Joseph Paul Cohen PhD
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
Joseph Paul Cohen is a Postdoctoral Fellow with Yoshua Bengio at Mila and the University of Montreal. Joseph is currently focusing on the limits of AI in medicine with respect to computer vision, genomics, and clinical data. He holds a PhD Degree in Computer Science and Machine Learning from the University of Massachusetts Boston. Joseph has worked on issues related to ML deployment in healthcare focusing on out-of-distribution detection and the limits of generalization. As well as general biology tools for mRNA/DNA representation learning from RNA-Seq and cell counting from microscopy data. Joseph received a U.S. National Science Foundation Graduate Fellowship as well as an IVADO Postdoctoral Fellowship. Joseph is the director of the Institute for Reproducible Research which is dedicated to improving the process of scientific research using technology.
Joseph is the director of the Machine Learning and Medicine Lab, a group dedicated to improving healthcare with machine learning. Joseph has created ShortScience.org; which lets researchers publish and read summaries of research papers like an online journal club, as well as Academic Torrents; a system designed to move large datasets and become the library of the future. He is also the creator of BlindTool; a mobile application providing a sense of vision to the blind by using an artificial neural network that speaks names of objects as they are identified. Joseph is the creator of Blucat; a cross-platform Bluetooth debugging tool.