Wuhan University, China
An Associate Professor at the School of Informatics and Computing, Indianan University. Before she worked as a senior researcher at the University of Innsbruck, Austria and as a researcher at the Free University of Amsterdam, the Netherlands. She has been involved in various NIH and European-Union funded Semantic Web projects. She has published 180+ papers in journals, conferences and workshops. She serves as a Program Committee member for 120+ international conferences and workshops. She is the coeditor of book series called Semantic Web Synthesis by Morgan & Claypool publisher. She is co-author of the book “Intelligent Information Integration in B2B Electronic Commerce” published by Kluwer Academic Publishers. She is also co-author of book chapters in the book “Spinning the Semantic Web” published by MIT Press and “Towards the Semantic Web: Ontology-driven Knowledge Management” published by Wiley. She is the editorial board member of four ISI indexed top journals in Information Science and Semantic Web. Her current interest areas include social network analysis, Semantic Web, citation analysis, knowledge management and application of Web Technology.
An associate professor at University of Chicago. He is the Director of Knowledge Lab (http://knowledgelab.org), which has collaborative, granting, employment opportunities, and ongoing seminars. He also directs the Computational Social Science initiative at the university, including workshops and educational programs. His research focuses on the collective system of thinking and knowing, ranging from the distribution of attention and intuition, the origin of ideas and shared habits of reasoning to processes of agreement, accumulation of certainty, and the texture of human understanding. He is especially interested in innovation--how new ideas and practices emerge--and the role that social and technical institutions (e.g., the Internet, markets, collaborations) play in collective cognition and discovery. Much of my work has focused on areas of modern science and technology. Evans’ work uses machine learning, generative modeling, social and semantic network representations to explore knowledge processes, scale up interpretive and field-methods, and create alternatives to current discovery regimes. A current project reasons over claims in the literature and the structure of the community that produced it to generate experiments that optimize therapeutic combinations against several cancers. His research is funded by the National Science Foundation, the National Institutes of Health, the Templeton Foundation and several other sources, and has been published in Science, PNAS, American Journal of Sociology, American Sociological Review, Social Studies of Science, Administrative Science Quarterly, PLoS Computational Biology and other journals. His work has been featured in Nature, the Economist, Atlantic Monthly, Wired, NPR, BBC, El País, CNN and many other outlets.
The Principal Data Scientist at IBM Almaden Research Center. His group develops the Watson Discovery Advisor for Life Sciences solution. In his role as Data Scientist he is leading the application of Watson technology to Accelerate Discovery. Some recent customer engagements include:
1) A project with Baylor College of Medicine to aid in the discovery of new potential cancer therapies centered around the P53 protein;
2) Work with Sanofi on using Watson technology for Drug Repurposing;
3) A First of a Kind project with Johnson & Johnson to analyze clinical trial information;
4) Supporting our efforts to help the NY Genome Center discovery new treatments for late stage cancer patients.
Assistant professor, University of Illinois at Urbana-Champaign
An assistant professor in the Department of Electrical and Computer Engineering, a research assistant professor in the Coordinated Science Laboratory, and a research affiliate in the Beckman Institute for Advanced Science and Technology, all at the University of Illinois at Urbana-Champaign. He received the B. S. degree with honors in electrical and computer engineering (magna cum laude) from Cornell University, Ithaca, New York in 2004. He received the S. M., E. E., and Ph. D. degrees in electrical engineering and computer science from the Massachusetts Institute of Technology (MIT), Cambridge in 2006, 2008, and 2010, respectively. He received the Jin-Au Kong Award Honorable Mention for Electrical Engineering doctoral thesis, the Ernst A. Guillemin Thesis Award for Outstanding Electrical Engineering S.M. Thesis, a best paper award at the 2012 SRII Global Conference, the Capocelli Prize at the 2006 Data Compression Conference, the Best Student Paper Award at the 2003 IEEE Radar Conference, and was a winner of the IEEE 2004 Student History Paper Contest. He has received an IBM eminence and excellence award for his work on crowdsourcing and has been named a Forward Thinker by IBM for his work on culinary computational creativity.
I am Associate Professor of Management and Organizations at the Kellogg School of Management, and (by courtesy) Industrial Engineering & Management Sciences at the McCormick School of Engineering, Northwestern University. I am also a core faculty at the Northwestern Institute on Complex Systems (NICO). Prior to joining Northwestern, I was Assistant Professor of Information Sciences and Technology at the Pennsylvania State University and before that, a Research Staff Member at the IBM T.J. Watson Research Center. I received my PhD in Physics in 2013 from Northeastern University, where I was a member of the Center for Complex Network Research. From 2009 to 2013, I had also held an affiliation with Dana-Farber Cancer Institute, Harvard University as a Research Associate. I received my B.S. degree in Physics from Fudan University in 2007. I am a recipient of the AFOSR Young investigator award (2016).
I lead a group of highly interdisciplinary researchers who are extremely passionate about data. Our research takes a multidisciplinary approach—combining statistical physics, computer science, and computational social science—to exploit the opportunities and promises offered by Big Data. Through the lens of new and increasingly available large-scale datasets, we hope to use and develop tools of network science to help improve the way in which we understand the interconnectedness of the social technical and business world around us. Our work has been applied to understand and predict social interactions, human mobility, knowledge production and scientific impact. Our research has been published in such general audience journals as Science, and PNAS as well as top specialized venues in computer science and physics, and has been featured in The New York Times, Forbes, The Economist, The Guardian, The Washington Post, The Boston Globe, among other major global media outlets.
Indiana University Bloomington 2017