|Ziv Bar-Joseph, PhD
Carnegie Mellon University
|Elaine Mardis, PhD
Nationwide Children's Hospital
|Rada Mihalcea, PhD
University of Michigan
|Sara Mostafavi, PhD
|Harinder Singh, PhD
University of Pittsburgh
Dr. Bar-Joseph is the FORE Systems Professor of Computer Science at the Machine Learning Department and the Computational Biology Department which are part of the School of Computer Science at Carnegie Mellon University. He is the recipient of the 2012 Overton Prize in computational biology.
His primary research areas are computational Biology, Bioinformatics and Machine learning. He is heading the Systems Biology Group at the School of Computer Science at CMU. His group develops computational methods for understanding the interactions, dynamics and conservation of complex biological systems. His work addresses issues ranging from the experimental design level to the systems biology level. He is also interested in how shared principles between computation and biology can be used to improve our understanding of both fields. His group is looking at algorithms used by nature to see if we can obtain new ideas on how to design better algorithms for distributed computing systems while at the same time infer new insights regarding information processing in biology.
Co-Executive Director of the Institute for Genomic Medicine at Nationwide Children’s Hospital and the Nationwide Foundation Endowed Chair of Genomic Medicine. She also is Professor of Pediatrics at The Ohio State University College of Medicine. Dr. Mardis joined Nationwide Children’s Hospital in 2016.
Educated at the University of Oklahoma with a B.S. in Zoology and a Ph.D. in Chemistry and Biochemistry, Dr. Mardis did postgraduate work in industry at BioRad Laboratories. She was a member of the faculty of Washington University School of Medicine from 1993-2016.
Dr. Mardis has authored over 350 articles in prestigious peer-reviewed journals and has written book chapters for several medical textbooks. She serves as an associate editor for three peer-reviewed journals (Disease Models and Mechanisms, Molecular Cancer Research, and Annals of Oncology) and is Editor-in-Chief of Molecular Case Studies, published by Cold Spring Harbor Press. Dr. Mardis has given lectures at scientific meetings worldwide and was awarded the Morton K Schwartz award from the American Association for Clinical Chemistry in 2016. She has been listed since 2013 as one of the most highly cited researchers in the world by Thompson Reuters. Dr. Mardis has been a member of the American Association for Cancer Research (AACR) since 2007, was the program committee chair for the 2018 AACR Annual Meeting and is the current AACR President. She was elected a Fellow of the AACR Academy, and also was elected to membership in the National Academy of Medicine in 2019.
Rada Mihalcea is a Professor of Computer Science and Engineering at the University of Michigan and the Director of the Michigan Artificial Intelligence Lab. Her research interests are in computational linguistics, with a focus on lexical semantics, multilingual natural language processing, and computational social sciences. She serves or has served on the editorial boards of the Journals of Computational Linguistics, Language Resources and Evaluations, Natural Language Engineering, Journal of Artificial Intelligence Research, IEEE Transactions on Affective Computing, and Transactions of the Association for Computational Linguistics. She was a program co-chair for EMNLP 2009 and ACL 2011, and a general chair for NAACL 2015 and *SEM 2019. She currently serves as ACL Vice-President. She is the recipient of a Presidential Early Career Award for Scientists and Engineers awarded by President Obama (2009) and an ACM Fellow (2019). In 2013, she was made an honorary citizen of her hometown of Cluj-Napoca, Romania.
Dr. Mostafavi's main interest lies in developing and using machine learning and statistical techniques to study and understand the genetic basis of complex diseases, with a particular interest in psychiatric disorders and cancer. She is especially interested in developing models for combining association evidence across multiple genome-wide data sources, such as gene expression and genotype data, and modeling prior biological pathways and networks for disentangling spurious from meaningful correlations.
Dr. Singh's interests are focused on the analysis of transcription factors and gene regulatory networks (GRNs) that orchestrate the development and functioning of innate as well as adaptive cells of the immune system. As an HHMI Investigator at the University of Chicago, his lab discovered that the Ets family member PU.1 was required for the development of multiple innate and adaptive immune cell lineages. They have systematically illuminated the molecular functions of PU.1 in the development of B cells and macrophages. In a collaboration, they cloned IRF4, a PU.1 partner. IRF4 regulates plasma cell differentiation and its molecular actions are antagonized by the related protein IRF8 to promote the germinal center B cell fate. IRF4 and IRF8 are immune-system specific members of the IRF family of transcriptions factors that have crucial and diverse functions in regulating B and T lymphocytes as well as macrophages and dendritic cells. They have elucidated key activities of IRF4 in the genomic programming of Th17 cells as well as dendritic cells. A notable structural finding has been the discovery of distinct types of composite regulatory elements in immune response genes that are cooperatively bound by IRF4 or IRF8 with the Ets family member PU.1 or the AP-1 member BATF. Using structural and functional genomics as well as computational modeling, they are analyzing coherent networks of transcription factors and the large sets of genomic regulatory sequences through which they act. This is enabling them to assemble GRNs underlying B and macrophage cell fate specification, pre-B and plasma cell differentiation, and the programming of dendritic as well as CD4 T cell responses. They are interested in utilizing the knowledge of GRNs to engineer immune cells with new effector or regulatory capabilities that can be therapeutically harnessed.