The Herbert and Florence Irving Institute for Cancer Dynamics will continue its seminar series on the topic of mathematical sciences underpinning cancer research during the 2022-2023 academic year. The monthly seminars take place on the second Wednesday of the month, 2:00-3:00 PM EST. The presentations are open to the Columbia community (in person and online) and to researchers outside Columbia (via Zoom).
On Wednesday, April 10th (2:00 PM ET), IICD welcomes Cameron Po-Hsuan Chen, Head of AI and Data Science at Need. Seminar hosted by Bianca Dumitrascu. The seminar will take place in person in Fairchild 700 (Morningside Heights campus). If you wish to attend the seminar remotely, please register using the following link: https://columbiauniversity.zoom.us/meeting/register/tJcqf--qrD4qH9w16E0NBzf9pF9ZkgD0gXy5
Title: How Can Humans Learn From AI To Better Treat Cancer?
Abstract: In traditional ML, models learn from hand-engineered features informed by existing domain knowledge. More recently, in the deep learning era, combining large-scale model architectures, compute, and datasets has enabled learning directly from raw data, often at the expense of human interpretability. In this talk, I'll discuss a series of studies that begin with the utilization of human annotations to achieve performance that exceeds that of humans, and then delve into employing deep learning for directly predicting patient outcomes. Here, we will look into interpretability methods as a means to discover new insights that can be comprehended and leveraged by humans. This process is a natural next step in the evolution of applying ML to problems in medicine and science, moving from the use of ML to distill existing human knowledge to people using ML as a tool for knowledge discovery. Finally, I will discuss our efforts at Need in compiling a comprehensive, multimodal longitudinal dataset on a large scale, and our endeavors in creating machine learning systems aimed at enhancing standardization in cancer care.
Bio: Po-Hsuan Cameron Chen, PhD, is the Head of AI and Data Science at Need. Need is an early-stage startup building the world's first cancer protection system, enabling anyone, anywhere to achieve the best cancer outcome. Before Need, Cameron was a staff software engineer and a tech lead manager of Google Research/Google Health/Google Brain. His research has been published in leading scientific, clinical, and machine learning venues, including Nature, JAMA, and NeurIPS, and covered by media outlets such as the New York Times, Forbes, and Engadget. He received his PhD in Electrical Engineering and Neuroscience from Princeton University and his BS in Electrical Engineering from National Taiwan University. Cameron was also a recipient of the Google PhD Fellowship.
If you would like to meet one-on-one (possibility via zoom) or attend the lunch or dinner with the speaker, please contact the event organizer.
