Joseph Paul Cohen PhD

Postdoctoral Research Fellow, AIMI, Stanford University
Postdoctoral Fellow, Mila, Quebec AI Institute
Director, The Institute for Reproducible Research

I am working on representation learning, generalization, and out of distribution detection for chest X-ray. My goal is to identify and overcome issues limiting the deployment of AI tools in healthcare and to provide the highest quality healthcare to the most people

My interests are in medical applications of deep learning:

  • Medical Imaging: radiology, histology, microscopy, cell counting
  • Genomics: gene representations, scRNA-Seq, cancer subtype/phenotype prediction
  • Clinical: survival/event prediction, automated triage

As well as core deep learning:

  • Generalization: unsupervised representation learning, meta-learning, concept representations
  • Uncertainty: out of distribution detection, model calibration
  • Attribution: prediction explanation, model interpretation

Bio: Joseph Paul Cohen is a researcher and pragmatic engineer. He currently focuses on the challenges in deploying AI tools in medicine specifically computer vision and genomics. He maintains many open source projects including Chester the AI radiology assistant, TorchXRayVision, and BlindTool – a mobile vision aid app. He is the director of the Institute for Reproducible Research, a US non-profit which operates and Academic Torrents.

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Selected Projects