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Learning Meaningful Representations of Life (LMRL.org)
Elizabeth Wood · Debora Marks · Ray Jones · Adji Bousso Dieng · Alan Aspuru-Guzik · Anshul Kundaje · Barbara Engelhardt · Chang Liu · Edward Boyden · Kresten Lindorff-Larsen · Mor Nitzan · Smita Krishnaswamy · Wouter Boomsma · Yixin Wang · David Van Valen · Orr Ashenberg

Fri Dec 11 06:00 AM -- 06:15 PM (PST) @
Event URL: http://www.lmrl.org »

This workshop is designed to bring together trainees and experts in machine learning with those in the very forefront of biological research today for this purpose. Our full-day workshop will advance the joint project of the CS and biology communities with the goal of "Learning Meaningful Representations of Life" (LMRL), emphasizing interpretable representation learning of structure and principle. As last year, the workshop will be oriented around four layers of biological abstraction: molecule, cell, synthetic biology, and phenotypes.

Mapping structural molecular detail to organismal phenotype and function; predicting emergent effects of human genetic variation; and designing novel interventions including prevention, diagnostics, therapeutics, and the development of new synthetic biotechnologies for causal investigations are just some of the challenges that hinge on appropriate formal structures to make them accessible to the broadest possible community of computer scientists, statisticians, and their tools.

Author Information

Elizabeth Wood (Broad Institute)

Elizabeth Wood co-founded and co-runs JURA Bio, Inc., an early-stage therapeutics start up focusing on developing and delivering cell-based therapies for the treatment of autoimmune and immune-related neurodegenerative disease. Before founding JURA, Wood was a post-doc in the lab of Adam Cohen at Harvard, after completing her PhD studies with Angela Belcher and Markus Buehler at MIT, and Claus Helix-Neilsen at The Technical University of Denmark. She has also worked at the University of Copenhagen’s Biocenter with Kresten Lindorff-Larsen, integrating computational methods with experimental studies to understand how the ability of proteins to change their shape help modulate their function. Elizabeth Wood is a visiting scientist at the Broad Institute, where she serves on the steering committee of the Machine Inference Algorithm’s Initiative.

Debora Marks
Ray Jones (Broad Institute)
Adji Bousso Dieng (Columbia University)
Alan Aspuru-Guzik (University of Toronto)
Anshul Kundaje (Stanford University)
Barbara Engelhardt (Princeton University)

Barbara E. Engelhardt is an associate professor in the Princeton Computer Science Department, on leave in 2019-2020 working as a principal scientist at Genomics Plc. Previously, she was an assistant professor at Duke University in Biostatistics and Bioinformatics and Statistical Sciences. She graduated from Stanford University and received her Ph.D. from the University of California, Berkeley, advised by Professor Michael Jordan. She did postdoctoral research at the University of Chicago, working with Professor Matthew Stephens. Interspersed among her academic experiences, she spent two years working at the Jet Propulsion Laboratory, a summer at Google Research, and a year at 23andMe, a DNA ancestry service. Professor Engelhardt received an NSF Graduate Research Fellowship, the Google Anita Borg Memorial Scholarship, and the Walter M. Fitch Prize from the Society for Molecular Biology and Evolution. As a faculty member, she received the NIH NHGRI K99/R00 Pathway to Independence Award, a Sloan Faculty Fellowship, and an NSF CAREER Award. Professor Engelhardt’s research interests involve developing statistical models and methods for the analysis of high-dimensional biomedical data, with a goal of understanding the underlying biological mechanisms and dynamics of complex phenotypes and human disease.

Chang Liu (UC Irvine)

Professor Liu’s research is in the fields of synthetic biology, chemical biology, and directed evolution. He is particularly interested in engineering specialized genetic systems for rapid mutation and evolution of genes in vivo. These systems can then be widely applied for the engineering, discovery, and understanding of biological function.

Edward Boyden (Massachusetts Institute of Technology)
Kresten Lindorff-Larsen (University of Copenhagen)

Kresten Lindorff-Larsen trained as a biochemist at the University of Copenhagen and Carlsberg Laboratory, and completed his Ph.D. at the University of Cambridge in 2004. He then moved on to become an assistant professor in Copenhagen before joining D. E. Shaw Research in New York in 2007. He returned to Copenhagen in 2011, where he now serves as a Professor of Computational Protein Biophysics. He received the Danish Independent Research Councils’ Young Researchers’ Award in 2006, was a co-recipient of the 2009 Gordon Bell Prize, and has received several prestigious grants including a Hallas-Møller stipend (2011), a Sapere Aude grant (2012), and most recently a Novo Nordisk Foundation challenge programme grant (2019). His current research interests include developing and applying computational methods for integrative structural biology, and the integration of biophysics and genomics research.

Mor Nitzan (Broad Institute)

Mor Nitzan is a Senior Lecturer (Assistant Professor) in the School of Computer Science and Engineering, and affiliated to the Institute of Physics and the Faculty of Medicine, at the Hebrew University of Jerusalem. Her research is at the interface of Computer Science, Physics, and Biology, focusing on the representation, inference and design of multicellular systems. Her group develops computational frameworks to better understand how cells encode multiple layers of spatiotemporal information, and how to efficiently decode that information from single-cell data. They do so by employing concepts derived from diverse fields, including machine learning, information theory and dynamical systems, while working in collaboration with experimentalists and capitalizing on vast publicly available data. Mor aims to uncover organization principles underlying information processing, division of labor, and self-organization of multicellular systems such as tissues, and how cell-to-cell interactions can be manipulated to optimize tissue structure and function. Prior to joining the Hebrew University as a faculty member, Mor was a John Harvard Distinguished Science Fellow and James S. McDonnell Fellow at Harvard University. She completed a BSc in Physics, and obtained a PhD in Physics and Computational Biology at the Hebrew University, working with Profs. Hanah Margalit and Ofer Biham, on the interplay between structure and dynamics in gene regulatory networks. She was then hosted as a postdoctoral fellow by Prof. Nir Friedman (Hebrew University) and Prof. Aviv Regev (Broad Institute). Mor is a recipient of the Azrieli Foundation Early Career Faculty Fellowship, Google Research Scholar Award, Researcher Recruitment Award by the Israeli Ministry of Science and Technology, John Harvard Distinguished Science Fellowship, James S. McDonnell Fellowship, and the Schmidt Postdoctoral Award for Women in Mathematical and Computing Sciences.

Smita Krishnaswamy (Yale University)
Wouter Boomsma (University of Copenhagen)
Yixin Wang (Columbia University)
David Van Valen (Caltech)
Orr Ashenberg (Broad Institute)

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