Speaker:
Professor Mohan KANKANHALLI
Provost’s Chair Professor of Computer Science and Dean, School of Computing

Session 1: NUS Artificial Intelligence Laboratory (NUSAiL) Distinguished AI Lecture

Host:
Professor Terence SIM Mong Cheng
Associate Professor of Computer Science and Vice Dean of Communications, School of Computing

Title: From Seeing to Doing: Understanding and Interacting With the Real World

Distinguished Speaker:
Professor LI Fei Fei
Sequoia Capital Professor of Computer Science and
Professor, By Courtesy, Of Operations, Information And Technology At The Graduate School Of Business
Co-Director Of The Stanford Institute For Human-Centered Artificial Intelligence (Hai)
Stanford University, USA

Dr. Fei-Fei Li (https://profiles.stanford.edu/fei-fei-li) is the inaugural Sequoia Professor in the Computer Science Department at Stanford University, and Co-Director of Stanford’s Human-Centered AI Institute. She served as the Director of Stanford’s AI Lab from 2013 to 2018. And during her sabbatical from Stanford from January 2017 to September 2018, she was Vice President at Google and served as Chief Scientist of AI/ML at Google Cloud. Dr. Fei-Fei Li obtained her B.A. degree in physics from Princeton in 1999 with High Honors and her Ph.D. degree in electrical engineering from the California Institute of Technology (Caltech) in 2005. She joined Stanford in 2009 as an assistant professor. Prior to that, she was on faculty at Princeton University (2007-2009) and the University of Illinois Urbana-Champaign (2005-2006).

Dr. Fei-Fei Li’s current research interests include cognitively inspired AI, machine learning, deep learning, computer vision, and AI+healthcare, especially ambient intelligent systems for healthcare delivery. In the past, she has also worked on cognitive and computational neuroscience. Dr. Li has published more than 200 scientific articles in top-tier journals and conferences, including Nature, PNAS, Journal of Neuroscience, CVPR, ICCV, NIPS, ECCV, ICRA, IROS, RSS, IJCV, IEEE-PAMI, New England Journal of Medicine, Nature Digital Medicine, etc. Dr. Li is the inventor of ImageNet and the ImageNet Challenge, a critical large-scale dataset and benchmarking effort that has contributed to the latest developments in deep learning and AI. In addition to her technical contributions, she is a national leading voice for advocating diversity in STEM and AI. She is co-founder and chairperson of the national non-profit AI4ALL aimed at increasing inclusion and diversity in AI education.

Dr. Li is an elected Member of the National Academy of Engineering (NAE), the National Academy of Medicine (NAM), and the American Academy of Arts and Sciences (AAAS). She is also a Fellow of ACM, a member of the Council on Foreign Relations (CFR), a recipient of the 2019 IEEE PAMI Longuet-Higgins Prize, 2019 National Geographic Society Further Award, 2017 Athena Award for Academic Leadership, IAPR 2016 J.K. Aggarwal Prize, the 2016 IEEE PAMI Mark Everingham Award, the 2016 Nvidia Pioneer in AI Award, 2014 IBM Faculty Fellow Award, 2011 Alfred Sloan Faculty Award, 2012 Yahoo Labs FREP award, 2009 NSF CAREER award, the 2006 Microsoft Research New Faculty Fellowship, among others. Dr. Li is a keynote speaker at many academic or influential conferences, including the World Economic Forum (Davos), the Grace Hopper Conference 2017, and the TED2015 main conference. Work from Dr. Li’s lab has been featured in a variety of magazines and newspapers, including New York Times, Wall Street Journal, Fortune Magazine, Science, Wired Magazine, MIT Technology Review, Financial Times, and more. She was selected as a 2017 Women in Tech by the ELLE Magazine, a 2017 Awesome Women Award by Good Housekeeping, a Global Thinker of 2015 by Foreign Policy, and one of the Great Immigrants: The Pride of America in 2016 by the Carnegie Foundation, past winners include Albert Einstein, Yoyo Ma, and Sergey Brin, et al.

Abstract:
Visual intelligence is a cornerstone of intelligence, for both humans and machines. In this talk, I go over a number of research work by our group on the topics of visual perception and robotic learning. The guiding principle of our work is inspired by the Gibsonian belief that perceptual and robotic learning should be based on an ecology approach, solving tasks and problems approximating the real-world setting and scale.

Session 2: NUSAiL-Rosetta Expert Panel on Inclusive AI Education

Toward Gender-Balanced AI Education: How to Encourage More Women to Pursue Education and Career in Computing and AI?

AI is a new power engine that will help build better lives. New challenges and opportunities in AI empower the solutions to many social, economic, and environmental challenges in the post-pandemic world. The future of AI will be shaped by the next generation of AI scientists, engineers, practitioners, and users. Over the decades, the gender imbalance in the AI research, education, and professional communities has persisted and shown dangerous signs of deterioration. How do we foster gender-balance AI education to face the opportunities and challenges ahead? How do we best teach AI in universities and lifelong education programs going forward?

The topics of interest include, but not limited to:

– How to inspire, motivate, and encourage more women to pursue a career in Computing and AI?
– How to design the core curriculum of a gender-balanced AI education at the undergraduate and graduate levels?
– What are some effective methods of teaching AI in a gender-balanced, multidisciplinary setting?
– What are the main challenges and opportunities in developing a gender-balanced AI community?
– How to effectively support both men and women in a gender-balanced AI-related career?

Moderator:
Professor LEE Wee Sun
Professor of Computer Science and Head, Department of Computer Science

Panelists:
Professor GOH Khim Yong
Associate Professor of Information Systems and Analytics and Head, Department of Information Systems and Analytics

Professor Atreyi KANKANHALLI
Provost’s Chair Professor of Information Systems and Analytics

Professor LI Fei Fei
Sequoia Professor, Stanford University and Co-Director, Stanford’s Human-Centered AI Institute

Dr. Angela YAO Ying Jie
Assistant Professor of Computer Science and National Research Foundation Fellow for AI