What: Virtual lecture series on topics across machine learning in medicine, featuring extensive Q & A and panel discussions
Why: To reduce academia’s carbon footprint and accommodate the schedules of the world’s top scientists
Where: Broadcast to in-person conference rooms at Cornell University in Ithaca NY and Weill Cornell Medicine in New York, NY
Also open to remote attendees everywhere via Zoom
Julia Schnabel, PhD- Professor and Chair, Computational Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, UK
When: POSTPONED
NYC location: Virtual only
Ithaca Location: Virtual only
Title: TBA
Abstract: TBA
Biography: Julia Schnabel joined King's College London in July 2015 as Chair in Computational Imaging at the School of Biomedical Engineering and Imaging Sciences, where she is Director of the EPSRC Centre for Doctoral Training in Medical Imaging, which is jointly run by King’s College London and Imperial College London. She is School Lead for Research and Impact, and Co-Director of the NIHR funded Medtech and In vitro diagnostic Co-operative (MIC) in Cardiovascular Diseases.
Omer T Inan, PhD- Associate Professor, Technical Interest Groups: Bioengineering (Group Chair), Electronic Design and Applications, Georgia Tech, Atlanta, GA
When: April 16th, 3:15 - 4:30 pm
NYC location: Belfer (413 E69 St), BB 204-C
Ithaca Location: Weill 226
Title: TBA
Abstract: TBA
Biography: Omer T. Inan received his B.S., M.S., and Ph.D. degrees in Electrical Engineering from Stanford University in 2004, 2005, and 2009, respectively. He worked at ALZA Corporation in 2006 in the Drug Device Research and Development Group. From 2007-2013, he was chief engineer at Countryman Associates, Inc., designing and developing several high-end professional audio products. From 2009-2013, he was a visiting scholar in the Department of Electrical Engineering at Stanford. In 2013, he joined the School of ECE at Georgia Tech as an assistant professor. Dr. Inan is generally interested in designing clinically relevant medical devices and systems, and translating them from the lab to patient care applications. One strong focus of his research is in developing new technologies for monitoring chronic diseases at home, such as heart failure.
Rajesh Ranganath, PhD- Assistant Professor, Computer Science, Courant Institute, New York University, New York, NY
When: April 23rd, 3:15 - 4:30 pm
NYC location: Weill Greenberg (1305 2nd Floor), WGC-C
Ithaca Location: Weill Hall, 226
Title: TBA
Abstract: TBA
Biography: I am an Assistant Professor at the Courant Institute at NYU in Computer Science and at the Center for Data Science (affiliate). I am also part of the CILVR group. My research interests center on easy-to-use probabilistic inference, understanding the role of randomness and information in model building, and machine learning for healthcare. Before joining NYU, I completed my PhD at Princeton working with Dave Blei and my undergraduate at Stanford both in computer science. I have also spent time as a research affiliate at MIT’s Institute for Medical Engineering and Science.
Souptik Barua, PhD- Postdoctoral Fellow, Scalable Health Lab, Rice University, Houtson, TX
When: May 8th, 9:45 - 11:00 am
NYC location: TBA
Ithaca Location: TBA
Title: TBA
Abstract: TBA
Biography: I am currently a postdoctoral research scientist under Dr. Ashutosh Sabharwal in the Scalable Health Lab at Rice University. I obtained my Ph.D. in Electrical Engineering at Rice University under Prof. Arvind Rao and Prof. Ashok Veeraraghavan. My research is focused on applying ideas from machine learning, signal processing, and statistics, to discover clinically relevant information in medical data.
Alexander Lavin- Founder, CTO, Latent Sciences, Cambridge, MA
When: May 14th, 3:15-4:30 pm
NYC location: Belfer (413 E69 St), BB 302-A
Ithaca Location: Phillips 233
Title: TBA
Abstract: TBA
Biography: Alexander Lavin is an AI researcher and SW engineer, specializing in Bayesian machine learning and probabilistic computation. He's the founder of Latent Sciences, a precision health startup developing solutions for neurodegenerative diseases, with a focus on Alzheimer's and Parkinson’s. Before Latent he was a Senior Research Engineer at both Vicarious and Numenta, building artificial general intelligence for robotics, and developing biologically-derived AI & ML algorithms, respectively. Lavin was previously a spacecraft engineer, building computational design and optimization algorithms for NASA and Blue Origin, and leading the development of a lunar rover. Lavin was a Forbes 30 Under 30 honoree in Science, is an AI advisor for NASA and several deep tech startups, and has published in top journals and conferences across AI/ML and neuroscience. In his free time, Alexander enjoys running, yoga, live music, and reading sci-fi and theoretical physics books.
Danielle Bassett, PhD - J Peter Skirkanich Professor, Department of Bioengineering, University of Pennsylvania, Philadelphia, PA
When: TBA
NYC location: TBA
Ithaca Location: TBA
Title: TBA
Abstract: TBA
Biography: Dani Bassett's group studies biological, physical, and social systems by using and developing tools from network science and complex systems theory. Our broad goal is to isolate problems at the intersection of basic science, engineering, and clinical medicine that can be tackled using systems-level approaches. Recent examples include predicting the extent of learning from human brain networks, resolving the evolution of the neuronal synapse via genetic interaction networks, determining bulk material properties from mesoscale force networks, and isolating individual drivers of collective social behavior during evacuations. In these contexts, we seek to develop new mathematical methods for the principled characterization of temporally dynamic, spatially embedded, and multiscale networked systems, with the goal of predicting system behavior and designing perturbations to affect a specific outcome. A current focal interest of the group lies in network neuroscience. We develop analytic tools to probe the hard-wired pathways and transient communication patterns inside of the brain in an effort to identify organizational principles, to develop novel diagnostics of disease, and to design personalized therapeutics for rehabilitation and treatment of brain injury, neurological disease, and psychiatric disorders.