Richard J. Chen

I am a 3rd year Ph.D. Candidate (and NSF-GRFP Fellow) 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. In industry, I have also worked at Apple Inc. in the Health Special Project and Applied Machine Learning Groups (with Belle Tseng and Andrew Trister), and at Microsoft Research in the BioML Group (with Rahul Gopalkrishnan).

Research Highlights

Prospective Summer Interns, Undergraduate / Master Students, and other Visiting Students: Several positions in the Mahmood Lab are open for projects around weakly-supervised, self-supervised, and multimodal learning for CPATH. Email richardchen@g.harvard.edu with your resume / CV, and a brief research statement on what you’re interested in!

Recent News

Mar, 2022 In press, our work on CRANE was published in Nature Medicine. Also, code + pretrained model weights are made available for our recent Self-Supervised ViT work in NeurIPSW LMRL 2021. Lastly, Hierarchical Image Pyramid Transformer was accepted in CVPR 2022! Stay tuned :^)
Feb, 2022 In press, federated learning for CPATH (HistoFL) was published in Medical Image Analysis. Lastly, my visiting student, Yicong Li, was accepted into the Computer Science Ph.D. program at Harvard University (SEAS). Congratulations Yicong!
Nov, 2021 In press, our editorial on human-augmented labeling systems (HALS) for CPATH was published in npj Digital Medicine. Excited to also announce that my preprint on algorithm fairness for medicine and healthcare is on arXiv! Please reach out if you have any feedback on this work :)
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 and ICCV respectively.
Jun, 2021 Joined Microsoft Research as an PhD Research Intern, working with Rahul Gopalkrishnan in the BioML Group. In press, our commentary on synthetic data for machine learning and healthcare was also published in Nature Biomedical Engineering. Lastly, I passed my Qualifying Exam, and am now 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. 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
    Best Paper, Case Western Artificial Intelligence in Oncology Symposium, 2020.
  3. Multimodal Co-Attention Transformer for Survival Prediction in Gigapixel Whole Slide Images
    Richard J. Chen, Ming Y. Lu, Wei H. Weng, Tiffany Y Chen, Drew FK Williamson, Trevor Manz, Maha Shady, and Faisal Mahmood
    In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) 2021
  4. Algorithm Fairness in AI for Medicine and Healthcare
    Richard J. Chen, Tiffany Y. Chen, Jana Lipkova, Judy J. Wang, Drew FK. Williamson, Ming Y. Lu, Sharifa Sahai, and Faisal Mahmood
    arXiv preprint arXiv:2110.00603 2021
  5. 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
  6. Federated Learning for Computational Pathology on Gigapixel Whole Slide Images
    Ming Y. Lu*, Richard J. Chen*, Dehan Kong, Jana Lipkova, Rajendra Singh, Drew FK. Williamson, Tiffany Y. Chen, and Faisal Mahmood
    Medical Image Analysis 2022
  7. 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