External Advisory Council

The External Advisory Committee is composed of senior scientists with expertise in various scientific domains that are of relevance to the center. The EAC meets annually to discuss and assess project scientific quality, implementation and impact, and to provide recommendations to the Steering Committee on major decisions, including budgetary allocations. The EAC also provides guidance to the Center investigators on issues such as best practices and policy changes.

Mathieu Blanchette, Ph.D.

Professor, McGill University

Mathieu Blanchette is the Head of the External Advisory Council of the KnowEnG Center. He is a faculty at the McGill School of Computer Science and heads the Computational Genomics lab. His lab focuses on the development of algorithmic and machine learning approaches to biological sequence analysis. He is particularly interested in the analysis of transcriptional regulation, in particular the prediction of transcription factor binding sites and regulatory modules, as well as in splicing regulation.

Gill Bejerano, Ph.D.

Associate Professor of Developmental Biology & Computer Science
Associate Professor of Pediatrics, Stanford University

Gill Bejerano studies genome function in human and related species. He is deeply interested in the following broad questions: Mapping genome sequence (variation) to phenotype (differences) and extracting specific genetic insights from deep sequencing measurements. His research group takes a particular interest in gene cis regulation.

Murthy Devarakonda, Ph.D.

Principal Investigator, IBM Watson

Murthy Devarakonda is a Research Staff Member & Manager at IBM Research and in the new Watson Group. His long term work is best characterized as transforming results from measurement, monitoring, and analysis into foundational observations, and applying them to systems design and management. Before Watson, he applied this methodology in the areas of IT Discovery and Dependency Analysis, Cloud Computing, Distributed Systems, File Systems, and Storage. Now, he is fascinated by the challenges of unstructured data analytics and the potential to apply Watson to health care.

Dave Valle, M.D.

Henry J. Knott Professor and Director of the Institute of Genetic Medicine
Professor, Johns Hopkins University School of Medicine

David Valle is the director of the Institute of Genetic Medicine and professor of pediatrics and ophthalmology at the Johns Hopkins School of Medicine. He also serves as a geneticist for the Johns Hopkins Children’s Center and is board-certified by the American Board of Medical Genetics in clinical molecular genetics, clinical biochemical genetics, clinical genetics and pediatrics.

Ting Wang, Ph.D.

Associate Professor of Genetics; Associate Professor of Computer Science and Engineering, Washington University in St. Louis

Ting Wang is the Associate Professor of Genetics and of Computer Science. He is interested in understanding the evolution and adaption of gene regulatory networks. Research in his lab focuses on understanding genetic and epigenetic factors that determine cell fate, including cell fate in normal development and differentiation, abnormal cell fate in cancer, and how specific cell types evolve. Specifically, the roles of transposable elements and the roles of DNA methylation in these processes.

Wei Wang, Ph.D.

Professor, Department of Computer Science; University of California, Los Angeles

Wei Wang is a professor in the Department of Computer Science at University of California, Los Angeles and the director of the Scalable Analytics Institute (ScAi). She received an MS degree from the State University of New York at Binghamton in 1995 and a PhD degree in Computer Science from the University of California, Los Angeles in 1999. She was a professor in Computer Science and a member of the Carolina Center for Genomic Sciences and Lineberger Comprehensive Cancer Center at the University of North Carolina at Chapel Hill from 2002 to 2012, and was a research staff member at the IBM T. J. Watson Research Center between 1999 and 2002. Dr. Wang’s research interests include big data analytics, data mining, bioinformatics and computational biology, and databases. She has filed seven patents, and has published one monograph and more than one hundred seventy research papers in international journals and major peer-reviewed conference proceedings