Andre Levchenko, Ph.D.

Andre Levchenko, a John C. Malone Professor of Biomedical Engineering at Yale University, and the founding Director of Yale Systems Biology Institute and Yale Cancer Systems Biology Center, combines experimental analysis with computational models to learn about the interactions of proteins and cells in healthy and disease states.

After growing up in Siberia, Levchenko received a Master of Science degree in biophysics from the Moscow Institute of Physics and Technology. After moving to the United States as a refugee, he went on to earn a Master of Science and a Doctor of Science degree in bioengineering from Columbia University, while also working at the Memorial Sloan-Kettering Cancer Center. He was then a postdoctoral scholar in the California Institute of Technology's Biology Division, initiating his work in systems biology.

Levchenko joined the faculty of the Department of Biomedical Engineering at Johns Hopkins University as an assistant professor in 2001, rising through the ranks to associate professor (with tenure) in 2007 and full professor in 2011. He then moved to Yale University in 2013 to lead a newly created Systems Biology Institute. He is internationally recognized as a pioneer and leader in the fields of systems biology of cell signaling, application of nanotechnology and microfabrication to biological experimentation. His contributions are particularly recognized in the areas of the analysis of cell migration and the cellular networks underlying multiple disease states, where he has combined computational moldering and novel experimentation methods to develop new insights at the molecular, cellular and organismal levels. He is the author of more than 150 published research articles and several book chapters, mostly in top publication venues. He is an elected fellow of the American Institute for Medical and Biological Engineering, Biomedical Engineering Society, American Physical Society and Connecticut Academy of Science and Engineering.

Thomas Yankeelov, Ph.D.

Thomas Yankeelov received an MA in Applied Mathematics and an MS in Physics from Indiana University, before completing the PhD in Biomedical Engineering at SUNY @ Stony Brook. He completed his post-doc under Dr. John Gore at the Vanderbilt University Institute of Imaging Science and climbed the ranks to Full Professor in 2010. He then joined the faculty at The University of Texas at Austin in 2016 where he is now the W.A. "Tex" Moncrief Chair of Computational Oncology and Professor of Biomedical Engineering, Diagnostic Medicine, and Oncology. Dr. Yankeelov is the founding Director of the Center for Computational Oncology, and also serves as co-Director for the Quantitative Oncology Research Program and Director of Cancer Imaging Research within the Livestrong Cancer Institutes at UT Austin. He is also an Adjunct Professor of Imaging Physics at MD Anderson Cancer Center.

The overall goal of Dr. Yankeelov's research is to develop tumor forecasting methods by integrating advanced imaging technologies with predictive, multi-scale models of tumor growth to optimize therapy. This is accomplished by dividing his efforts into approximately equal parts mathematical modeling, pre-clinical development, and implementation in clinical trials.

Steven M. Lipkin, Ph.D., M.D.

Dr Lipkin is Vice Chair for Research, Weill-Cornell Department of Medicine. He is also a a standing member of the FDA Molecular and Clinical Genetics Panel, which reviews and votes on approval of new genetic tests in the US. He is Director of the Weill Cornell Medical College Genetics Clinic, where he practiced as a Clinical Geneticist and supervise Genetic Counselors in the Departments of Medicine and Genetic Medicine, and Director of the Program in Mendelian Genetics. As a physician-scientist he has published in many well cited journals, including Cell, Cell Stem Cell, Nature Biotechnology, Nature Genetics, Science, Genes and Development, Proceedings of the National Academy of Sciences and Journal of Clinical Investigation, among others. He directs a research laboratory that uses immunology, massively parallel sequencing, computational biology, mouse models, cell culture and genomics to understand the contribution of genetics to, and mechanisms of, hereditary genetic syndromes. Previously he discovered and mechanistically characterized MLH3, a DNA mismatch repair gene colorectal polyposis and cancer predisposition gene, and also identified or co-identified 6 B cell malignancy predisposition genes. One of his current areas of focus is to help drive an international effort to develop and validate a cancer immunoprevention vaccine for Lynch syndrome.

Title of Speech: Immune Surveillance and Cancer Immunoprevention vaccines

Matteo Pellegrini, Ph.D.

Matteo Pellegrini is a biophysicist who has served on the UCLA Life Sciences Division faculty since he joined the Department of Molecular, Cell and Developmental Biology in 2005. Dr. Pellegrini earned his B.A. in Physics at Columbia University and his Ph.D. in Physics at Stanford. He was a postdoctoral fellow at UCLA, where he worked on computational biology. Following his postdoctoral studies, Dr. Pellegrini co-founded a start-up company and later worked for the pharmaceutical company, Merck, before returning to UCLA. His laboratory research centers on the development of novel computational approaches to analyze large-scale genomic data. His present focus is on data produced using the latest generation of high-throughput sequencers. The Pellegrini group is developing suites of tools for the analysis of high-throughput sequencing data such as methC-seq, RNA-seq, and scRNA-seq. These approaches have been used in many settings, including tissue decomposition and biomarker discovery for the study of aging.

Title of Speech: The Effects of Genes, Environment and Physiology on DNA Methylomes

Gary Royle, Ph.D.

Gary Royle is head of Cancer Engineering at University College London (UCL) and co-chairs UCL's cross-faculty cancer research network. Having studied mathematics and theoretical physics at Imperial College London he went on to apply that to medicine, with a focus on cancer. Initially developing technologies and methodologies for cancer diagnostics he now leads a large team focusing on cancer therapies for both UCL and UCL Hospital. Research includes radiation oncology, proton therapy, cancer technologies, cancer imaging and computational cancer. The latter includes computational biology, digital pathology and predictive modelling, using a combination of artificial intelligence and analytical methods. He has particular interest in metastatic disease and in understanding and predicting the response of cancers to treatment. He has published >150 papers and leads multi-institutional collaborations and networks in the field of cancer therapeutics. The team also run educational and training programmes for oncology and cancer research in UK and China.

Title of Speech: Predicting Response to Cancer Treatment