Apr 11
Invited Speakers
Keynote Speaker:
Dr. Gavin Schmidt, NASA GISS
GAVIN SCHMIDT is a climatologist with NASA’s Goddard Institute for Space Studies in New York, where he models past, present, and future climate. He received a B.A. in mathematics in 1989 from Oxford University and a Ph.D. in applied mathematics in 1994 from University College London. He was a postdoctoral fellow at McGill University, in Montreal, until 1996, when he was awarded a Climate and Global Change Fellowship from the National Oceanic and Atmospheric Administration and moved to the Goddard Institute. Schmidt was cited by Scientific American as one of the fifty leading researchers of 2004 and was a contributing author for the 2007 Nobel prize-winning report of the Intergovernmental Panel on Climate Change. He is a cofounder and contributing editor of RealClimate.org, which provides context and background on climate science issues that are missing in popular media coverage. (edge.org)
Dr. Schmidt has made appearances on the Daily Show and PBS.
Invited Speakers
Dr. Hamsa Balakrishnan, MIT
HAMSA BALAKRISHNAN is the T. Wilson Career Development Assistant Professor of Aeronautics and Astronautics, and of Engineering Systems at the Massachusetts Institute of Technology (MIT). She received a B.Tech in Aerospace Engineering from the Indian Institute of Technology, Madras in 2000 and a Ph.D. in Aeronautics and Astronautics from Stanford University in 2006. Between May and December 2006, she was a researcher at the University of California, Santa Cruz and the NASA Ames Research Center. Her research interests address various aspects of air transportation systems, including algorithms for air traffic scheduling and routing, integrating weather forecasts into air traffic management and minimizing aviation-related emissions; air traffic surveillance algorithms; and mechanisms for the allocation of airport and airspace resources. She was a recipient of the NSF CAREER Award in 2008.
Dr. Sugato Basu, Google Research
SUGATO BASU is a Staff Research Scientist at Google Research. His areas of research interest include machine learning, data mining, predictive modeling and optimization, with special emphasis on scalable algorithm design for text and social network analysis. He did his Ph.D. in machine learning from UT Austin and worked briefly at SRI International before joining Google Research. He has written multiple papers, book chapters, and encyclopedia articles on large-scale learning, computational advertising, clustering, semi-supervised learning, record linkage, social search/routing, rule mining, and optimization. He is, however, yet to design an algorithm that learns faster than his 2-year old daughter.
Dr. Ying Chen, IBM Research
YING CHEN is a Research Staff Member, Master Inventor and a Sr. Manager at IBM Almaden Research Center. Ying received Ph.D. from Computer Science Department at University of Illinois at Urbana-Champaign. She has over 13 years of industry experience in established IBM research center and a start-up company. She leads a research team in IBM Almaden research center, focusing on Text Analytics and its application domains such as Social Media and Web analytics, patent and scientific literature analytics, bio- and Chem-informatics and Service-Oriented Computing. She also has extensive backgrounds in storage systems, parallel and distributed computing, databases, performance evaluation and modeling. Ying's team delivered successful analytics solutions that are commercially available. The work resulted in 30+ patents, numerous publications, and major awards such as Computer World Horizon award in 2006.
Dr. Fernando Gomez, UCF
FERNANDO GOMEZ graduated with a Ph.D. in Computer Science from the Ohio State University in 1981. He is now a Professor of Computer Science in the Department of Electrical Engineering and Computer Science at the University of Central Florida. Gomez's area of research is Natural Language Processing (NLP). His major focus is the determination of the verb meaning, or verb predicate, its argument structure, semantic roles and adjuncts from the output of statistical parses. In addition, he is working on the automated acquisition of knowledge from engineering domains, the Web, Wikipedia and the Google 1T 5-gram corpus. Recent publications describing this research include the ACL (Association for Computational Linguistics), AAAI (American Association for Artificial Intelligence), CoNLL (Conference on Computational Natural Language Learning).
Dr. David Hogg, NYU
DAVID HOGG is an astronomer in the Department of Physics at New York University. His work is focused on the Dark Matter; its properties can only be inferred (at the present day) by considering the kinematics of stars and gas (on small scales) or galaxies (on large scales). He also works on comprehensive projects in astrophysics, including measurement of the position and velocity of every star in our Galaxy, and the position and mass of every galaxy in the observable Universe. He received his Ph.D. from Caltech in 1998 and started at NYU in 2001.
Dr. Jane Malin, NASA JSC
As Expert Consultant, engineer and technology developer in the Software, Robotics and Simulation Division at NASA Johnson Space Center, Dr. JANE MALIN has developed methods and software for engineering advanced software and performing safety analyses for the past 26 years. She began her career at NASA developing expert systems technology for diagnosis and system management, and then moved on to develop qualitative simulation tools to aid in the development and simulation-based evaluation of intelligent control software. She holds two software patents for the qualitative simulation software. To streamline model development, Dr. Malin has developed software for automatically extracting system models from requirements and Failure Modes and Effects Analysis (FMEA) worksheets. To support model extraction and safety analysis, she has developed an extensible aerospace nomenclature (called an ontology) for text analysis, text mining, and information extraction. The ontology is also used in natural language processing software that identifies types of problems that are described in various ways in text descriptions in problem reports.
Dr. Ramakrishna Nemani, NASA ARC
RAMAKRISHNA NEMANI is a senior research scientist with the Earth Science Division at Ames Research Center. He leads a small group of research scientists and engineers to create ecological nowcasts and forecasts, the biological equivalents of weather and climate forecasts.
Tutorial Speaker
Dr. Arindam Banerjee, U. Minnesota
Arindam Banerjee is an Assistant Professor and a McKnight Land Grant Professor in the Department of Computer Science & Engineering, and a Resident Fellow in the Institute on the Environment (IonE) at the University of Minnesota, Twin Cities. He received his Ph.D. from the University of Texas at Austin in 2005, where his dissertation was nominated for the best dissertation award. His research interests are in Machine Learning, Data Mining, Information Theory, Convex Analysis and Optimization, and their applications in complex real world problems including those in Text and Web Mining, Social Network Analysis, Healthcare, Bioinformatics, Climate and Environmental Sciences, and Finance. He has won several awards including the NSF CAREER award in 2010, the McKnight Land-Grant Professorship at the University of Minnesota, Twin Cities, 2009-2011, the J. T. Oden Faculty Research Fellowship from the Institute for Computational Engineering and Sciences (ICES), University of Texas at Austin, 2006, and the prestigious IBM PhD fellowship for the academic years 2003-2004 and 2004-2005. He has also won several awards for his publications, including the Best Paper Award at the SIAM International Conference on Data Mining (SDM), 2004, the Best Research Paper Award under University Cooperative Society Research Excellence Awards, University of Texas at Austin, 2005, and the Best of SIAM Data Mining (SDM) Award at the SIAM International Conference on Data Mining, 2007.