Yoshua Bengio is Full Professor of the Department of Computer Science and Operations Research, head of the Montreal Institute for Learning Algorithms (MILA), CIFAR Program co-director of the CIFAR program on Learning in Machines and Brains, Canada Research Chair in Statistical Learning Algorithms. His main research ambition is to understand principles of learning that yield intelligence. He supervises a large group of graduate students and post-docs. His research is widely cited (over 135,000 citations found by Google Scholar in September 2017, with an H-index of 125).

Yoshua Bengio is currently action editor for the Journal of Machine Learning Research, associate editor for the Neural Computation journal, editor for Foundations and Trends in Machine Learning, and has been associate editor for the Machine Learning Journal and the IEEE Transactions on Neural Networks.

Dr. Steve Chien is Technical Group Supervisor of the Artificial Intelligence Group and Senior Research Scientist in the Mission Planning and Execution Section at the Jet Propulsion Laboratory, California Institute of Technology where he leads efforts in automated planning and scheduling for space exploration. Dr. Chien is also Adjunct Faculty with the Department of Computer Science of the University of Southern California and previously was a Visiting Scholar with the Department of Computer Science of the University of California at Los Angeles. He holds a B.S. with Highest Honors in Computer Science, with minors in Mathematics and Economics, M.S., and Ph.D. degrees in Computer Science, all from the University of Illinois.

Dr. Chien was a recipient of the 1995 Lew Allen Award for Excellence, JPLs highest award recognizing outstanding technical achievements by JPL personnel in the early years of their careers. In 1997, he received the NASA Exceptional Achievement Medal for his work in research and development of planning and scheduling systems for NASA. He is the Team Lead for the ASPEN Planning System , which received Honorable Mention in the 1999 Software of the Year Competition and was a contributor to the Remote Agent System which was a co-winner in the same 1999
competition. In 2000, he received the NASA Exceptional Service Medal for service and leadership in research and deployment of planning and scheduling systems for NASA. He is the Principal Investigator for the Autonomous Sciencecraft Experiment which is a co-winner of the 2005 NASA Software of the Year Award. In 2007, he received the NASA Exceptional Achievement Medal for outstanding technical accomplishments in the development of the Autonomous Sciencecraft deployed on the Earth Observing One Mission and the development of the Earth Observing Sensorweb. In 2011 He was awarded the innaugural AIAA Intelligent Systems Award, for his contributions to Spacecraft Autonomy. In 2011, he was the team co-lead for the Sensorweb Toolbox team, which was awarded Honorable mention in the 2011 NASA Software of the Year Competition. In 2015 He was awarded a JPL Magellan Award as well as the NASA Exceptional Achievement Medal for his contributions to automated science scheduling for ESAs Rosetta mission.

As Chief Decision Scientist at Google Cloud, Cassie Kozyrkov advises leadership teams on decision process, AI strategy, and building data-driven organizations. She works to democratize statistical thinking and machine learning so that everyone – Google, its customers, the world! – can harness the beauty and power of data. She is the force behind bringing the practice of Decision Intelligence to Google and she has personally trained over 15,000 Googlers in machine learning, statistics, and data-driven decision-making. Before her current role, she served in Googles Office of the CTO as Chief Data Scientist. Prior to joining Google, Cassie worked as a data scientist and consultant. She holds degrees in mathematical statistics, economics, psychology, and cognitive neuroscience. When she’s not working, you’re most likely to find Cassie at the theater, in an art museum, exploring the world, or curled up with a good novel.

Itamar (一塔) Friedman is the founder and head of Alibaba Israel Machine Vision Lab, leading teams to create innovations for Alibaba’s diverse ecosystems.

Itamar was the CTO of Visualead, a startup developing cutting-edge machine vision O2O technologies acquired by Alibaba.

In the 90s, during high school, Itamar founded his first company, at that time pioneering the Internet scene in Israel by developing web applications to assist businesses having an online presence. Later on Itamar worked as an engineer at Mellaxon and Kaminario, and then was the co-founder and CTO of Dreambots, a startup in the robotic field.

Itamar holds a BSc in Electrical Engineering (Summa Cum Laude) and a MSc in Computer Vision and Machine Learning from the Technion (Israel Institute of Technology).

Manuela M. Veloso is the Head of J.P. Morgan AI Research, which pursues fundamental research in areas of core relevance to financial services, including data mining and cryptography, machine learning, explainability, and human-AI interaction. J.P. Morgan AI Research partners with applied data analytics teams across the firm as well as with leading academic institutions globally.

Professor Veloso is on leave from Carnegie Mellon University as the Herbert A. Simon University Professor in the School of Computer Science, and the past Head of the Machine Learning Department. With her students, she had led research in AI, with a focus on robotics and machine learning, having concretely researched and developed a variety of autonomous robots, including teams of soccer robots, and mobile service robots. Her robot soccer teams have been RoboCup world champions several times, and the CoBot mobile robots have autonomously navigated for more than 1,000km in university buildings.

Professor Veloso is the Past President of AAAI, (the Association for the Advancement of Artificial Intelligence), and the co-founder, Trustee, and Past President of RoboCup. Professor Veloso has been recognized with a multiple honors, including being a Fellow of the ACM, IEEE, AAAS, and AAAI. She is the recipient of several best paper awards, the Einstein Chair of the Chinese Academy of Science, the ACM/SIGART Autonomous Agents Research Award, an NSF Career Award, and the Allen Newell Medal for Excellence in Research. See www.cs.cmu.edu/~mmv/Veloso.html for her scientific publications.

Dr. Joseph Sirosh is the CTO for Microsoft AI. Prior to this role, he has served as a Corporate Vice President of the AI and Data Platform at Microsoft responsible for Databases, Big Data, Machine Learning Cognitive Services, Bot Services and Information Management, and as the Vice President of the Global Inventory Platform at Amazon where he also spent nearly 9 years in various roles including building internal Machine Learning platforms. Prior to Amazon he was the VP of R&D at Fair Isaac Corporation. He holds a PhD in Neural Networks from the University of Texas at Austin and a BTech from Indian Institute of Technology, Chennai.

Francesca Rossi is AI Ethics Global Leader, Distinguished Research Staff Member at IBM Research AI and professor of computer science at the University of Padova, Italy, currently on leave.

Her research interests focus on artificial intelligence, specifically they include constraint reasoning, preferences, multi-agent systems, computational social choice, and collective decision making. She is also interested in ethical issues in the development and behaviour of AI systems, in particular for decision support systems for group decision making. She has published over 170 scientific articles in journals and conference proceedings, and as book chapters. She has co-authored a book. She has edited 17 volumes, between conference proceedings, collections of contributions, special issues of journals, as well as the Handbook of Constraint Programming. She has more than 100 co-authors.

She is a AAAI and a EurAI fellow, and a Radcliffe fellow 2015. She has been president of IJCAI and an executive councillor of AAAI.
She is Editor in Chief of JAIR and a member of the editorial board of Constraints, Artificial Intelligence, AMAI, and KAIS.

She co-chairs the AAAI committee on AI and ethics and she is a member of the scientific advisory board of the Future of Life Institute and of the Leverhulme Centre for the Future of Intelligence. She is in the executive committee of the IEEE global initiative on ethical considerations on the development of autonomous and intelligent systems and she belongs to the World Economic Forum Council on AI and robotics.

She is a member of the board of directors of the Partnership on AI, where she represents IBM as one of the founding partners.

Mikhail Parakhin has been leading teams in AI innovation for some of the world’s top tech companies for over a decade. After several years at Microsoft leading the Bing Multimedia team, Mikhail brought his machine learning expertise to Yandex, one of Europe’s largest tech companies that builds intelligent products and services powered by machine learning. As CTO of Yandex, Mikhail leads all technical teams globally for the company.

Under his leadership, Yandex introduced the Machine Intelligence and Research (MIR) Division, which functions as a centralized, cross-functional unit to accelerate innovation and unify Yandex’s core machine learning technologies: MatrixNet (proprietary ML platform) and its development, CatBoost (best in class GBDT implementation), DaNet (DNN framework), computer vision, speech, and translation. Yandex has also recently launched it’s intelligent assistant, Alice, and tested its driverless vehicle on the snowy roads of Moscow among other innovation milestones set to shape the future.

Mikhail brings his unique background in machine learning and coding plus specializations in Search, Image processing and Handwriting/Speech recognition algorithms to not only advance Yandex’s technologies and products but the global tech ecosystem. Mikhail holds a Master’s in Physics from the Moscow Engineering Physics Institute.

Jay Bellissimo is the Global Managing Partner of IBM Services Cognitive Process Transformation Growth Platform, leading the service lines of Cognitive Process Re-engineering, Cognitive Process Services, and Cognitive Business Decision Support. The Practices he oversees include Watson AI & Data Platform, Advance Analytics, Blockchain, Watson Internet of Things, Watson Health, Talent & Engagement, Process Automation, among others. His primary mission is to fuel growth by deploying competitive market offerings and building a diverse and differentiated talent pool and to continue to amaze and delight our customers.

Dr. Danny Lange is Vice President of AI and Machine Learning at Unity Technologies where he leads multiple initiatives around applied artificial intelligence. Previously, Danny was Head of Machine Learning at Uber, where he led the efforts to build a highly scalable machine learning platform to support all parts of Uber’s business.

Before joining Uber, Danny was General Manager of Amazon Machine Learning providing internal teams with access to machine intelligence. He also launched an AWS product that offers machine learning as a cloud service to the public. Prior to Amazon, he was Principal Development Manager at Microsoft where he led a product team focused on large-scale machine learning for big data. Danny spent eight years on speech recognition systems, first as CTO of General Magic, Inc., and then as founder of his own company, Vocomo Software. During this time he was working on General Motor’s OnStar Virtual Advisor, one of the largest deployments of an intelligent personal assistant until Siri. Danny started his career as a Computer Scientist at IBM Research.

He holds MS and PhD degrees in computer science from the Technical University of Denmark. He is a member of ACM and IEEE Computer Society and has numerous patents to his credit.