Assistant Professor, University of Rochester
American Politics and Political Methodology
Matthew Blackwell is an Assistant Professor of Political Science at the University of Rochester. His research focuses on American politics and political methodology. In American politics, he studies campaigns, the effectiveness of negative advertising, and Congressional staff networks. In methods, he works on dynamic causal inference, missing data, panel data, and social network analysis.
Senior Manager, Business Analytics Research , IBM T.J. Watson Research Center
From Deep Computing to Big Data
Murray Campbell is Senior Manager of Business Analytics Research at the IBM T.J. Watson Research Center. His group conducts basic research in analytics and optimization, and applies this expertise to a broad range of business problems. He was a lead member of the team that developed Deep Blue, the first computer to defeat the reigning world chess champion in a regulation match. Murray is an ACM Distinguished Scientist and a Fellow of the Association for the Advancement of Artificial Intelligence.
Associate Professor, Cornell University
Tanzeem Choudhury directs the People-Aware Computing group at Cornell University, which works on developing machine learning techniques for systems that can reason about human activities, interactions, and social networks in everyday environments. She received my Ph.D. degree from M.I.T., where she helped pioneer a new field of research referred to as Reality Mining. She holds a B.S. in Electrical & Computer Engineering from the University of Rochester.
Senior Associate Dean for Faculty and Research; Professor of Computers and Information Systems, University of Rochester - Simon School
Professor Dewan is responsible for faculty affairs, faculty research, and faculty recruiting and development.
He has teaching and research interests in electronic commerce, organizational issues in management of information systems, the information technology industry, and financial information systems. He has won three Best Paper Awards for research, done in collaboration with his colleagues at the Simon School, in the use of information systems standards in organizations, redesign of business processes and management of websites. His current research interests include marketing on the Internet, the Internet industry, strategic use of technology, the use of standards in managing information systems, and accounting and financial information systems. His papers have appeared in the Journal of Computing, Management Science, Decision Support Systems and IEEE Transactions on Computers, among other journals.
Prior to joining the Simon School, Dewan was a faculty member at Northwestern University’s Kellogg Graduate School of Management. He is a member of INFORMS, the Association for Information Systems and Beta Gamma Sigma.
Dewan earned a B. Tech. degree from the Indian Institute of Technology, New Delhi; an MS degree with concentrations in Computers and Information Systems and Operations Research from the University of Rochester; and a PhD in Business Administration from the University of Rochester.
Associate Professor, University of Washington
Pedro Domingos, faculty member at the University of Washington, is the author or co-author of over 150 technical publications in machine learning and data mining. He is a member of the editorial board of the Machine Learning journal, co-founder of the International Machine Learning Society, and a AAAI Fellows.
Professor, Department of Computer Science, Carnegie Mellon University
Christos Faloutsos is a Professor at Carnegie Mellon University. He has received the Presidential Young Investigator Award by the National Science Foundation (1989), the Research Contributions Award in ICDM 2006, the SIGKDD Innovations Award (2010), eighteen ``best paper'' awards, and four teaching awards. He is an ACM Fellow. His research interests include data mining for graphs and streams, fractals, database performance, and indexing for multimedia and bio-informatics data.
Assistant Professor, University of Texas
Vibhav Gogate is an Assistant Professor in the Computer Science Department at University of Texas, Dallas. He is a member of the Human Language Technology Research Institute. His research interests are in machine learning, automated reasoning and artificial intelligence with a focus on graphical models and their logic-based extensions such as Markov logic.
Professor and Director , Cornell University
Carla Gomes is a Professor of Computer Science at Cornell University and Director of the Institute for Computational Sustainability. Her research includes the integration of constraint reasoning, operations research, and machine learning techniques for solving scale constraint reasoning and optimization problems, complete randomized search methods, and algorithm portfolios, planning and scheduling, and multi agent systems. Gomes is a Fellow of the Association for the Advancement of Artificial Intelligence.
Professor, Computer Science & Engineering at the University of Washington
Carlos Guestrin is a professor of Computer Science & Engineering at the University of Washington. He is also the co-founder of GGideaLab, a start up focused on monetizing social networks. Carlos was named one of the 2008 `Brilliant 10' by Popular Science Magazine, received the IJCAI Computers and Thought Award and the Presidential Early Career Award for Scientists and Engineers (PECASE). His leads the GraphLab project, developing an infrastructure for distributed and cloud-based large-data analytics, optimization, and machine learning.
Head of the Structured Data Group, Google
Dr. Alon Halevy heads the Structured Data Group at Google Research. Dr. Halevy's research interests are in data integration, structured-data on the Web, semantic heterogeneity, personal information management, management of XML data, web-site management, peer-data management systems, query optimization, database theory, knowledge representation, and more generally, the intersection between Database and AI technologies. He lead the creation of Google Fusion Tables, a collaborative tool for data management and visualization in the cloud. He is Fellow of the Association of Computing Machinery (ACM), and was a Sloan Fellow, and received the Presidential Early Career Award for Scientists and Engineers (PECASE) when he held the rank of Professor at University of Washington. He is also an expert on coffee and its impact on culture, and author of the book, The Infinite Emotions of Coffee.
Chair, Computer Science
Henry Kautz is Chair of the Department of Computer Science at the University of Rochester. He performs research in social media, knowledge representation, pervasive computing, and assistive technology. He is President (2010-2012) of the Association for the Advancement of Artificial Intelligence, Fellow of the AAAI, a Fellow of the American Association for the Advancement of Science, and a recipient of the IJCAI Computers and Thought Award.
Assistant Professor, University of Oregon
Daniel Lowd is an Assistant Professor in the Department of Computer and Information Science at the University of Oregon. His research interests include learning and inference with probabilistic graphical models, adversarial machine learning, and statistical relational machine learning. He maintains Libra, an open-source toolkit for Learning and Inference in Bayesian networks, Random fields, and Arithmetic circuits.
Associate Professor, University of Rochester
Computer Vision and Data Mining
Jiebo Luo joined the University of Rochester in Fall 2011 after over fifteen years at Kodak Research Laboratories, where he was a Senior Principal Scientist leading research and advanced development. He has been involved in numerous technical conferences, including serving as the program co-chair of ACM Multimedia 2010 and IEEE CVPR 2012. He is the Editor-in-Chief of the Journal of Multimedia, and has served on the editorial boards of the IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Multimedia, IEEE Transactions on Circuits and Systems for Video Technology, Pattern Recognition, Machine Vision and Applications, and Journal of Electronic Imaging. He is a Fellow of the SPIE, IEEE, and IAPR.
Professor, Duke University
Wavelet and Diffusion Analysis
Dr. Mauro Maggioni received the Ph.D. in Mathematics from the Washington University, St. Louis, in 2002. He then was a Gibbs Assistant Professor in Mathematics at Yale University, till 2006 when he moved to Duke University as an Assistant Professor of Mathematics and Computer Science. He is currently Professor of Mathematics and Computer Science. His work focuses on high-dimensional probability, approximation theory, harmonic analysis, machine learning, graph theory, signal processing and control theory.
Professor Deborah L. McGuinness Tetherless World Constellation Chair , Rensselaer Polytechnic Institute
Deborah McGuinness is the Tetherless World Professor of Computer and Cognitive Science, and the founding director of the Web Science Research Center at Rensselaer Polytechnic Institute. Deborah is a leading authority on the semantic web and has been working in knowledge representation and reasoning environments for over 25 years. Deborah's primary research thrusts include work on explanation, trust, ontologies, escience, open data, and semantically-enabled schema and data integration. Prior to joining RPI, Deborah was the acting director of the Knowledge Systems, Artificial Intelligence Laboratory and Senior Research Scientist in the Computer Science Department of Stanford University. Deborah is also widely known for her leading role in the development of the W3C Recommended Web Ontology Language (OWL) and her work on earlier description logic languages and environments. She has built and deployed numerous ontology environments and ontology-enhanced applications, including some that have been in continuous use for over a decade at AT&T and Lucent, and two that have won deployment awards for variation reduction on plant floors and interdisciplinary virtual observatories. She has published over 200 peer-reviewed papers and has authored granted patents in knowledge based systems, ontology environments, configuration, and search technology.
Deborah also consults with clients wishing to plan, develop, deploy, and maintain semantic web and/or AI applications. Some areas of recent work include: ontology design and evolution environments, semantically-enabled virtual observatories, semantic integration of scientific data, context-aware mobile applications, search, eCommerce, eHealth, configuration, and supply chain management. She is a frequent technology advisory board member, currently with Qualcomm, SocialWire, and Sandpiper Software. She also advised Applied Semantics, Guru Worldwide, and Cerebra prior to their acquisitions. Deborah has also worked as an expert witness in a number of cases, and has deposition and trial experience. Deborah received her Bachelors degree in Math and Computer Science from Duke University, her Masters degree in Computer Science from University of California at Berkeley, and her Ph.D. in Computer Science from Rutgers University.
Independent Consultant and Author on Data Mining and Analytics
Temporal Data Mining
Dr. Mitsa holds a Ph.D. degree in Electrical Engineering from the University of Rochester and is the author of 47 publications, 10 U.S. patents and the book (CRC Press, 2010) Temporal Data Mining. She has diverse academic and industrial experience, having served as a faculty member at the Universities of Iowa and Massachusetts and a Senior Software Engineer at GE HealthCare and Abiomed. Dr. Mitsa has received awards from the National Science Foundation, the Whitaker Foundation, HP, and the Fulbright program. Her most recent patent (awarded Aug. 2012), is on a adaptive hybrid reasoning decision-support system.
Professor and Director , University of Texas at Austin / UT Artificial Intelligence Laboratory
Natural Language Learning
Raymond J. Mooney is a Professor in the Department of Computer Science at the University of Texas at Austin. He is an author of over 150 published research papers, primarily in the areas of machine learning and natural language processing. He was the President of the International Machine Learning Society from 2008-2011 and is a Fellow of both the American Association for Artificial Intelligence and the Association for Computing Machinery.
Professor, Rensselaer Polytechnic Institute
Heidi Jo Newberg is an American astrophysicist known for her work in understanding the structure of our Milky Way galaxy. Among her team's findings is the first-ever evidence that the Milky Way is "cannibalizing" stars from smaller galaxies. She is a founding participant in the Sloan Digital Sky Survey (SDSS) and the Sloan Extension for Galactic Understanding and Exploration (SEGUE), and is a leader of the astrophysical MilkyWay@home distributed computing project team. She is currently a professor of Physics, Applied Physics, and Astronomy at Rensselaer Polytechnic Institute (RPI) in Troy, New York.
John Quackenbush is a computational biologist and genome scientist. He is the Professor of Biostatistics and Computational Biology, Professor of Cancer Biology at the Dana-Farber Cancer Institute (DFCI), as well as the director of its Center for Cancer Computational Biology (CCCB). Quackenbush also holds an appointment as Professor of Computational Biology and Bioinformatics in the Department of Biostatistics at the Harvard School of Public Health (HSPH). In 2011, Quackenbush published The Human Genome: Book of Essential Knowledge, which outlines the history, science, and implications behind the Human Genome Project.
Assistant Professor, Cornell University
Human Neuroscience and Computational Modeling
In July 2013, Rajeev Raizada will be starting as an Assistant Professor in the Department of Brain & Cognitive Sciences at the University of Rochester. He is currently in the Psychology Department at Cornell. More information about his research and downloadable publications can be found at http://raizadalab.org
Assistant Professor, University of Rochester - Simon School
Social Media and Decision Making
Assistant Professor of Computers and Information Systems Professor Rui's research interests include the study of social media, online advertising, securitization, and operation management. His current research focuses on the how business can make use of "big data" from social media sites such as Twitter and Facebook to improve decision making. He is also presently investigating how to efficiently allocate heterogeneous and uncertain display advertising opportunities among multiple advertisers.
Associate Chair, Professor of Biostatistics, Professor of Psychiatry, University of Rochester
Xin Tu is Professor of Biostatistics and Psychiatry in the Department of Biostatistics and Computational Biology and Department of Psychiatry. He is the Director of the Statistical Consulting Center and the Director of the Psychiatric Statistics Division within the Department of Biostatistics and Computational Biology. Dr. Tu has done important work in the areas of U-statistics, longitudinal data analysis, survival analysis with interval censoring and truncation, and pooled testing, and has successfully applied his novel development to addressing important methodological problems in HIV/AIDS, mental health and psychosocial research. In recent years, he and his group have been focusing on issues arising in research on accuracy of proxy outcomes, causal effect from group-based psychosocial interventions and observational longitudinal data, and intervention pathways (mechanism of action) as well as interplay between biological, behavioral and societal factors in the study of disease etiology and treatment.
Assistant Professor , University of Florida
Daisy Zhe Wang is an Assistant Professor in the Department of Computer & Information Science & Engineering at University of Florida. Daisy’s main research interest lies at the border of Data Management Systems (DBMS’s) and Statistical Machine Learning (SML) in Computer Science. She pursues research topics such as probabilistic databases, in-database information extraction, large-scale advanced data analysis, and query-driven interactive machine learning.
Associate Professor of Radiology Associate Professor of Biomedical Engineering Associate Professor of Electrical and Computer Engineering Director, Computational Radiology Laboratory, University of Rochester
Computational Intelligence in Biomedicine
Axel W. E. Wismueller is an Associate Professor of Radiology, Biomedical, and Electrical Engineering at the University of Rochester Medical Center, where he directs the Computational Radiology Laboratory at the Department of Imaging Sciences. Dr. Wismueller holds M.D. and Ph.D. degrees from the Technical University of Munich. Based on his dual professional qualification in both science and medicine, his main research interest is focused on innovative strategies for pattern recognition and computational intelligence, with a specific emphasis on computer-aided diagnosis in biomedical imaging, such as functional MRI for human brain mapping and image-based breast cancer diagnosis. Dr. Wismueller is author of more than 120 scientific journal and conference publications, holds U.S. and European medical licenses, multiple international patents, and has recently been granted an NIH Award to establish an international scientific initiative for exploring large-scale connectivity in the human brain.
Research Associate , University of Colorado at Boulder