Mark your calendars! Another exciting season of the Allen School’s Distinguished Lecture Series kicks off on Oct. 10. During the 2019-2020 season, we will explore deep learning, domain-specific architectures, recent advances in artificial intelligence and robotics, and so much more. All lectures take place at 3:30 p.m. in the Amazon Auditorium on the ground floor of the Bill & Melinda Gates Center on the University of Washington’s Seattle campus. In addition, each lecture will be live streamed on the Allen School’s YouTube channel.
Oct. 10: Jeff Dean, Google Senior Fellow and Senior Vice President for Google AI
Allen School alumnus Jeff Dean (Ph.D., ‘96) returns to his alma mater on Thursday, Oct. 10 to deliver a talk on “Deep Learning to Solve Challenging Problems.” Dean’s presentation will highlight recent accomplishments by Google research teams, such as the open-source TensorFlow system to rapidly train, evaluate and deploy machine learning systems, and how they relate to the National Academy of Engineering’s Grand Challenges for Engineering in the 21st Century. He will also explore how machine learning is transforming many aspects of today’s computing hardware and software systems.
Dean, who joined Google in 1999, currently leads teams working on systems for speech recognition, computer vision, language understanding and various other machine learning tasks. During his two decades with the company, he co-designed and implemented many of Google’s most important and visible features, including multiple generations of its crawling, indexing and query serving systems as well as pieces of Google’s initial advertising and AdSense for content systems. He also helped create Google’s distributed computing infrastructure, including MapReduce, BigTable and Spanner.
Oct. 29: David Patterson, Professor Emeritus, University of California, Berkeley; Distinguished Engineer, Google; and Vice Chair, Reduced Instruction Set Computer (RISC) Foundation
David Patterson will deliver a talk on Oct. 29 examining “Domain Specific Architectures (DSA) for Deep Neural Networks: Three Generations of Tensor Processing Units (TPUs).” His presentation will explore how the recent success of deep neural networks has inspired a resurgence in domain specific architectures to run them, partially as a result of the declaration of microprocessor performance improvement due to the ending of Moore’s Law. His talk will review Google’s first generation Tensor Processing Unit (TPUv1) and how the company built the first production DSA supercomputer for the much harder problem of training, which was deployed in 2017.
Patterson’s work on RISC, Redundant Array of Inexpensive Disks (RAID), and Network of Workstation projects helped lead to multibillion-dollar industries. In 2017, he and RISC collaborator John Hennessy shared the Association for Computing Machinery’s A.M. Turing Award — the “Nobel Prize of computing” — for pioneering a systematic, quantitative approach to the design and evaluation of computer architectures with enduring impact on the microprocessor industry.
Nov. 14: Elizabeth Spelke, Marshall L. Berkman Professor of Psychology at Harvard University and Investigator, NSF-MIT Center for Brains, Minds and Machines
Elizabeth Spelke will deliver a lecture on Nov. 14 titled, “From Core Concepts to New Systems Knowledge.” Her lecture will center on cognitive systems in young children and the ability of the human species to gain knowledge not only through gradual learning but also through a fast and flexible learning process that appears to be unique to humans and emerges with the onset of language. Although this phase of life isn’t fully understood, Spelke is using research in psychology, neuroscience and artificial intelligence to better understand human cognitive function.
Spelke explores the sources of uniquely human cognitive capacities, including the capacity for formal mathematics, for constructing and using symbolic representations, and for developing comprehensive taxonomies of objects. Conducting behavioral research on infants and preschool children, Spelke studies the origins and development of human cognition by examining how humans develop their understanding of objects, actions, people, places, numbers and geometry. She also works with computational cognitive scientists to test computational models of infants’ cognitive capacities, and to extend her research into the field with the ultimate goal to enhance young children’s learning.
Dec. 5: Ayanna Howard, Linda J. and Mark C. Smith Professor and Chair, School of Interactive Computing at the Georgia Institute of Technology
Ayanna Howard will deliver a presentation on Dec. 5 titled “Roving for a Better World.” Her talk will focus on the role of computer scientists as responsible global citizens. She will delve into the implications of recent advances in robotics and artificial intelligence, and explain the critical importance of ensuring diversity and inclusion at all stages to reduce the risk of unconscious bias and ensuring robots are designed to be accessible to all.
Prior to joining Georgia Tech, Howard was a senior robotics researcher and deputy manager in the Office of the Chief Scientist at NASA’s Jet Propulsion Laboratory. She was first hired by NASA at the age of 27 to lead a team designing a robot for future Mars exploration missions that could “think like a human and adapt to change.” While at Georgia Tech, she has served as associate director of research for the Institute for Robotics and Intelligent Machines and chair of the robotics Ph.D. program. Business Insider named her one of the most powerful women engineers in the world in 2015 and in 2018 she was named in Forbes’ Top 50 Women in Tech.
Jan. 16: Kathleen McKeown, Henry and Gertrude Rothschild Professor of Computer Science and Founding Director, Data Science Institute, Columbia University
McKeown’s research is in natural language processing, summarization, natural language generation and analysis of social media. In these areas, her work focuses on text summarization and generating updates on disasters over live, streaming information, generating messages about electricity usage and using reinforcement learning over usage logs to determine what kinds of messages can change behavior and the analysis of social media to detect messages about aggression and loss. While at Columbia, McKeown has served as the director of the Data Science Institute, was department chair from 1998-2003 and was the vice dean for research for the School of Engineering and Applied Science for two years. McKeown is also active internationally, having served as president, vice president and secretary-treasurer of the Association of Computational Linguistics as well as a board member and secretary of the board for the Computing Research Association.
Feb. 27: Fernando Pereira, Vice President and Engineering Fellow, Google
Pereira leads research and development at Google in natural language understanding and machine learning. Previously, he was chair of the computer and information science department at the University of Pennsylvania, head of the machine learning and information retrieval department at AT&T Labs, and held research and management positions at Scientific Research Institute International. Pereira has produced more than 120 research publications on computational linguistics, machine learning, bioinformatics, speech recognition and logic programming. He holds several patents and is widely recognized for his contributions to sequence modeling, finite-state methods, and dependency and deductive parsing.
Be sure to check our Distinguished Lecture Series page for updates throughout the season, and please plan to join us!