Visions of AI Futures
A Workshop on Artificial Intelligence (AI)
Co-organised by AI Singapore and NUS Computing
For a long time, researchers did not make much progress in creating general and capable artificial intelligence agents. The field fragmented, and researchers specialised in subareas involving perception, reasoning, learning, representation, and related application areas. Recent progress in techniques, catalysed by the availability of large amounts of data and exponentially increasing computational resources, has brought astounding successes. Autonomous vehicles can now drive alongside humans in cities. An artificial intelligence programme has finally beaten the Go world champion. Computers can now match or exceed human performance in recognising faces and speech, and even translate languages well enough to be useful.
Given the progress, it is now timely to take a more unified view of AI. At this workshop, researchers across various AI subareas will share their research visions and the perspectives from their fields, offering participants insights into some of the impediments to achieving more capable AI systems.
The programme features talks by global leaders and experts in various AI areas, including members of AI Singapore’s International Advisory Panel.
|Date:||26 May, 2018|
|Time:||0900hrs – 1545hrs
(Registration begins at 0815hrs) – Morning/ Full Day
(Registration begins at 1215hrs) – Afternoon Session
|Venue:||Seminar Room 1
Level 2, COM1
NUS School of Computing
13 Computing Drive
what to expect?
LIGHTNING TalkS A
LIGHTNING TalkS B
Gim Hee Lee (NUS)
Dr Lee is currently an Assistant Professor at the Department of Computer Science, National University of Singapore (NUS). He was a researcher at Mitsubishi Electric Research Laboratories (MERL), USA from June 2014 to July 2015. Prior to MERL, Dr Lee did his PhD in Computer Science at ETH Zurich from January 2009 to March 2014. He received his B.Eng with first class honors and M.Eng degrees from the Department of Mechanical Engineering, NUS in June 2005 and February 2008 respectively. Dr Lee also worked at DSO National Laboratories in Singapore as a Member of Technical Staff from August 2007 to December 2008.
KULDEEP MEEL (NUS)
Kuldeep Meel is an Assistant Professor of Computer Science in School of Computing at the National University of Singapore. He received his Ph.D. (2017) and M.S. (2014) degree in Computer Science (Artificial Intelligence and Formal Methods) from Rice University. He holds B. Tech (with Honors) degree (2012) in Computer Science and Engineering from Indian Institute of Technology, Bombay. His research interests lie at the intersection of Artificial Intelligence and Formal Methods. Meel has co-presented tutorials at top-tier AI conferences, UAI 2016 and AAAI 2017. His work received the 2018 Ralph Budd Award for Best PhD Thesis in Engineering, 2014 Outstanding Masters Thesis Award from Vienna Center of Logic and Algorithms and Best Student Paper Award at CP 2015. He received the IBM Ph.D. Fellowship and the 2016-17 Lodieska Stockbridge Vaughn Fellowship for his work on constrained sampling and counting.
Shaowei Lin (NUS)
Dr Lin is an Assistant Professor (Engineering Systems and Design Pillar) of Singapore University of Technology and Design (SUTD). He received his Ph.D. in Mathematics under Bernd Sturmfels in 2011 from the University of California, Berkeley, where he analysed singularities in statistical models over large data sets through the lens of modern algebraic geometry. This work was continued at Stanford University in a one-year DARPA postdoctoral collaboration with Andrew Ng’s lab to explore mathematical challenges in deep learning. In 2012, Dr Lin returned to Singapore to join the Institute for Infocomm Research (A*STAR) where he started the Sense-making Group in the Sense and Sense-abilities (S&S) programme. The group focused on exploiting machine learning techniques in sensor networks to create resource-efficient algorithms that exhibit higher-order intelligence. Before joining SUTD, he oversaw deep science activities in S&S as the Deputy Head for Research. Beyond basic research, he worked closely with government and industry partners such as NEA, HDB and Sky Greens in several urban projects. These projects received both local and international recognition such as the MTI Borderless Silver Award 2015 and the World Smart Cities Award Finalist 2014. He was also appointed by the Science and Engineering Research Council (SERC) in A*STAR to lead a multi-agency panel of experts in developing future roadmaps for Data-Driven Research and Future Computing Paradigms.
Sinno Pan (NTU)
Dr Sinno Jialin Pan is a Nanyang Assistant Professor with the School of Computer Science and Engineering at Nanyang Technological University (NTU), Singapore. He is also a Cluster Deputy Director of Data Science and AI Data Science & Artificial Intelligence Research Centre at NTU. Prior to joining NTU, he was a scientist and Lab Head of text analytics with the Data Analytics Department, Institute for Infocomm Research, Singapore. He received his Ph.D. degree in computer science from the Hong Kong University of Science and Technology (HKUST) in 2011. His research interests include transfer learning, and its applications to wireless sensor networks, natural language processing, computer vision, and software engineering. His research in transfer learning has resulted in 50+ top-tier international referred publications, and received more than 7,300 citations according to Google Scholar.
Bo An (NTU)
Bo An is an associate professor with the School of Computer Science and Engineering, Nanyang Technological University, Singapore. He received the Ph.D degree in Computer Science from the University of Massachusetts, Amherst in 2011. His current research interests include artificial intelligence, multiagent systems, game theory, and optimization. Dr. An was the recipient of the 2010 IFAAMAS Victor Lesser Distinguished Dissertation Award, an Operational Excellence Award from the Commander, First Coast Guard District of the United States, the Best Innovative Application Paper Award at AAMAS’12, the 2012 INFORMS Daniel H. Wagner Prize for Excellence in Operations Research Practice, and the Innovative Application Award at IAAI’16. He was invited to give Early Career Spotlight talk at IJCAI’17. He led the team HogRider which won the 2017 Microsoft Collaborative AI Challenge. He was named to IEEE Intelligent Systems’ “AI’s 10 to Watch” list for 2018. He is a member of the editorial board of JAIR and the Associate Editor of JAAMAS. He was elected to the board of directors of IFAAMAS.
Hady W. Lauw (SMU)
Hady W. Lauw is currently Assistant Professor of Information Systems at Singapore Management University, as well as NRF Fellow of the Singapore National Research Foundation. Formerly, he served as postdoctoral researcher at Microsoft Research in Silicon Valley, as well as scientist at A*STAR’s Institute for Infocomm Research. He received his PhD from Nanyang Technological University on A*STAR Graduate Scholarship. At SMU, he leads the Preferred.AI research project, whose research activities span data mining and machine learning, focusing on preference analytics and recommender systems. He is also active in the academic community, currently serving as the Chair of the Singapore Chapter of ACM SIGKDD. More information may be found at http://www.hadylauw.com
HAROLD SOH (NUS)
Dr Soh is currently an Assistant Professor at the Department of Computer Science at the National University of Singapore. His research interests are broadly in human-AI interaction, machine learning, and robotics. He is particularly fascinated by collaborative human-machine intelligent systems. Previously, he has worked on robots that help children get around, continuous robot/machine learning, controlling disease spread, and self-driving cars. He was a graduate student in at the Personal Robotics Lab at Imperial College London under the supervision of Yiannis Demiris where he worked on online learning and model building for assistive robotics. As part of his PhD, he designed and built two smart robotic wheelchairs that help young children explore their environment safely. He was then awarded a SMART Postdoctoral Scholar fellowship to pursue independent research at MIT‘s SMART Center, where he was mentored by Emilio Frazzoli. He did a second postdoctoral fellowship at the Cognitive Engineering Lab (CEL) and Data-Driven Decision Making (D3M) lab at the University of Toronto, with Greg Jamieson and Scott Sanner.
Hwee Tou Ng (NUS)
Hwee Tou Ng is Provost’s Chair Professor of Computer Science at the National University of Singapore and a Senior Faculty Member at the NUS Graduate School for Integrative Sciences and Engineering. He received a PhD in Computer Science from the University of Texas at Austin, USA. His research focuses on natural language processing and information retrieval. He is a Fellow of the Association for Computational Linguistics (ACL).
Jiashi Feng (NUS)
Dr Jiashi Feng is currently an assistant Professor in the department of electrical and computer engineering in the National University of Singapore. He got his B.E. degree from University of Science and Technology, China in 2007 and Ph.D. degree from National University of Singapore in 2014. He was a postdoc researcher at University of California from 2014 to 2015. His current research interest focus on machine learning and computer vision techniques for large-scale data analysis. Specifically, he has done work in object recognition, deep learning, machine learning, high-dimensional statistics and big data analysis.
Jiewen Wu (I2r)
Wu Jiewen is a scientist at the A*STAR Artificial Intelligence Initiative and the Institute for InfoComm Research. Before joining A*STAR, he worked as a leading research scientist at Accenture AI Labs in Ireland and as a researcher at IBM Research, Ireland. In his previous roles, he used AI techniques to develop intelligent solutions to real-world problems across a variety of domains, including transportation, health care, and corporate finance, among others. In A*STAR, his main research interests lie in explainable AI, which aims to make AI systems more human-centric.
Alexandre thiery (nus)
Dr Alexandre Thiery, co-founder of Abyss Processing, is an Assistant Professor in the department of Statistics and Applied Probability at the National University of Singapore (NUS). Dr Thiery was educated in theoretical mathematics at the Ecole Normale Superieure (ENS) of Paris and recently shifted to more applied areas of research such as Data-Assimilation and Monte-Carlo methods. Dr Thiery is recognized as a leader in the field of Bayesian statistics and machine learning.
Akshat kumar (SMU)
Dr Kumar is Assistant Professor of Information Systems at the Singapore Management University (SMU). He received his Masters and Ph.D. in computer science from University of Massachusetts Amherst in 2012 advised by Prof. Shlomo Zilberstein. Far back in time, He received his Bachelors in Computer Science and Engineering from Indian Institute of Technology, Guwahati in 2005. He has worked as a research scientist at IBM Research India in the Business Analytics and Mathematical Sciences Dept. from Oct 2012 till Feb. 2014. Dr Kumar’s research interests lie at the intersection of AI and ML with a focus on multiagent decision making and reinforcement learning. He is particularly excited by the application of large scale multiagent planning and learning for optimizing urban systems including land and maritime transportation.
VAIBHAV RAJAN (nus)
Dr Vaibhav Rajan is an Assistant Professor in the Department of Information Systems and Analytics at the School of Computing, National University of Singapore (NUS). Earlier, he was a Senior Research Scientist at Xerox Research Centre India where he led a project on Clinical Decision Support Systems for over 4 years. He has also worked as a consultant at Hewlett-Packard Labs India and as Chief Data Scientist at Videoken (an education technology startup). Dr Vaibhav Rajan received his PhD and Master’s degrees in Computer Science from the Swiss Federal Institute of Technology at Lausanne (EPFL), Switzerland in 2012 and 2008 respectively and his Bachelor’s degree in Computer Science from Birla Institute of Technology and Science (BITS), Pilani, India in 2004. His research interests include Machine Learning, Algorithm Design and their applications, primarily in Healthcare and Bioinformatics. He is a recipient of the ERS IASC Young Researchers Award 2014 given by European Regional Section (ERS) of the International Association for Statistical Computing (IASC).
Reza shokri (nus)
Reza Shokri is an Assistant Professor in the Department of Computer Science, National University of Singapore (NUS). He obtained his PhD from EPFL, and was a researcher at Cornell University, prior to joining NUS. His research is mainly focused on data and computational privacy.
leslie p. kaelbling (mit)
Leslie Pack Kaelbling is Professor of Computer Science and Engineering at the Computer Science and Artificial Intelligence Laboratory (CSAIL) at the Massachusetts Institute of Technology. She has made research contributions to decision-making under uncertainty, learning, and sensing with applications to robotics, with a particular focus on reinforcement learning and planning in partially observable domains. She holds an A.B in Philosophy and a Ph.D. in Computer Science from Stanford University, and has had research positions at SRI International and Teleos Research and a faculty position at Brown University. She is the recipient of the US National Science Foundation Presidential Faculty Fellowship, the IJCAI Computers and Thought Award, and several teaching prizes and has been elected a fellow of the AAAI. She was the founder and editor-in-chief of the Journal of Machine Learning Research.
ming lei (baidu)
Mr Ming Lei is one of the seven co-founders of Baidu. He served as the chief architect and led the team that developed Baidu’s search engine. Mr Lei founded Kuwo in 2005, serving as CEO and chairman. Kuwo later merged with Kugou and QQ Music to form Tencent Music Entertainment Inc. Mr Lei is involved in AI related research, incubation and investment. He is the director of the AI Innovation Center in Peking University, where he teaches “AI Frontier and Industry Trends” and works on bridging AI research and industry demand. He is also chairman of Happy Intelligence, a robot company for children, and Deep Wise, a AI medical diagnosis company. Mr Lei has invested in several AI related start-ups, including New AI Era (新智元), an AI media company in China; and BigTiger, an AI education company in Silicon Valley.
MICHAEL WOOLDRIDGE (OXFORD)
Professor Michael Wooldridge is head of the Department of Computer Science at the University of Oxford, and a senior research fellow at Hertford College. He joined Oxford on 1 June 2012. Before this he was a professor of computer science at the University of Liverpool for twelve years. His research interests are in the use of formal techniques of one kind or another for reasoning about multiagent systems. His current research is at the intersection of logic, computational complexity, and game theory.
satoshi matsuoka (riken)
In April 2018, Satoshi Matsuoka became director of Riken CCS, the top-tier HPC centre in Japan that currently hosts the K computer and where the next generation post-K machine is being developed. Since 2000, he has been full professor at the Global Scientific Information and Computing Center, a Japanese supercomputing centre hosted by the Tokyo Institute of Technology. In 2016, he became a fellow at the AI Research Center, AIST, the largest national lab in Japan. In 2017, he served as head of the joint Open Innovation Lab on Real World Big Data Computing between the two institutions. He was leader of the TSUBAME series of supercomputers and won the 2014 IEEE-CS Sidney Fernbach Memorial Award, the highest honour in the field of HPC. He has an appointment as a professor in the Department of Mathematical and Computing Sciences in the Tokyo Institute of Technology. His research spans the three institutions in HPC and scalable big data and AI. He is also involved in several important roles in research in Singapore, including being on the steering board of NSCC, an advisory consultancy for A*CRC-A*STAR, as well as being an advisory board member for AI Singapore.
Co-founder of Baidu & Director of AI Innovation Center, Peking University
Industry opportunities in THE ai era
Artificial intelligence (AI) is an extremely popular subject in academia and industry.
Have you ever wondered what the root cause is of the wave of interest in AI? What about the impact of AI on industry?
This talk will focus on AI and industry. Analyzing the relationship between AI performance and human skills will enable a new breakthrough on the use of AI in industry. How to discover emerging AI industries and catch the opportunities they present will also be discussed.
Director of Riken CCS
Infrastructures for hpc and AI CONVERGENCE
With the rise of big data and AI as high-performance workloads on supercomputers, we must accommodate them so that traditional simulation-based HPC and BD/AI converge. The convergence infrastructures are as important as algorithms and applications, as with traditional HPCs. The TSUBAME3 supercomputer at the Tokyo Institute of Technology went online in August 2017 becoming the greenest supercomputer in the world with a Green 500 ranking of 14.11 GFlops/W. TSUBAME3 allows for HPC to BD/AI convergence, with significant scalable horizontal bandwidth, support for deep memory hierarchy and capacity, and high flops in low precision arithmetic for deep learning. TSUBAME3’s technologies will be commoditised to construct one of the world’s largest BD/AI focused and “open-source” cloud infrastructures, called ABCI (AI-Based Bridging Cloud Infrastructure), which will be online in Spring 2018. Its open architecture, software, and datacentre infrastructure design will drive rapid adoption and improvement, unlike today’s concealed cloud infrastructures. In 2020, the next generation post-K flagship Japanese supercomputer will focus on delivering cutting edge AI capabilities. Its deep learning capacity is expected to dwarf the ABCI by more than an order of magnitude, and it is expected to serve as the key infrastructure for HPC and AI convergence.
Head of Computer Science Department in the University of Oxford
Artificial Intelligence: What little we know
Artificial intelligence (AI) as a field seems to have suffered more reversals of fortune in its 60-year history than perhaps any other comparable scientific discipline. We have seen wearying sequences of boom and bust cycles, and some researchers seem to regard AI in much the same way they regard homeopathic medicine. Right now, we are in AI boom times again, and the question every researcher wants answered is whether a bust will follow. In this talk, he will argue that, despite the apparent boom and bust cycles, the truth is that there has been steady progress in AI over the past 60 years, and the current international excitement around AI owes as much to developments over this period as it does to recent breakthroughs. He will also emphasise the areas where our AI knowledge is sparse and speculate about challenges for the field going forward.
Leslie P. Kaelbling
Professor of Computer Science and Artificial Intelligence Laboratory in Massachusetts Institute of Technology
Making robots behave
The fields of AI and robotics have made great improvements in many individual subfields, including in motion planning, symbolic planning, probabilistic reasoning, perception, and learning. Our goal is to develop an integrated approach to solving very large problems that are hopelessly intractable to solve optimally. We make a number of approximations during planning, including serializing subtasks, factoring distributions, and determinizing stochastic dynamics, but regain robustness and effectiveness through a continuous state-estimation and replanning process. I will describe our initial approach to this problem, as well as recent work on improving effectiveness and efficiency through learning.
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