Download AAAI 2016 Executive Council Candidates

AAAI 2016 Executive Council Candidates PRESIDENT-­‐ELECT (2) Rina Dechter Rina Dechter is a professor of Computer Science at the University of California, Irvine. She received her PhD in Computer Science at UCLA in 1985, an MS degree in Applied Mathematics from the Weizmann Institute and a B.S in Mathematics and Statistics from the Hebrew University, Jerusalem. Her research centers on computational aspects of automated reasoning and knowledge representation including search, constraint processing and probabilistic reasoning. Professor Dechter is an author of ‘Constraint Processing’ published by Morgan Kaufmann, 2003, and ‘Reasoning with Probabilistic and Deterministic Graphical Models: Exact Algorithms’ by Morgan and Claypool publishers, 2013, has co-­‐authored over 150 research papers, and has served on the editorial boards of: Artificial Intelligence, the Constraint Journal, Journal of Artificial Intelligence Research, Logical Methods in Computer Science (LMCS) and journal of Machine Learning (JLMR). She is a fellow of AAAI, a Radcliffe Fellow 2005-­‐2006, received the 2007 Association of Constraint Programming (ACP) research excellence award and is a 2013 Fellow of the ACM. She served as the Program co-­‐chair of AAAI 2002 and as a AAAI councilor, as Program Chair of CP-­‐2000 and Program co-­‐chair of UAI-­‐2006. She has been Co-­‐Editor-­‐in-­‐Chief of Artificial Intelligence, since 2011. Statement AAAI is the leading organization promoting scientific research and education in artificial intelligence. It has been my professional home for more than 30 years, and I am honored to be considered for this leadership position. If elected, I will dedicate myself to giving back and advancing the mission of an organization that has enabled me—and countless others—to collaborate with colleagues in world-­‐class conferences, workshops, and symposia. My primary goal as president will be to encourage and facilitate greater interaction among AI’s subfields. While progress made in some of these subfields is remarkable, our ultimate goal is to assemble all the pieces in a universal intelligent agent, incorporating vision, speech, natural language processing, machine learning, planning, knowledge representation and reasoning. This goal requires extensive cooperation and collaboration and can only be facilitated by having all AI’s parts interact through a unified language and under a single supportive umbrella. AAAI is the organization best positioned to facilitate that ongoing integration project, but it must be a constant priority. AAAI must also remain agile in order to handle emerging issues in a timely manner. I would strive to ensure that AAAI is the key global platform for an ongoing discussion on AI’s future, facilitated through workshops, panels, and articles in the AI magazine and elsewhere. We have a pivotal role in helping shape future research directions and in providing public education. Moreover, AAAI can and should encourage inclusion in the field, and continue to offer leadership in promoting diversity through training and education. Finally, AAAI should continue to broaden its outreach to the international community, especially in order to bring the potentially beneficial impact of AI to the emerging world. To make progress on this agenda, AAAI must be sustained and strengthened by a growing membership. I recognize and embrace the fact that an essential focus of AAAI leadership must be to increase membership by encouraging young researchers to join, in the legacy communities of North America and Europe—and even more so in Asia and the Middle East. Thank you for your consideration. Yolanda Gil Yolanda Gil is Director of Knowledge Technologies at the Information Sciences Institute of the University of Southern California, and Research Professor in Computer Science. She received her M.S. and Ph. D. degrees in Computer Science from Carnegie Mellon University. Her research is in intelligent user interfaces, knowledge-­‐rich collaborative problem solving, and the semantic web. A recent focus is scientific data analysis through semantic workflows. She initiated and chaired the W3C Provenance Group that led to a community standard in this area. She served in the Advisory Committee of the Computer Science and Engineering Directorate of the NSF. She is Chair of ACM SIGAI, the Association for Computing Machinery's Special Interest Group on Artificial Intelligence, and is on the Editorial Board of the Artificial Intelligence journal. She was elected Fellow of AAAI in 2012. Statement AAAI is a fantastic organization that greatly benefits our field. I understand how it serves our community from many perspectives, having started as a student volunteer and then author, workshop and symposium organizer, AAAI program co-­‐chair, and finally councilor and AAAI conference committee chair. I have always been impressed by the enthusiasm and creativity of my colleagues in making AAAI a vibrant community. Looking forward, I believe AAAI needs to have a greater presence in the broader science ecosystem and propose here some possibilities. First, I believe AAAI needs to join science initiatives in reproducibility and digital scholarship. From ACM to AAAS, many scientific organizations and conferences are improving the accessibility and persistence of digital research products beyond published articles. Science communities are recommending repositories and best practices for sharing data, software, workflows, and other resources in ways that promote reusability and author credit. AAAI must create best practices for our field, and in doing so it will make our research more visible in other communities. Second, AAAI could do more to promote younger AI researchers. We need to instate a Dissertation Award, if possible in cooperation with ACM SIGAI to raise its visibility in the broader CS community. We should include an Early Career Researcher Keynote at AAAI, and profile young researchers in AI Magazine. We should have a registry of AI thesis abstracts to promote the important ideas that PhD students contribute to our field. I have been a judge for AAAI at the ISEF high school science competition, and have seen that two thirds of their CS projects are actually in AI. One student reported that his hobby is reading AI papers from the 60s. There is tremendous interest that we need to capitalize on to attract the best talent to our field. Finally, I think that we can do more to give AI higher visibility and stronger ties with the CS and science community. AAAI could work with ACM, AAAS, and other organizations to promote AI and involve AI researchers in the broader discussions that are taking place about the future of intelligent systems, autonomy, computer-­‐mediated interactions, and big data in the broader science, government, and social context. EXECUTIVE COUNCILOR (8) Blai Bonet Blai Bonet is a professor in the computer science department at Universidad Simon Bolivar, Venezuela. He received his Ph.D. in computer science from the University of California, Los Angeles. His research are in the areas of automated planning, heuristic search and knowledge representation. He has received six best paper awards or honorable mentions, including the 2009 and 2014 ICAPS Influential Paper Awards. Blai Bonet is a co-­‐author (with Hector Geffner) of the book titled "A Concise Introduction to Models and Methods for Automated Planning." Blai Bonet is an associate editor of Artificial Intelligence and the Journal of Artificial Intelligence Research, and served as conference co-­‐chair of ICAPS-­‐12 and program co-­‐chair of AAAI-­‐15. Statement Fragmentation and internationalization are the biggest challenges for AAAI over the next few years. The high success of fragmented areas such a ML, NLP, Vision and robotics is affecting traditional AI core areas in many respects, from insufficiency of funds and difficulty to attract the best students to lack of incentives and loss of researchers. On the other hand, the sudden growth of conferences like NIPS and AAMAS, and IJCAI's change of schedule put more pressure on AAAI on how to sustain and even increase its status as the main conference in AI, worldwide. Fortunately, we have seen in the two last AAAI conferences very good signs and opportunities that need to be leveraged for handling these challenges. We saw an incredible increase on the number of submissions and international participants, and on the number of submissions in the fragmented areas. So, AAAI is healthy and strong as an organization but it needs to prepare itself for the times ahead. Discussions on issues such as international representation inside the different committees, internationalization of conferences, and joint ventures with fragmented areas may prove instrumental for making the right decisions. J. Christopher Beck Chris Beck (PhD University of Toronto, 1999) is a Professor in the Department of Mechanical & Industrial Engineering at the University of Toronto. Prior to (re)joining UofT, he was a Staff Scientist at the Cork Constraint Computation Centre, Ireland and a Senior Scientist at ILOG, France. He has been conducting research since 1992 in both AI and Operations Research, focusing on planning and scheduling, constraint programming, and optimization. He has over 100 peer-­‐reviewed publications and has given over 100 scholarly presentations in 17 countries. Chris is the President of the Executive Council for the International Conference on Automated Planning and Scheduling and Associate Editor or member of the Editorial Board for the Journal of Artificial Intelligence Research (since 2010), Constraints (2008-­‐2013), Journal of Scheduling (2005-­‐2012), and The Knowledge Engineering Review (2005-­‐2015). He has served as the Program/Conference Chair/Co-­‐chair of CPAIOR (2006, 2011), ICAPS (2008), and SARA (2009) and will be the Program Chair for CP2017. Statement While AI becomes increasingly a part of our lives and as society raises important concerns about its implications, AI researchers are fragmented by geography and sub-­‐discipline and lack a unified voice in the media, on funding bodies, and in larger societal discussions. If AAAI wants to be (or be part of) a larger, international collective, I believe that it needs to re-­‐examine its goals and develop paths toward them. For example, we should consider introducing sub-­‐discipline "societies" within AAAI and, more radically, making the AAAI conference a non-­‐peer-­‐reviewed, abstract-­‐based conference focusing on bringing together AI researchers, practitioners, teachers, users, and enthusiasts. Such changes would multiply the AAAI membership, attract more industrial exhibitors, make the conference the hub of academic and industrial job interviews, and counter our traditional fragmentation. Ariel Felner Ariel Felner is a Professor at Ben-­‐Gurion University. His research regards all aspects of Heuristic Search with specific interest in historical and pedagogical aspects of search algorithms. He published 100 peer-­‐reviewed papers in various AI venues. He won the AAAI-­‐2016 Outstanding Paper Award, the 2007 IJCAI-­‐JAIR Best Paper award, the SoCS-­‐2012 and SoCS-­‐2014 Best-­‐paper award, and the AAAI-­‐2013 outstanding SPC member. He serves as the chair of the Israeli Association for AI and on the council of SoCS. He is on the editorial board of AIJ and JAAMAS. He served as PC/SPC/Area-­‐chair in numerous AI conferences (AAAI/IJCAI/AAMAS/ICAPS/ECAI) and as the chair of conferences (SoCS-­‐2010, SoCS-­‐2012) and tracks (AAAI-­‐2015 SMT, AAAI-­‐2013 Late-­‐
breaking paper track, ICAPS-­‐2016 workshops track). Statement A great challenge for the rapidly growing AI field is to effectively disseminate knowledge between researchers from different subareas. Very often researchers have important knowledge and experience needed by colleagues but the lack of communication prevents them from collaborating. For example, my colleague from NLP was desperately developing a new search algorithm which was already deeply studied in the heuristic search literature. Luckily we joined together and developed a state-­‐of-­‐the-­‐art method for textual entailment in NLP. But, many times relevant researchers lack the abilities to find each other. To address this, the AI community, and in particular AAAI, need to actively facilitate better acquaintance among researchers from different subareas and to help researchers become more knowledgeable on concepts and developments in other subareas. A number of directions can be taken to address this such as: (1) Establish summer school programs for researchers (students and seniors alike). (2) Encourage/invite deeper tutorials on basics and recent developments in the various subareas. (3) Improve current events and add more events to the conference that will directly acquaintance researchers and research fields to the general attendees. Sabine Hauert Sabine Hauert is Assistant Professor at the University of Bristol in the UK and President and Co-­‐
founder of Robohub.org, a non-­‐profit dedicated to connecting the robotics and AI community to the public. Robohub has helped thousands of experts in robotics and AI communicate about their work through podcasts, articles, and videos, that reach over a million views each year. As an expert in science communication with 10 years of experience, Sabine is often invited to discuss the future of AI, including in the journal Nature, at the European Parliament, and as a member of the Royal Society's Working Group on Machine Learning. Sabine’s research focuses in designing swarms that work in large numbers (>1000), and at small scales (<1 cm). Swarm strategies are either inspired from nature or are automatically discovered using machine learning and crowdsourcing. Before joining the University of Bristol, Sabine engineered swarms of nanoparticles for cancer treatment at MIT as a Human Frontier Science Program Cross-­‐Disciplinary Fellow, and deployed swarms of flying robots at EPFL. Statement Artificial Intelligence will improve the way we work, live, and innovate. By being cross-­‐
disciplinary, AI researchers are enabling breakthroughs in areas ranging from medicine to robotics. Unfortunately, misinformation and hype about artificial intelligence is driving public perception. The public includes taxpayers, policy-­‐makers, investors and those who could benefit from the technology. High-­‐quality information is therefore key, and experts should be delivering it. This requires training in social media, support, and incentives for experts, and a common online platform we can use to expand our reach. AAAI is ideally positioned to deliver this vision and raise the quality of the discussion around AI. The AAAI Video Competition is an excellent example of this. During the past three years I’ve served as chair, or co-­‐chair, submitted videos have been viewed over one million times. This direct dialog with the public will also allow our community to understand what technology has the most potential to benefit society. Mausam Mausam is an Associate Professor at Indian Institute of Technology, Delhi. Earlier he was a Research Assistant Professor at University of Washington, Seattle from 2007 to 2013. He received his PhD from University of Washington in 2007 and a Bachelor of Technology from IIT Delhi in 2001. Mausam's research interests span a variety of sub-­‐fields within AI, including planning under uncertainty, natural language processing, probabilistic reasoning, machine learning, and AI applications to crowdsourcing. He is an author on scores of conference and journal publications in AI, and has co-­‐authored a book on the use of MDPs for AI planning. Mausam was awarded the AAAI Senior Member status at AAAI 2015. He received HCOMP best paper award in 2013, and an ICAPS best paper nomination in 2010. He is an associate editor for JAIR, and has served on numerous conference committees, NSF panels and conference award committees. Statement These are unprecedented times for the field of artificial intelligence. Last year, NIPS had over 3,000 attendees; the number of AAAI and IJCAI submissions is consistently breaking previous records with every offering; and AI is featured regularly in mainstream media. On the other hand, the popular rhetoric on AI is increasingly filled with fear -­‐-­‐ signature campaign against intelligent weapons, the dangers due to widespread employment loss, and loss of personal privacy have begin to substantially tarnish AI’s popular image. AAAI must take a leadership role to highlight the value ofAI technologies for mankind at large. It must mediate the public debate on both AI and policy. It must encourage ethics research to pre-­‐
empt any potential future dangers. AAAI must work towards bridging the gap between technology and its real-­‐world deployment, while keeping various human factors in focus. Additionally, AAAI must also take a substantial role in integrating researchers from emerging regions. This will not only spread AI's influence, but will also enable access to local societal problems where AI technology could be impactful. Michela Milano Michela Milano is full professor of computer science at DISI – University of Bologna since November 2016. Her research activity concerns decision support systems based on Constraint Programming and its integration with Mathematical programming. In this field, she has achieved international visibility. She is Editor in Chief of the Constraints Journal, Area Editor of Constraint Programming Letters in the area of Search and Area Editor of INFORMS Journal on Computing in the area Logic, Constraint and Optimization. She is author of more than 120 papers on peer reviewed international conferences and journals. She has been program chair of CPAIOR 2005, CPAIOR 2010, CP2012 and CompSust2012. She is member of the ECCAI board (now EurAI), of the Steering Committee of CPAIOR. She has been elected member of the Executive Committee of the Association of Constraint Programming, and of the Executive committee of the Italian Association of AI. She has been the coordinator of the FP7 EU project ePolicy, Engineering the Policy Making Life Cycle, 2011-­‐2014 and partner of the FP7 EU project COLOMBO, Cooperative Self-­‐Organizing System for low Carbon Mobility at low Penetration Rates, 2012-­‐2015, and of EU-­‐
FP7-­‐SMARTCITY DAREED: Decision Advisor for Energy Efficient Districts, 2013-­‐2016. In 2016 she has been the recipient of the Google Faculty Research Award on the use of deep network in combinatorial optimization and in 2015 won the best Blue Sky Research Paper award at AAAI 2015. Statement Artificial intelligence has witnessed incredible advancements in the last years and for the first time AI techniques are able to face social, economic and environmental challenges. In these contexts complex problems arise, involving socio-­‐technical systems often relying on big data sets coming from sensors, social networks, smartphones and crowd-­‐sourced information. Modeling such complex systems requires interdisciplinary approaches, merging natural language processing, robotics, knowledge representation, advanced reasoning techniques, machine learning, human-­‐machine interaction and computational social choice. Bringing together such a number of techniques would have the potential to reduce the fragmentation of AI and puts it at the frontier of socio-­‐technical systems planning, management and optimization. AAAI, EurAI and all AI associations would play an important role in this scenario by organizing initiatives and events (possibly open to the public at large) to promote the role of AI in supporting our society, improving our quality of life and reducing the fear that AI could steal jobs and threat our world. Matthew E. Taylor Matthew E. Taylor is an assistant professor in the School of Electrical Engineering and Computer Science at Washington State University and holds the Allred Distinguished Professorship in Artificial Intelligence. He is currently on the editorial board for JAIR, is an associate editor for JAAMAS, and serves on the IFAAMAS board of directors. He has been a member of AAAI for over ten years, has been the AAAI Symposium Series chair, and served on AAAI conference organizing committees. Statement Matt’s two goals as AAAI Councilor would be to 1) improve the public’s understanding and perception of AI and 2) strengthen connections between AAAI and sub-­‐fields of AI. In support of the first goal, I propose we identify AI researchers willing to speak with reporters, along with their areas of expertise. Such a database will allow AAAI to easily serve as a clearing house for journalists and help ensure the popular press has access to accurate scientific information. Additionally, I will work to expand existing outreach efforts, such as aitopics.org and the AAAI Open House. In support of the second goal, I will work to strengthen the ties between AAAI and other sub-­‐disciplines, such as agents, NLP, robotics, and vision. This can be accomplished by supporting programs like the robotics fellowship and robotics exhibition at the AAAI conference, and looking for ways to co-­‐locate related conferences (e.g., IJCAI-­‐18’s co-­‐location with multiple AI conferences in Stockholm). Qiang Yang Qiang Yang is the chair professor and department head at the Computer Science and Engineering Department, Hong Kong University of Science and Technology in Hong Kong. He is also the director of WeChat-­‐HKUST Joint Lab on Artificial Intelligence (WHAT Lab), director of the Big Data Institute at HKUST, Vice Chair of Chinese Artificial Intelligence Society, Trustee of IJCAI as well as the founding editor in chief of ACM TIST and Editor in Chief of the IEEE Transactions on Big Data. Qiang Yang was also the founding head of Huawei Noah’s Ark Lab. He had taught at University of Waterloo and Simon Fraser University prior to joining HKUST in 2001. He published three books, Intelligence Planning – A decomposition and Abstraction Based Approach, Constraint-­‐based Design Recovery for Software Reengineering : Theory and Experiments and Crafting Your Research Future: A Guide to Successful Master’s and PH.D. Degrees in Science & Engineering. His expertise spans artificial intelligence transfer learning, planning and case-­‐based reasoning. Qiang Yang earned his PHD in computer science from the University of Maryland in 1989. He is a fellow of AAAI, IEEE and AAAS. Statement One of the critical issues facing the AI community is to effectively communicate the science of AI to the public when many misunderstood AI as science fiction. With the increasing success of AI in machine learning, robotics and many other fields, there is an increasing need to address the ‘educational’ issue of AI for different crowds, ranging from various industries, investment communities, students who are future AI researchers as well as the general public. It is important to manage a well-­‐placed balance on the expectation of what AI can and cannot do. It is also important to guide AI research towards higher relevance to people’s lives. Another important issue to involve researchers, practitioners and students from different cultural and demographic background in serving the AI community, to truly understand their needs and address the current imbalance in community organization. I look forward to a more healthy and truly global representation of the AI community in our activities.