AAAI-18 Invited Speakers Schedule

Sunday, February 4
9:00 – 9:50 am – Rao Kambhampati (Presidential Address)
5:10 – 6:10 pm – Yejin Choi

Monday, February 5
8:50 – 9:50 am – Charles Isbell
5:00 – 6:00 pm – Zoubin Ghahramani (AAAI/IAAI Joint Talk)

Tuesday, February 6
8:50 – 9:50 am – Cynthia Dwork
4:00 – 5:00 pm – Joe Halpern

Wednesday, February 7
8:50 – 9:50 am – Percy Liang

AAAI-19 Invited Speaker Program

AAAI-19 will feature the following series of distinguished speakers (partial list):

Dimitris Bertsimas

Dimitris Bertsimas

Massachusetts Institute of Technology

AAAI 2019 Invited Talk
Talk Title: Interpretable AI

Abstract: We introduce a new generation of machine learning methods that provide state of the art performance and are very interpretable. We introduce optimal classification (OCT) and regression (ORT) trees for prediction and prescription with and without hyperplanes. We show that (a) Trees are very interpretable, (b) They can be calculated in large scale in practical times, and (c) In a large collection of real world data sets they give comparable or better performance than random forests or boosted trees. Their prescriptive counterparts have a significant edge on interpretability and comparable or better performance than causal forests. Finally, we show that optimal trees with hyperplanes have at least as much modeling power as (feedforward, convolutional and recurrent) neural networks and comparable performance in a variety of real world data sets. These results suggest that optimal trees are interpretable, practical to compute in large scale and provide state of the art performance compared to black box methods. (joint work with Jack Dunn)

Dimitris Bertsimas is currently the Boeing Professor of Operations Research, the co-director of the Operations Research Center, and faculty director of the Master of Business analytics at MIT. He received his SM and PhD in Applied Mathematics and Operations Research from MIT in 1987 and 1988 respectively. He has been with the MIT faculty since 1988. His research interests include optimization, machine learning and applied probability and their applications in health care, finance, operations management and transportation. He has co-authored more than 200 scientific papers and four graduate level textbooks. He is the editor in Chief of INFORMS Journal of Optimization and former department editor in Optimization for Management Science and in Financial Engineering in Operations Research. He has supervised 67 doctoral students and he is currently supervising 25 others. He is a member of the National Academy of Engineering since 2005, an INFORMS fellow, and he has received numerous research and teaching awards including the Morse prize (2013), the Pierskalla award for best paper in health care (2013), the best paper award in Transportation (2013), the Farkas prize (2008), the Erlang prize (1996), the SIAM prize in optimization (1996), the Bodossaki prize (1998) and the Presidential Young Investigator award (1991-1996).

Qiang Yang

Qiang Yang

Hong Kong University of Science and Technology

AAAI 2019 Invited Talk
Talk Title: GDPR, Data Shortage and AI

Abstract: Despite its great progress so far, artificial intelligence (AI) is facing a serious challenge in the availability of high-quality Big Data. In many practical applications, data are in the form of isolated islands. Efforts to integrate the data are increasingly difficult partly due to serious concerns over user privacy and data security. The problem is exacerbated by strict government regulations such as Europe’s General Data Privacy Regulations (GDPR). In this talk, I will review these challenges and describe possible technical solutions to address them. In particular, I will give an overview of recent advances in transfer learning and show how it can alleviate the problems of data shortage. I will also give an overview of recent efforts in federated learning and transfer learning, which aims to bridge data repositories without compromising data security and privacy.

Qiang Yang is a chair professor at Computer Science and Engineering Department at Hong Kong University of Science and Technology (HKUST). His research interests include artificial intelligence, machine learning, especially transfer learning. He is a fellow of AAAI, ACM, IEEE, AAAS etc., and the founding Editor in Chief of the ACM Transactions on Intelligent Systems and Technology (ACM TIST) and the founding Editor in Chief of IEEE Transactions on Big Data (IEEE TBD). He received his PhD from the University of Maryland, College Park in 1989 and has taught at the University of Waterloo and Simon Fraser University. He was the PC Chair of IJCAI-2015, and received the ACM SIGKDD Distinguished Service Award in 2017. He is the current President of IJCAI (2017-2019) and an executive council member of AAAI.

Yu Zheng

Yu Zheng

JD Group

AAAI-19 Invited Talk
Talk Title: Urban Computing: Building Intelligent Cities Using Big Data and AI

Abstract: Urban computing is a synergy among cloud computing, big data and AI models in the context of cities, tackling urban challenges, such as air pollution, energy consumption and traffic congestion, to create win-win-win solutions that improve urban environment, human life quality and city operation systems. This talk presents the vision of urban computing, demonstrating how AI technology helps to build intelligent cities. A series of AI-driven applications, such as location selection for business, forecasting air and water quality, and reducing energy consumption are also introduced in this talk. More information can be found through the website:

Yu Zheng is the Vice President of JD Group, leading the Urban Computing Business Unit and JD Intelligent City Research. He also serves as the Chief Data Scientist at JD Digits, passionate about using big data and AI technology to tackle urban challenges. Before Joining JD Group, he was a senior research manager at Microsoft Research. Zheng is also a Chair Professor at Shanghai Jiao Tong University and an Adjunct Professor at Hong Kong University of Science and Technology. He currently serves as the Editor-in-Chief of ACM Transactions on Intelligent Systems and Technology and has served as chair on over 10 prestigious international conferences, such as the program co-chair of ICDE 2014 (Industrial Track), CIKM 2017 (Industrial Track) and IJCAI 2019 (industrial track), as well as an area chair of AAAI 2019. In 2013, he was named one of the Top Innovators under 35 by MIT Technology Review (TR35) and featured by Time Magazine for his research on urban computing. In 2014, he was named one of the Top 40 Business Elites under 40 in China by Fortune Magazine. In 2017, Zheng was honored as an ACM Distinguished Scientist. His homepage is

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