and Genomic Features for Cancer Diagnosis and Prognosis
    Richard J. Chen, Ming Y. Lu, Jingwen Wang, Drew F. K. Williamson, Scott J. Rodig, Neal I. Lindeman, and Faisal Mahmood
    IEEE Transactions on Medical Imaging 2020
    Top 5 Posters, NVIDIA GTC 2020
  3. Synthetic Data in Machine Learning for Medicine and Healthcare
    Richard J. Chen, Ming Y. Lu, Tiffany Y. Chen, Drew F. K. Williamson, and Faisal Mahmood
    Nature Biomedical Engineering 2021
  4. Pan-Cancer Integrative Histology-Genomic Analysis via Interpretable Multimodal Deep Learning
    Richard J Chen, Ming Y Lu, Drew FK Williamson, Tiffany Y Chen, Jana Lipkova, Muhammad Shaban, Maha Shady, Mane Williams, Bumjin Joo, Zahra Noor, and Faisal Mahmood
    arXiv preprint arXiv:2108.02278 2021