sábado, 27 de julio de 2013

AI's 10 to Watch

ORIGINAL: IEEE

AI 10 to Watch 2013
Every two years, IEEE Intelligent Systems acknowledges and celebrates 10 young stars in the field of AI as "AI's 10 to Watch." These accomplished researchers have all completed their doctoral work in the past five years. Despite being relatively junior in their career, each one has made impressive research contributions and had an impact in the literature — and in some cases, in real-world applications as well. Nominations in all subfields of AI were sought from a wide range of senior AI researchers. A short list of top candidates was voted on by the award committee, and then the decisions were finalized with the entire advisory and editorial boards of IEEE Intelligent Systems. I would like to take this opportunity to thank two past editors-in-chief of IEEE Intelligent Systems, Jim Hendler and Fei-Yue Wang, who served as the co-chairs of the AI's 10 to Watch award committee and did a great job managing the nomination and selection process. The group nominated this year was particularly strong. It has been a struggle to choose the best of the best. In the end, the top 10 surfaced with unanimous support from the advisory and editorial boards. We're particularly pleased about the diversity of the winning group. It's safe to say that everyone involved in the selection process has been very proud of these young stars' contributions, of what AI as a community can offer, and how bright the future of AI can be. We're sure that young AI students and researchers will find inspiration from these young stars, and that the AI community will look forward to their continued excellence and sustained impact. Congratulations again to our young colleagues for winning this special recognition! — Daniel Zeng Stay tuned for a more comprehensive description of each person's research focus, coming soon.

The 10  
Nora Ayanian 
Finale Doshi-Velez 
Heng Ji 
Brad Knox
Honglak Lee 
Nina Narodytska 
Ariel Procaccia 
Stefanie Tellex
Jun Zhu 
Aviv Zohar

Automatic Multirobot Coordination

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Nora Ayanian

Nora Ayanian is a postdoctoral associate in the Distributed Robotics Lab at the Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology. She will join the University of Southern California as a WiSE Gabilan Assistant Professor of Computer Science in 2013. Ayanian has a PhD in mechanical engineering from the University of Pennsylvania. She received a graduate fellowship from the National Science Foundation (NSF) in 2005 and won Best Student Paper in the International Conference of Robotics and Automation in 2008.



Defining Diseases with Data

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Finale Doshi-Velez

Finale Doshi-Velez is an NSF postdoctoral fellow at the Center for Biomedical Informatics at Harvard Medical School. Her research focuses on developing novel probabilistic modeling techniques to create clinical diagnostic tools and generate scientific research hypotheses in medicine. Doshi-Velez has a PhD in computer science from MIT. She is a 2007 Marshall Scholar and was a Trinity Prince of Wales Research Student at the University of Cambridge.


Extracting Information from Heterogeneous Data

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Heng Ji

Heng Ji is an associate professor in the computer science department at Queens College and a doctoral faculty member in the Departments of Computer Science and Linguistics at the Graduate Center of City University of New York. In Fall 2013 she is joining Rensselaer Polytechnic Institute as an associate professor and the Edward G. Hamilton Development Chair in Computer Science. Her research interests focus on natural language processing, especially on cross-source information extraction and knowledge base population. Ji has a PhD in computer science from New York University. She received a Google Research Award in 2009, an NSF CAREER award in 2010, and the Sloan Junior Faculty award and IBM Watson Faculty award in 2012.


Learning through Human Interaction

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Brad Knox

Brad Knox is a postdoctoral researcher at the MIT Media Lab. His research interests span machine learning, human-robot interaction, and psychology, especially machine-learning algorithms that learn through human interaction. Knox has a PhD in computer science from the University of Texas at Austin. He won the Pragnesh Jay Modi Best Student Paper Award at AAMAS in 2010, and his dissertation, "Learning from Human-Generated Reward," received the Bert Kay Dissertation Award from his doctoral department and was runner-up for the Victor Lesser Distinguished Dissertation Award.


Honglak Lee
Learning Representations from Data

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Honglak Lee

Honglak Lee is an assistant professor of computer science and engineering at the University of Michigan, Ann Arbor. His research interests lie in machine learning, which spans representation learning, unsupervised and semisupervised learning, transfer learning, graphical models, and optimization. Lee has a PhD in computer science from Stanford. He received best paper awards at ICML and CEAS, and the Google Faculty Research Award. Lee has served as an area chair for ICML 2013 and as a guest editor of the IEEE Transactions on Pattern Analysis and Machine Intelligence special issue on learning deep architectures.


Nina Narodytska
Optimization, Social Choice, and Game Theory

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Nina Narodytska

Nina Narodytska is a postdoctoral research fellow at the University of Toronto, Canada. She's also a visiting researcher in the School of Computer Science and Engineering at the University of New South Wales. Narodytska has a PhD in computer science from the University of New South Wales and NICTA. She received an Outstanding Paper Award for AAAI 2011 and an outstanding program committee member award at the Australasian Joint Conference on Artificial Intelligence 2012.


Ariel Procaccia
AI and Economics: The Dynamic Duo

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Ariel Procaccia

Ariel Procaccia is an assistant professor in the computer science department at Carnegie Mellon University. Procaccia has a PhD in computer science from the Hebrew University of Jerusalem, and was subsequently a postdoc at Microsoft and Harvard. He is a recipient of the Victor Lesser Distinguished Dissertation Award (2009), a Rothschild postdoctoral fellowship (2009), an inaugural Yahoo Academic Career Enhancement Award (2011), and a TARK best paper award (2011). He is currently the editor of ACM SIGecom Exchanges and an associate editor of the Journal of AI Research (JAIR) and Autonomous Agents and Multi-Agent Systems (JAAMAS).


Stefanie Tellex
Talking to Robots

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Stefanie Tellex

Stefanie Tellex will join the computer science department at Brown University as an assistant professor in September 2013. She is currently a research scientist at the MIT Computer Science and Artificial Intelligence Laboratory. Her research interests include probabilistic graphical models, human-robot interaction, and grounded language understanding. Tellex has a PhD from the MIT Media Lab for her work on models for the meanings of spatial prepositions and motion verbs.


Jun Zhu
Bayesian AI

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Jun Zhu

Jun Zhu is an associate professor in the Department of Computer Science and Technology at Tsinghua University. His research focuses on developing machine-learning methods to understand complex scientific and engineering data. Jun has a PhD in computer science from Tsinghua University. He's an active member of the research community, serving as an area chair for Advances in Neural Information Processing Systems 2013 and a local chair for International Conference on Machine Learning 2014. His dissertation received the China Computer Federation Distinguished Dissertation Award, which recognizes the best PhD in China in computer science.


Aviv Zohar
Incentives in Multiagent Systems

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Aviv Zohar

Aviv Zohar is a senior lecturer at the School of Engineering and Computer Science in the Hebrew University of Jerusalem and he is a Golda Meir Fellow. His postdoctoral work was at Microsoft Research. Zohar has a PhD in computer science from the Hebrew University. His other honors include an award of excellence from the Israeli Knesset and the committee of university heads, a Leibniz scholarship during his PhD studies, and a scholarship from the Wolf Foundation during his MSc.

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