Yale-BI Joint Selection Committee (JSC) and Advisors

Anthony J. Koleske is an expert in understanding the biochemical mechanisms that regulate neuronal dendrite and synapse development. After receiving a B.S. in Biochemistry and Molecular Biology at the University of Wisconsin-Madison, Dr. Koleske performed his Ph.D. studies with Dr. Richard Young at the Whitehead Institute/Massachusetts Institute of Technology. For his Ph.D. thesis, Dr. Koleske discovered the RNA polymerase II holoenzyme, an important advancement in understanding how gene transcription is turned on. Dr. Koleske went on to do a postdoctoral fellowship with Dr. David Baltimore at M.I.T., where he began his work studying cellular functions of Abl family kinases, which his laboratory has shown are essential regulators of the cytoskeleton in diverse cell types. Dr. Koleske joined the Department of Molecular Biophysics and Biochemistry at Yale University in 1998, where he currently is Professor and holds a joint appointment in the Department of Neuroscience. Dr. Koleske is the recipient of numerous awards including a Jane Coffin Childs Postdoctoral Fellowship, Special Fellowship and Scholar Awards from the Leukemia and Lymphoma Society, Young Investigator and Established Investigator Awards from NARSAD, an Established Investigator Award from the American Heart Association. He has served widely on review panels, including terms as Chair of the Basic Science Study Section for the American Heart Association and the Neurodifferentiation, Plasticity, Repair, and Rhythmicity Study Section of the NIH. He served as Director of the combined PhD programs in the Biological and Biomedical Sciences at Yale (2014-2019).  He also served Director of the China Scholarship Council-Yale World Scholars Program (2014-2019) and was a co-Director of the Yale BioMed SURF Amgen Scholars Program (w/Faye Rogers and Barbara Kazmierczak)(2015-2020).

Dean Jeff Brock was recruited to Yale in July 2018 to assume the role of dean of science in the Faculty of Arts and Science (FAS). In this capacity, he oversees the day-to-day activities and mid- and long-term planning of the departments of: applied physics, astronomy, chemistry, geology and geophysics, mathematics, and physics; as well as ecology and evolutionary biology, molecular biophysics and biochemistry, and molecular, cellular and developmental biology.In August 2019, Jeff was appointed to the additional role of dean of the School of Engineering & Applied Science (SEAS). From this unique position, serving simultaneously as the dean of engineering and the dean of science, Jeff leads strategic thinking bridging these multidisciplinary areas of research and teaching.Prior to Yale, Jeff held several leadership roles at Brown University. He was a founding deputy director of the Institute for Computational and Experimental Research in Mathematics and established the campus-wide Data Science Initiative. Additionally, he was chair of the department of mathematics.Jeff earned his undergraduate degree from Yale in 1992 and his Ph.D. in mathematics from UC Berkeley in 1997. He then held postdoctoral positions at both Stanford University and the University of Chicago. An elected fellow of the American Mathematical Society, Jeff’s research focuses on spaces with negatively curved, or “hyperbolic” geometry. His foundational work led to the geometric classification of objects called hyperbolic 3-manifolds. Recently, Dean Brock’s research has focused on connections between hyperbolic geometry and theoretical physics, leading to the idea of a geometric evolution of 3-manifolds reminiscent of heat flow, and on the notion of a topology and geometry, or shape of complex and high dimensional data sets.Jeff resides locally with his wife, Sarah Cussler ’92, and their three children. An accomplished musician, he was the founding jazz bassist for the Vijay Iyer Trio, and a member of the Whiffenpoofs while in college at Yale.

Dr. Hongyu Zhao is the Ira V. Hiscock Professor of Biostatistics and Professor of Statistics and Data Science and Genetics. He received his B.S. in Probability and Statistics from Peking University in 1990 and Ph.D. in Statistics from the University of California at Berkeley in 1995. His research interests are the developments and applications of novel statistical methods to address scientific questions in genetics, molecular biology, drug developments, and precision medicine. Some of his recent projects include large scale genome wide studies to identify genetic variants underlying complex diseases, genetic risk prediction, single cell analysis, biological network modeling and analysis, disease biomarker identification, genome annotation, cancer genomics, microbiome analysis, image analysis, and wearable device data analysis. He has published over 700 articles in statistics, human genetics, bioinformatics, genomics, and proteomics, and edited three books on human genetics analysis and statistical genomics. He has trained over 110 doctoral and post-doctoral students, many of whom are holding tenured or tenure-track positions at major universities in the states and overseas. Dr. Zhao has served as an editor and/or associate editor of leading statistical and genetics journals, including as a Co-Editor of the Journal of the American Statistical Association Theory and Methods and a co-Editor of Statistics in Biosciences. He was the recipient of the Mortimer Spiegelman Award for a top statistician in health statistics under the age of 40 awarded by the American Public Health Association and the Pao-Lu Hsu Award from the International Chinese Statistical Association. His research has also been recognized by the Evelyn Fix Memorial Medal and Citation by UC Berkeley, a Basil O'Connor Starter Scholar Award by the March of Dimes Foundation, election to the fellowship of the American Association for the Advancement of Science, the American Statistical Association, the Institute of Mathematical Statistics, and Connecticut Academy of Science and Engineering.

Smita Krishnaswamy is an Associate professor in Genetics and Computer Science. She is affiliated with the applied math program, computational biology program,  Yale Center for Biomedical Data Science and Yale Cancer Center. Her lab works on the development of machine learning techniques to analyze high dimensional high throughput biomedical data. Her focus is on unsupervised machine learning methods, specifically manifold learning and deep learning techniques for detecting structure and patterns in data. She has developed algorithms for non-linear dimensionality reduction and visualization, learning data geometry,  denoising, imputation, inference of multi-granular structure, and inference of feature networks from big data. Her group has applied these techniques to many data types such as single cell RNA-sequencing, mass cytometry, electronic health record, and connectomic data from a variety of systems. Specific application areas include immunology,  immunotherapy, cancer, neuroscience, developmental biology and health outcomes. Smita has a Ph.D. in Computer Science and Engineering from the University of Michigan.

C. Brandon Ogbunu is an Assistant Professor in the Department of Ecology and Evolutionary Biology at Yale University. He is a computational biologist whose research investigates complex problems in epidemiology, evolutionary & population genetics, and evolution. His work utilizes a range of methods, from experimental evolution, to biochemistry, applied mathematics, and evolutionary computation.

Dr. Brandt completed a general Preventive Medicine residency at Madigan Army Medical Center in 1989 and a post-doctoral fellowship sponsored by the National Library of Medicine at Yale School of Medicine in 1997. She is board certified in Preventive Medicine and Clinical Informatics. Her research is interdisciplinary and focuses on issues related to the design, development and use of informatics tools in the domain of clinical research, as well as health services research.

Dr. Steven Kleinstein is a computational immunologist with a combination of big data analysis and immunology domain expertise. His research interests include both developing new computational methods and applying these methods to study human immune responses. Dr. Kleinstein received a B.A.S. in Computer Science from the University of Pennsylvania and a Ph.D. in Computer Science from Princeton University. He is currently Professor of Pathology (with a secondary appointment in Immunobiology) at the Yale School of Medicine, and a member of the Interdepartmental Program in Computational Biology and Bioinformatics (CBB), and the Human and Translational Immunology Program. Specific areas of research focus include:High-throughput single-cell B cell receptor (BCR) repertoire profiling (AIRR-seq, Rep-seq, scRNA-seq+VDJ)Multi-omic immune signatures of human infection and vaccination responses

Dr. Jensen holds a PhD in Health Science from University of Copenhagen and a Master of Science in Biochemistry. After multiple years in the US as a graduate student and later holding a few Post Doc positions, Jensen joined the pharmaceutical industry as a leader of beta cell biology and pancreatic regeneration. Jensen then became the lead of large strategic initiatives as well as lead of experimental testing of an entire therapeutic portfolio. During this time, Jensen developed more and more interest in data science and computational biology, connecting data science with drug discovery. Jensen then became Deputy site head and strategic partner of a new research institute in Oxford, this time heading Computational Biology and Technologies. The focus was on data driven drug discovery as well as external partnerships with Academia and Biotech’s. This led to a great opportunity to Join Boehringer-Ingelheim as Global Head of Computational Biologists Digital Sciences in October 2019 with initiatives and research groups across the major research sites Vienna (Austria), Ridgefield (United States) and Biberach (Germany). The ambition is here to shape the future drug portfolio by acting on novel biological insights generated from the application of state-of-the-art in silico methods to human disease data. LinkedIn Google Scholar

Dr. James Cai is the VP, Head of Computational Biology and Digital Sciences at BI’s Ridgefield site in the US, and Global Head of Computational Biology in Immunology, Respiratory (I&R), Cancer Immunotherapy and Immunoregulation (CIIM), responsible for applying state-of-the-art computational approach and data-driven insights to our current and next-generation drug pipeline to eventually benefit patients with unmet medical needs. James has been an innovative leader in drug discovery and development for the past 20 years, passionate about creating value from complex data, advanced analytics, and collaboration. Before joining BI, Dr. James Cai was the head of Data Science at Roche Innovation Center New York since 2014, focusing on value creation using human disease data in Early Clinical Development and Translational Research. Prior to that, he spent more than a decade at the Roche Nutley site in NJ, then the US headquarter of Roche Pharma, leading various Bioinformatics and Data Science teams. As a champion of innovative technologies, he helped Roche in the development of many modern analytic capabilities in drug discovery and development, including the first large scale whole exome sequence analysis pipeline, the introduction of NLP and text analytics, and later Real World Data (RWD), scRNA-seqanalysis, and AI/Deep Learning. James holds a Ph.D. in Molecular & Cell Biology from Cornell University and a Master’s degree in Biomedical Informatics from Columbia University. LinkedInGoogle Scholar

Dr. Christian Haslinger, based in Vienna, Austria, is currently the Department Head of Computational Biology and Digital Sciences at Boehringer Ingelheim RCV Holding GmbH. He brings experience from previous roles at Boehringer Ingelheim and Boehringer Ingelheim Oncology. Christian Haslinger graduated from the University of Vienna and has a robust skill set that includes Strategy, Transcriptomics, Drug Discovery, R, Cell Biology, and more. LinkedInGoogle Scholar

Dr. Maria Faelth Savitski is the head of Computational Biology at Boehringer’s site in Biberach, Germany. She is responsible for the computational biology work for three therapeutic areas, Cardio-Metabolic, CNS and Research Beyond Borders, applying state-of-the art computational approaches to discover and validate novel drug targets, linking targets to disease and biomarker discovery. Dr. Maria Faelth Savitski has more than 10 years of experience applying innovative computational methods for drug discovery and before joining Boehringer she was leading computational biology teams at GSK, pioneering novel omics technologies and multi-omics integration to understand mode-of-action of drug target and link it to disease mechanisms. Maria holds a Master of Science in Information Technology and PhD in Pharmaceutical Sciences from Uppsala University and before joining the pharmaceutical industry she was a Post-doc at the German Cancer Research Center (dkfz) in Heidelberg. LinkedIn: Maria Fälth Savitski | LinkedIn Google Scholar: https://scholar.google.se/citations?user=Q93Z1uIAAAAJ&hl