UW MSR Summer Institute 2012
Crowdsourcing Personalized Online Education
Attendees
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Eytan Adar is an Assistant Professor of Information and Computer Science at the University of Michigan. He works on temporal-informatics which is the study of the change of information - and our consumption of it - over time. This is primarily at Internet scales and it gives him an excuse to work on lots of different things he likes: text and log mining, visualizations, social network analysis, etc. Before grad school, he was a researcher at HP Labs' Information Dynamics Group and at Xerox PARC. He can be reached at eytanadar-at-yahoo-dot-com. Among other things, he is associated with the MISC and MIDAS groups (HCI and data mining, respectively). He is one of the founders of ICWSM, and more recently Jaime Teevan and he organized WSDM 2012 which took place in Seattle.

Sumit Basu is a Researcher in the Machine Learning Department at Microsoft Research, Redmond. His research focus is on developing interactive, machine-learning based power tools to assist users in understanding and extracting answers from complex data - teaching material/textbooks, computer systems, sensory signals like speech or music, scientific data, document collections, or the web. These power tools sometimes work by observing a user as they perform a task, then assisting them in their efforts once it understands what's going on; in other cases (as in teaching) they provide inputs to the user and adaptively refine their strategy based on what works best. The interactive aspect comes from having humans in a tight loop with the learning algorithm: instead of getting a big batch of labeled data, interactive learning tasks involve a delicate dance between the human and the algorithm to achieve sufficient performance with a minimum of operator effort.

Michael Bernstein will be joining Stanford University's Computer Science department as an Assistant Professor. His research in human-computer interaction focuses on crowdsourcing and social computing systems. He has been awarded Best Student Paper at UIST 2010, Best Paper at ICWSM 2011, the NSF graduate research fellowship and the Microsoft Research PhD fellowship. His work has appeared in venues like the New York Times, Slate, CNN and The Atlantic. He received Ph.D. and masters degrees in EECS at MIT, and a bachelors degree in Symbolic Systems at Stanford University.

Jeff Bigham is an Assistant Professor in the Department of Computer Science at the University of Rochester where he heads the ROC HCI Group. His work is at the intersection of human-computer interaction, human computation, and artificial intelligence, with a focus on developing innovative technology that serves people with disabilities in their everyday lives. He's worked on the cloud-based screen reader WebAnywhere, which led him to Raising the Floor Consortium and the architecture committee for the Global Public Inclusive Infrastructure. He's also the creator of VizWiz, an iPhone application that lets blind users take a picture, speak a question, and receive answers from the crowd quickly (usually in less than 30 seconds). Most recently he's been working on "closed-loop crowd control and support" that allow dynamic groups to act like highly-skilled individuals.

Emma Brunskill is an assistant professor in the computer science department at Carnegie Mellon University. She was recently selected as a Microsoft Research faculty fellow. Her research lies in artificial intelligence and machine learning, where she focuses on novel methods to automatically make good sequences of decisions under uncertainty. She is particularly interested in applications of this work to intelligent tutoring systems and healthcare. She is also interested in how information technology can be used to help address challenges that arise in low resource areas.

Stephanie Chang is a software engineer at Khan Academy, where she aims to make learning more engaging for millions of people. She graduated from Duke with a BSE in Electrical and Computer Engineering and a minor in Computer Science.

Micki Chi is a cognitive scientist interested in how middle-school students learn complex science concepts. One topic of her research focuses on what students can do to enhance their own learning. She introduced the constructive process of self-explaining, and more recently, proposed the ICAP hypothesis that predicts the level of learning as a function of the mode of engagement activities students undertake. Another topic of her research examines the origin of scientific misconceptions and how to teach robustly misconceived emergent kind of processes covered in middle school science. A 2012 paper, published in Cognitive Science, titled Misconceived Causal Explanations for Emergent Processes describes this work. A third topic of her research addresses novel ways of delivering instruction. She suggests that tutorial dialogue may be a promising way to deliver online instruction. Dr. Chi has published numerous papers and has well over 21,000+ citations of her work. Dr. Chi is a Fellow in Cognitive Science, APA, APS; she was awarded the Chancellor's Distinguished Research Award by the University of Pittsburgh in 2006, and inducted into the National Academy of Education in 2010.

Lydia Chilton is a computer science PhD student at the University of Washington advised by James Landay. From 2002 to 2009 she was at MIT where she did Economics '06, EECS '07 and an EECS M.Eng '09 advised by Rob Miller. She also did Math, but MIT doesn't let you triple major.

Cristina Conati is an associate professor of Computer Science at the University of British Columbia. Her goal is to integrate research in Artificial Intelligence, Cognitive Science and Human Computer Interaction to make complex interactive systems increasingly more effective and adaptive to user needs. She is particularly interested in extending the range of user features that can be captured in and efficiently processed by a computational user model - from purely cognitive features (knowledge, goals, preferences), to meta-cognitive skills (e.g., the capability of effectively exploring a large information space),personality traits and emotional reactions. The aim is to widen the spectrum of information that an interactive system can use to dynamically adapt its behavior to a user's needs.

Laura Dabbish is an assistant professor of Information Technology and Organizations in the H. John Heinz III College of Public Policy, Information Systems, and Management at Carnegie Mellon University. She also has a partial appointment in the Human-Computer Interaction Institute in the School of Computer Science. She studies Computer-Supported Cooperative Work, particularly the design and use of communication technologies. She is interested in understanding and addressing problems of attention, interruption, multi-tasking, and overload in the modern workplace. In her current research, she is examining how distributed groups coordinate their work, and what technological and social interventions can facilitate coordination. Her goal is to design interfaces and organizational processes that more efficiently manage human attention at work.

Emily Dalton Smith is a program officer at the Bill & Melinda Gates Foundation, where she manages the foundation's portfolio of digital courseware for middle and high school. Her investments include adaptive games, digital tutors, and mobile apps for education. Emily worked previously at Arizona State University, where she oversaw student services and technology partnerships for ASU's online campus, and was special assistant to the provost. She graduated with honors from the University at Buffalo and received a master's degree in political science with a focus on science and technology policy from ASU.

Ed Dieterle is a senior program officer at the Bill & Melinda Gates Foundation. He develops and supports research projects and evaluation efforts that target learning and teaching with next generation learning innovations. His research and scholarship has focused on the psychosocial and policy aspects of learning and teaching with serious games and other highly interactive and immersive technologies using qualitative and quantitative methods.

Mira Dontcheva is a senior research scientist at Adobe Systems. Her research focuses on instructional design, search and sensemaking interfaces, and creativity. She finished my Ph.D. in Computer Science in 2008 at the University of Washington with David Salesin, Michael Cohen and Steven Drucker. Her thesis focused on novel interaction techniques for collecting and organizing Web content. She was an undergraduate at the University of Michigan in Ann Arbor and completed her B.S.E. in Computer Engineering in 2000.

Susan Dumais is a Principal Researcher and manager of the Context, Learning and User Experience for Search (CLUES) Group at Microsoft Research. Prior to joining Microsoft Research, she was at Bell Labs, where she worked on Latent Semantic Indexing (a statistical method for concept-based retrieval), interfaces for combining search and navigation, and organizational impacts of new technology. Her current research focuses on user modeling and personalization, temporal dynamics of information, and interactive information retrieval systems. She has worked closely with several Microsoft groups (Bing, Windows Desktop Search, SharePoint and Office) on search-related innovations, and has published many articles in the fields of information science, human-computer interaction, and cognitive science. Susan is also an adjunct professor in the Information School at the University of Washington. She is Past-Chair of ACM's Special Interest Group in Information Retrieval (SIGIR), and serves on several editorial boards, technical program committees, and government panels. She was elected to the CHI Academy in 2005, an ACM Fellow in 2006, received the Gerard Salton Award from SIGIR for Lifetime Achievement in 2009, and was elected to the National Academy of Engineering (NAE) in 2011. More information can be found at http://research.microsoft.com/~sdumais.

Krzysztof Gajos is an assistant professor in Computer Science in the School of Engineering and Applied Sciences at Harvard University. His research interests are in human-computer interaction, artificial intelligence and applied machine learning. The phrase "intelligent interactive systems" describes well many of his interests: He is interested in how intelligent technologies can enable novel ways of interacting with computation, and in the new challenges that human abilities, limitations and preferences create for machine learning algorithms embedded in interactive systems. Together with several students, he has started the Intelligent Interactive Systems Group at Harvard. The main themes in his current research are ability-based user interfaces, creativity support tools, and interactive machine learning.

Barbara Grosz is a professor of computer science in the School of Engineering and Applied Sciences at Harvard University. To create the scientific and technological base for easy-to-use, large-scale information systems requires better systems for human-computer communication. Theories and models of collaboration are essential for constructing systems able to work with each other and their users. The ability to collaborate is critical if we are to have systems that are helpful assistants and not merely tools. Professor Grosz's research group addresses fundamental problems in modeling collaborative activity, developing computer agents able to collaborate with each other and their users, and constructing collaborative, multi-modal systems for human-computer communication. In the last several years, her group has been applying these theories and techniques to the development of collaborative interfaces for educational software and health informatics systems.

Sumit Gulwani is a senior researcher at Microsoft Research, Redmond. His research interests are in the cross-disciplinary application areas of automating end-user programming (for a variety of systems such as spreadsheets, smartphones, robots), and in building intelligent tutoring systems (for K-12 math/science/language subjects). He has expertise in automated programming (from examples, natural language and/or logic) and program analysis techniques. He obtained his Phd in Computer Science from UC-Berkeley in 2005 and was awarded the ACM SIGPLAN Outstanding Doctoral Dissertation Award. He received his undergraduate degree from IIT Kanpur in 2000 and was awarded the President's Gold Medal.

Anoop Gupta is a Distinguished Scientist at Microsoft Research. He works on cross-disciplinary research that has potential for large business or societal impact. His most recent projects focus on areas of communication, collaboration, and natural user interfaces. He reports to Rick Rashid, Chief Research Officer and global head for Microsoft Research.

Bjoern Hartmann is an Assistant Professor in the Computer Science Division at UC Berkeley. His research in Human-Computer Interaction focuses on novel design, prototyping, and implementation tools for the era of post-personal computing. He co-directs the Berkeley Institute of Design and the Berkeley Swarm Lab. His research has received numerous Best Paper Awards at ACM CHI and UIST.

Eric Horvitz is a Distinguished Scientist at Microsoft Research. His interests span theoretical and practical challenges with developing systems that perceive, learn, and reason. His research includes exploration of principles for meshing machine and human intelligence, including the use of machine learning and decision-theoretic procedures in studies of crowdsourcing and human computation. He has been elected a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) and of the American Academy of Arts and Sciences. He serves on the NSF Computer & Information Science & Engineering (CISE) Advisory Board and on the council of the Computing Community Consortium (CCC). He received his PhD and MD degrees at Stanford University. More information can be found at http://research.microsoft.com/~horvitz.

Panos Ipeirotis is an Associate Professor at the Department of Information, Operations, and Management Sciences at Leonard N. Stern School of Business of New York University. His recent research interests focus on crowdsourcing and on mining user-generated content on the Internet. He received his Ph.D. degree in Computer Science from Columbia University in 2004, with distinction. He has received three "Best Paper" awards (IEEE ICDE 2005, ACM SIGMOD 2006, WWW 2011), two "Best Paper Runner Up" awards (JCDL 2002, ACM KDD 2008), and is also a recipient of a CAREER award from the National Science Foundation.

Ece Kamar is a researcher in the Adaptive Systems and Interaction group at Microsoft Research, Redmond. Her research interests include human-computer collaboration, decision-making under uncertainty, and mechanism design with a focus on real-world applications that bring people and adaptive agents together. She is in particular interested in building collaborative systems for assisting users in mobile domains and for solving crowdsourcing tasks. She received a Ph.D. in computer science from Harvard University in 2010. Her thesis focused on reasoning under uncertainty for successful human-computer teamwork. She received a M.S. from Harvard University in 2007 and a B.S. from Sabanci University in Turkey in 2005.

David Karger is a member of the Computer Science and Artificial Intelligence Laboratory in the EECS department at MIT. His interests include information retrieval (particularly The haystack project) and analysis of algorithms. He has also spent some time working at Akamai and consulting for Google and Vanu Inc. Last year he spent half his time on sabbatical at MSR New England.

Scott Klemmer is an Associate Professor of Computer Science at Stanford University. He co-directs the Human-Computer Interaction Group and holds the Bredt Faculty Scholar development chair. Organizations around the world use his lab's open-source design tools and curricula; several books and popular press articles have covered his research and teaching. He has been awarded the Katayanagi Emerging Leadership Prize, Sloan Fellowship, NSF CAREER award, Microsoft Research New Faculty Fellowship, and several best paper awards at the premier HCI conferences (CHI and UIST). His former graduate students are leading professors, researchers, founders, social entrepeneurs, and engineers. He has a dual BA in Art-Semiotics and Computer Science from Brown University, Graphic Design work at RISD, and an MS and PhD in Computer Science from UC Berkeley. He serves on the editorial board of TOCHI and HCI, was the program co-chair of UIST 2011, and co-chaired the systems area of CHI 2010. He is teaching a free, online HCI class.

Andrew Ko is an assistant professor in the iSchool at UW. Modern software is increasingly complex, making it ever more difficult to use, understand, and fix. His research group invents technologies that help people understand and overcome this complexity, including new help systems for end users, new debugging tools for developers, and new educational technologies for people learning to program. His interests span human-computer interaction, software engineering, and computing education.

Mitchell Koch is a PhD student in Computer Science & Engineering at the University of Washington, advised by Dan Weld. His primary research interests are in the field of machine learning, and he is presently working on specialized Web search for online course materials.

Kenneth Koedinger's background includes a BS in Mathematics, a MS in Computer Science, a PhD in Cognitive Psychology, and experience teaching in an urban high school. This multi-disciplinary preparation has been critical to his research goal of creating educational technologies that dramatically increase student achievement. Toward this goal, he creates "cognitive models", computer simulations of student thinking and learning, that are used to guide the design of educational materials, practices and technologies. These cognitive models provide the basis for an approach to educational technology called "Cognitive Tutors" in which we create rich problem solving environments for students to work in and provide just-in-time learning assistance much like a good human tutor does. He has developed Cognitive Tutors for mathematics and science and have tested them in the laboratory and the classroom. In a whole-year classroom study with their Algebra Cognitive Tutor, he has shown that students in their experimental classrooms outperformed students in control classes by 50-100% on targeted real world problem solving skills and by 10-25% on standardized tests. His research has contributed new principles and techniques for the design of educational software and has produced basic cognitive science research results on the nature of mathematical thinking and learning. He has authored 67 peer-reviewed publications, 6 book chapters, and 42 other papers and have been a Project Investigator on 16 major grants. He is a co-founder and board member of Carnegie Learning, Inc. and the CMU director of the Pittsburgh Science of Learning Center (PSLC). The PSLC is a $25 million National Science Foundation center that will provide researchers with the "LearnLab", an international resource for creating, running, and analyzing realistic and rigorous experiments on human and machine learning.

James Landay is a Professor in Computer Science & Engineering at the University of Washington, specializing in human-computer interaction. His current research interests include Automated Usability Evaluation, Demonstrational Interfaces, Ubiquitous Computing, User Interface Design Tools, and Web Design. He is also an Adjunct Associate Professor of both Human Centered Design & Engineering and in the Information School. James was previously the Laboratory Director of Intel Labs Seattle, a university affiliated research lab that is exploring the new usage models, applications, and technology for ubiquitous computing. He is a founding member of the University of Washington Design:Use:Build (DUB) Center, a cross-campus interdisciplinary group of HCI and Design researchers.

Christopher Lin is a first-year PhD student in Computer Science and Engineering at the University of Washington. He is advised by Dan Weld and Mausam. His primary research interests are in the field of Artificial Intelligence. Presently, he is working on planning and machine learning with applications to crowdsourcing.

Yun-En Liu is a 3rd year PhD student in UW CSE. He is interested in games, especially learning discovery games, such as Refraction. These are games that can be used to run educational experiments on student players to determine students' optimal pathways for learning. His current research focus is on assessment of students' game and fraction knowledge as they play our games; if we could infer what students know based on types of moves students are willing to make, we would be able to both present this information to their teachers and parents along with possible interventions, or we could use this to generate levels or hints that force students to experiment with concepts they do not yet know well.

Mausam graduated with his PhD in 2007 and joined the Turing Center at the University of Washington as a Research Assistant Professor. His research explores several threads in artificial intelligence, including scaling probabilistic planning algorithms, large-scale information extraction over the Web, panlingual machine translation and enabling complex computation over crowd-sourced platforms. His PhD dissertation received honorable mention for the 2008 ICAPS Best Dissertation Award awarded to the best AI Planning and Scheduling dissertation of the two previous years. He had earlier received his B.Tech. from Indian Institute of Technology, Delhi in 2001.

Rob Miller is an associate professor of computer science at MIT CSAIL. He earned his PhD from Carnegie Mellon University (2002), and has won an ACM Distinguished Dissertation honorable mention, NSF CAREER award, and six best paper awards at UIST and USENIX. His research interests lie at the intersection of programming and human computer interaction: making programming easier for end-users (web end-user programming), making it more productive for professionals (HCI for software developers), and making humans part of the programming system itself (crowd computing and human computation).

David Molnar's interests are primarily in software security, cryptography, and electronic privacy. More recently he has started exploring mobile devices and cloud security. He works in the Security and Privacy group let by Helen Wang. He also works with Patrice Godefroid, Ella Bounimova, and Michael Levin on the Scalable Automated Guided Execution (SAGE) project. Before MSR, he spent several years at Berkeley, where he finished a PhD with David Wagner.

Andrew Ng is an associate professor in the computer science department at Stanford andis the director of Stanford's AI lab. His research interests include artificial intelligence, machine learning, unsupervised feature learning and deep learning, neuroscience-informed AI, and Robotics.

Nell O'Rourke is a third year Ph.D. student at the University of Washington advised by Zoran Popović. She works in the Center for Game Science developing technologies to foster learning and engagement in educational video games. She is particularly interested in understanding how game interfaces can adapt to a player's strengths and weaknesses and empower learning and exploration. She is also a member of DUB, a multidisciplinary group at UW that conducts research in Human Computer Interaction and Design.

Zoran Popović joined the CSE faculty in the summer of 1999. He received a Sc.B. with Honors in Computer Science from Brown University in 1991, M.S. in Computer Science in 1993 and a Ph.D. in Computer Science in 1999 from Carnegie Mellon University. His Ph.D. dissertation research focused on the automatic synthesis and transformation of realistic character animation. His thesis also involved numerous performances of embarrassing acts. He has also held research positions at Sun Microsystems and Justsystem Pittsburgh Research Center and University of California at Berkeley. Zoran's research interests lie primarily in computer graphics, especially in character animation, motion editing, physically based modeling and modeling/simulation of natural phenomena. He is also interested in nonlinearly constrained optimization, motion planning and biomechanics.

Meredith Ringel Morris is a researcher in the Natural Interaction group at Microsoft Research. She is also an affiliate associate professor in the department of Computer Science & Engineering and in the Information School at the University of Washington. Dr. Morris's research area is human-computer interaction, with a particular emphasis on computer-supported cooperative work and social computing. Dr. Morris served as the co-chair of the technical program for CHI 2009, the ACM's flagship conference on the topic of human-computer interaction, and is serving as program chair for CSCW 2014, the ACM's premier conference on collaborative and social computing. She was named one of 2008's 35 Innovators Under 35 by Technology Review. Dr. Morris earned a Ph.D. and M.S. in computer science from Stanford University, and an Sc.B. in computer science from Brown University.

Dawn Song is Associate Professor of Computer Science at UC Berkeley. Prior to joining UC Berkeley, she was an Assistant Professor at Carnegie Mellon University from 2002 to 2007. Her research interest lies in security and privacy issues in computer systems and networks, including areas ranging from software security, networking security, database security, distributed systems security, to applied cryptography. She is the recipient of various awards including the MacArthur Fellowship, the Guggenheim Fellowship, the NSF CAREER Award, the Alfred P. Sloan Research Fellowship, the MIT Technology Review TR-35 Award, the IBM Faculty Award, the George Tallman Ladd Research Award, the Okawa Foundation Research Award, the Li Ka Shing Foundation Women in Science Distinguished Lecture Series Award, and Best Paper Awards from top conferences.

Kate Starbird is an Assistant Professor at the Department of Human Centered Design and Engineering (HCDE) at the University of Washington. Situated within the fields of HCI and CSCW and incorporating theoretical perspectives from cognitive science and communication studies, Ms. Starbird's research examines interaction and collaboration as enabled, supported, and structured by social media and other online tools. Ms. Starbird investigates both large-scale and small group interaction within the context of crises and other mass disruption events, studying how digital volunteers and other members of the connected crowd work to filter and shape the information space. Her PhD research combined qualitative analysis of social media communications, interviews with digital volunteers, and participant observation within digital volunteer communities with quantitative and computational analysis of large, social media data sets to investigate patterns of human behavior that constitute the "crowdsourcing" phenomenon during crises.

Stewart Tansley is a Director at Microsoft Research Connections. He is responsible for Microsoft's academic research partnerships related to Natural User Interface (NUI), especially device-oriented, including Cyber-Physical Systems (CPS), Robotics and Sensor Networks. In 2011 he was acting product manager for the Kinect for Windows SDK from Microsoft Research. Before joining Microsoft in 2001, he spent 13 years in the telecommunications industry in software research and development, focusing on technology transfer. Stewart has a PhD in Artificial Intelligence applied to Engineering from Loughborough University, UK. He has published a variety of papers on robotics for education, artificial intelligence, and network management as well as several patents, and co-authored a book on software engineering for artificial intelligence applications. In 2009, he co-edited The Fourth Paradigm, a book that collates visionary essays on the emerging field of data-intensive science. His recent research interests have centered on multi-device NUI, social human-robot interaction, robotics as a context for computer science education, sensor networks, and ubiquitous computing.

Lucy Vanderwende's research focuses on text understanding. She is deeply involved with developing MindNet, a method for automatically acquiring semantic information. All types of semantic information can be identified in and extracted from text. Dictionaries can provide the semantic information, for example, that a sheep is an animal; encyclopedias provide specific knowledge, for example, that Armstrong landed on the moon. Specialized data sets provide information on a given topic, for example, that Microsoft Research was founded in 1991. Common sense information can also be extracted from web-scale resources. Such information can be extracted in a variety of ways, from rule-based to completely unsupervised. Currently, Lucy's focus is to work with applications that demonstrate how the information in a knowledge resource such as MindNet can be used to improve human understanding and productivity.

Kurt Van Lehn is a Professor in the School of Computing, Informatics and Decision Science Engineering at Arizona State University. He received a Ph. D. from MIT in 1983 in Computer Science, was a post-doc at BBN and Xerox PARC, joined the faculty of Carnegie-Mellon University in 1985, moved to the University of Pittsburgh in 1990 and joined ASU in 2008. He founded and co-directed two large NSF research centers (Circle; the Pittsburgh Science of Learning Center). He has published over 125 peer-reviewed publications, is a fellow in the Cognitive Science Society, and is on the editorial boards of Cognition and Instruction, and the International Journal of Artificial Intelligence in Education. Dr. VanLehn's research focuses on applications of artificial intelligence to education. Some of his projects are, starting from the most recent ones: LAITS, a system to help student learn by authoring intelligent tutoring systems; AMT, a meta-tutoring system combined with an affective learning companion; Why2-Atlas and Cordillera, two intelligent tutoring systems that pioneered the use of natural language dialogues for science teaching and have been shown to be just as effective as expert human tutors; Pyrenees, an intelligent tutoring system that successfully caused inter-domain transfer by implicitly teaching a meta-cognitive strategy; Andes, an intelligent tutoring system for a full year of college/high school physics that improves students grades by approximate a letter grade and is in daily use around the world; and Cascade, a highly accurate cognitive model of human students learning physics that accounts for the interaction of self-explanation and analogy.

Luis von Ahn is the A. Nico Habermann Associate Professor of Computer Science at Carnegie Mellon University. He is working to develop a new area of computer science that he calls Human Computation, which aims to build systems that combine the intelligence of humans and computers to solve large-scale problems that neither can solve alone. An example of his work is reCAPTCHA, in which over one billion people -- 15% of humanity -- have helped digitize books and newspapers. Among his many honors are a MacArthur Fellowship, a Packard Fellowship, a Sloan Research Fellowship, a Microsoft New Faculty Fellowship, the ACM Grace Hopper Award, and CMU's Herbert A. Simon Award for Teaching Excellence and Alan J. Perlis Teaching Award. He has been named one of the "50 Best Brains in Science" by Discover Magazine, one of the 50 most influential people in technology by silicon.com, and one of the "Brilliant 10 Scientists" by Popular Science Magazine.

Helen J. Wang is a principal researcher interested in system security and privacy. She is also a research manager leading the security and privacy research group at Microsoft Research, Redmond. Her recent work is on building security, privacy, usability into modern client platforms. Helen received her Ph.D. degree from the Computer Science department of U. C. Berkeley in 2001 and her B.S. in Computer Science from U.T. Austin in 1995.

Dan Weld is the Thomas J. Cable / WRF Professor of Computer Science & Engineering at the University of Washington. After formative education at Phillips Academy, he received bachelor's degrees in both Computer Science and Biochemistry at Yale University in 1982. He landed a Ph.D. from the MIT Artificial Intelligence Lab in 1988, received a Presidential Young Investigator's award in 1989, an Office of Naval Research Young Investigator's award in 1990, was named AAAI Fellow in 1999 and deemed ACM Fellow in 2005. Dan was a founding editor for the Journal of AI Research, was area editor for the Journal of the ACM, guest editor for Computational Intelligence and Artificial Intelligence, and was Program Chair for AAAI-96. Dan has published two books and scads of technical papers.

Jennifer Widom is the Fletcher Jones Professor and Chair of the Computer Science Department at Stanford University. She received her Bachelor's degree from the Indiana University School of Music in 1982 and her Computer Science Ph.D. from Cornell University in 1987. She was a Research Staff Member at the IBM Almaden Research Center before joining the Stanford faculty in 1993. Her research interests span many aspects of nontraditional data management. She is an ACM Fellow and a member of the National Academy of Engineering and the American Academy of Arts & Sciences; she received the ACM SIGMOD Edgar F. Codd Innovations Award in 2007 and was a Guggenheim Fellow in 2000; she has served on a variety of program committees, advisory boards, and editorial boards.

Haoqi Zhang is a fifth year Ph.D. student in Computer Science at Harvard University. His advisor is David Parkes. He is a member of the EconCS and AI research groups. His research focuses on advancing our ability to design and study social and economic systems on the Web to promote desired participant behaviors and outcomes. Problems he studies are motivated by the transformative conditions on the Internet, notably the ability to recruit individuals with diverse expertise to join problem solving efforts via crowdsourcing and social media, and the ability to track complex individual and group behaviors over time. His research is generously supported by the NSF and NDSEG fellowships.


Last updated: 17 July 2012

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