Dr. Danny Lange is VP of AI and Machine Learning at Unity Technologies. As VP of AI and Machine Learning, Danny leads Unity’s efforts around AI (Artificial Intelligence) and Machine Learning. He joined from Uber, where he was Head of Machine Learning. At Uber, Danny led the efforts to build the world’s most versatile Machine Learning platform to support Uber’s hyper growth. Previously, Danny was General Manager of Amazon Machine Learning -- an AWS product that offers Machine Learning as a Cloud Service. Before that, 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., then through his work on General Motors 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. Danny holds MS and Ph.D. degrees in Computer Science from the Technical University of Denmark. He is a member of ACM and IEEE Computer Society and has several patents to his credit.
Ashley is an engaged and innovative leader who has always had a deep interest in advancing the public good. Recently leaving her long-standing career in the public service where she was last Director of Data and Digital for the Government of Canada, she has now taken on the role of Executive Director of AI Global, a non-profit dedicated to creating practical tools to ensure the responsible use of AI. Throughout her career she has worked at the intersection of innovative technology and data, and its impact on providing better information and services.
Mark Weber is an applied researcher and Strategy & Operations Lead at the MIT-IBM Watson AI Lab, a $250 million partnership funding over 200 scientists making fundamental breakthroughs in AI. Through the lab’s corporate membership program, which he runs, Mark works closely with global leaders across multiple sectors on the creative challenge of bridging fundamental science to real-world impact. Mark’s current applied research includes neuro-symbolic generative modeling for construction monitoring, graph deep learning for anti-money laundering, and supply chain demand forecasting. Mark also oversees strategic engagements with IDEO and the International Monetary Fund. Prior to IBM Research, Mark was a graduate researcher at the MIT Media Lab and a fellow at the MIT Legatum Center for Development & Entrepreneurship while he earned his M.B.A in finance from MIT Sloan. There he led the development of an open-source protocol called b_verify for verifiable records in supply chain finance. Before his foray into technology, Mark spent the first chapters of his career focused on political economy and development. He produced three documentary films on these subjects, most notably the critically acclaimed film Poverty, Inc. In his personal time, he is an avid reader and an ultramarathon trail runner. Learn more at www.markrweber.com and follow Mark at @markrweber.
Kairan Quazi is an AI Summer Research Mentee at Intel Labs’ Anticipatory Computing Lab and a full-time undergraduate college student in the San Francisco Bay Area, California. He started his undergraduate studies in Mathematics and Computer Science at the age of 9. Kairan expects to enter his junior (third) year of undergraduate studies in August 2020 at the age of 11. To date, Kairan has earned five certifications in Deep Learning, four certifications in advanced Python programming, and maintains proficiency in 19 programming languages and frameworks. Kairan has been recognized by the prestigious Davidson Institute Young Scholars Program and the Johns Hopkins Study of Exceptional Talent. He has been featured as a guest writer in HuffPost and MIT Technology Review. He has been featured in numerous television and print media interviews as well as viral documentaries released by HuffPost, Voice of America, and 60 Seconds Documentary. Kairan is an extroverted learner with a passion for politics, current events, and all things STEM. He also enjoys reading, video-gaming, collecting Pokémon cards, traveling, and making friends.
Peter Grabowski is a longtime Googler and former Nest employee. He's currently the manager of the Enterprise Machine Learning team in Austin. Previously, he managed a data engineering team at Nest and helped build the Assistant for Kids team at Google. Outside of Google, he teaches machine learning as part of UC Berkeley's Master's in Data Science, and is a managing partner of PXN Residential, LLC.
Slater Victoroff is the Founder and CTO of indico data solutions, an Enterprise AI solution for unstructured content with an emphasis on text and NLP. He has been building machine learning solutions for startups, governments, and Fortune 100 companies for the past 5 years and is a frequent speaker at AI conferences.