Michael M. Shen, PhD, conducts basic and translational research in the areas of mammalian embryogenesis and stem cell differentiation, particularly in prostate organogenesis and molecular mechanisms of prostate carcinogenesis. He is Professor of Medicine and Genetics & Development, and Head of the Section of Tumor Cell Biology in the Division of Hematology/Oncology in the Department of Medicine at Columbia University Medical Center. He is also on the faculty of the Department of Systems Biology. Dr. Shen pursued doctoral studies at the MRC Laboratory of Molecular Biology in Cambridge, England, receiving his PhD from Cambridge University in 1988. Previously, he was a Professor and Director of the Transgenic/Knock-out Mouse Core at the University of Medicine and Dentistry of New Jersey Robert Wood Johnson Medical School, where he was also Associate Director of the Child Health Institute.
Peter Sims, PhD, is an Assistant Professor of Systems Biology in the Departments of Systems Biology and Biochemistry & Molecular Biophysics at Columbia University. In addition, he is the Associate Director for Novel Technologies at the JP Sulzberger Columbia Genome Center. Dr. Sims completed his graduate and postdoctoral studies in the laboratory of Prof. Sunney Xie at Harvard University, where he developed tools for making single molecule measurements in individual cells and a novel, microfluidics-based platform for next-generation sequencing. His laboratory at Columbia specializes in single cell analysis and uses cutting-edge microscopy, sequencing techniques, and microfluidics to conduct large-scale single cell studies in malignant tumors and developmental systems.
Anna Lasorella, MD, is Associate Professor of Pathology and Cell Biology and Pediatrics in the Institute for Cancer Genetics at Columbia University. Her scientific interest has been basic and translational research in brain tumor biology using an interdisciplinary approach that includes cellular biology, mouse genetics, and biochemical methods to integrate basic research with an understanding of malignant transformation. Dr. Lasorella has generated cellular and mouse models of malignant brain tumors that are faithful in vitro and in vivo systems to address the significance of computational predictions of driver genetic alterations in GBM and identify vulnerabilities of addicting oncogenes to targeted therapies.
Chris Wiggins, PhD, is an Associate Professor in the Department of Applied Physics and Applied Mathematics at Columbia. He is also affiliated with Columbia’s Institute for Data Sciences and Engineering, the Department of Systems Biology, and the Department of Statistics. He is an applied mathematician with a PhD in theoretical physics working on computational biology. His focus areas of research include applications of machine learning, statistical inference, and information theory for the inference, analysis, and organization of biological networks. In 2011 he was chosen by Crains magazine as one of 25 “People to watch in Silicon Alley,” and since 2014 has held an appointment as Chief Data Scientist at the New York Times.
Gunnar Carlsson, PhD, is the Anne and Bill Swindells Professor in the Department of Mathematics at Stanford University. Dr. Carlsson has worked on diverse aspects of algebraic topology and has been a pioneer in the development of topological data analysis, including persistent homology methods. Dr. Carlsson heads the Computational Topology workgroup in the Mathematics department at Stanford University. His work focuses on developing flexible topological methods for the analysis of data that are difficult to treat using classical algebraic methods. In particular, Dr. Carlsson supervised the development of the JavaPlex software package, which implements persistent homology and related techniques from computational and applied topology and has been used in a number of investigations in diverse data types. He has also led the development of the Mapper methodology, a method for providing simplicial complex maps of complex data sets, and which has demonstrated value applied to different kinds of data.
Andrew Blumberg, PhD, is an Associate Professor in the Department of Mathematics at the University of Texas, Austin. He completed his PhD at the University of Chicago under the supervision of Peter May and Michael Mandell, and was later a National Science Foundation postdoctoral fellow at Stanford. He also spent a year as a member at the Institute for Advanced Study. His research focuses primarily on homotopy theory and algebraic topology, with a particular emphasis on algebraic K-theory. He is also interested in equivariant stable homotopy theory. He is working with other members of Mathematics Core on the development of topological domain analysis techniques for applications to genomic data.
Bud Mishra, PhD, is a Professor of Computer Science and Mathematics at NYU’s Courant Institute of Mathematical Sciences, Professor of Human Genetics at Mt. Sinai School of Medicine, Professor of Cell Biology at NYU School of Medicine, and a visiting scholar of the Simons Center for Quantitative Biology at Cold Spring Harbor Laboratory. He founded the NYU/ Courant Bioinformatics Group, a multi-disciplinary group working on research at the interface of computer science, applied mathematics, biology, biomedicine, and bio/nano-technologies. He is an inventor of Optical Mapping and Sequencing, Array Mapping, Copy-Number Variation Mapping, Robot Grasping and Fixturing devices and algorithms, and nanotechnology for DNA profiling. He is a fellow of ACM, AAAS and IEEE.
Hossein Khiabanian, PhD, trained in astrophysics at Brown University. He is currently an Assistant Professor at the Rutgers Cancer Institute of New Jersey, and serves as Scientific Coordinator of the Center. Prior to joining Rutgers University, he worked closely with Dr. Rabadan in conducting research and training students and postdocs at Columbia where he was an Associate Research Scientist and a member of the Department of Biomedical Informatics faculty. Dr. Khiabanian has lectured in multiple multidisciplinary courses and is widely published in high-impact scientific journals. His work has been particularly focused on understanding clonal expansions, from intra-host pathogen evolution to unregulated cell growth in cancer, especially in the context of disease transformation and relapse.
Pablo G. Camara, PhD, is a postdoctoral research scientist in the Department of Biomedical Informatics, in the laboratory of Dr. Rabadan, and serves as Scientific Coordinator of the Center. The work of Dr. Camara currently focuses on developing topological methods for the analysis of large scale genomic data, in the contexts of single-cell genomics, cancer, and evolution. He is using these methods to tackle two broad biological questions: understanding the molecular mechanisms that operate during germ cell development and cell fate determination; and identifying new driver genes in cancer. Dr. Camara received his PhD in Theoretical Physics in 2006 and performed research in High Energy Physics until 2014, with postdoctoral appointments at Ecole Polytechnique, the European Organization for Nuclear Research (CERN), and University of Barcelona.