IEEE CC Event-15 June @ 6PM - Professor William Wang presents "Self-Supervised Language-and-Vision Reasoning"

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FREE EVENT

Location - Rusty’s Pizza 
5934 Calle Real, Goleta, CA 93117
6:00 PM – Free Pizza, Salad Bar & Beverage
6:25 PM – Central Coast Status
6:30 PM – Professor Wang Presents

Greetings, You (& guest) are invited to join us at Rusty’s Pizza on June15th at 6PM for a talk on the latest in AI Machine learning by Dr. William Wang PhD. UCSB.

Dr. Wang will introduce his team's recent work on visually-grounded language reasoning via the studies of vision-and-language navigation. In particular, he will emphasize three benefits of self-supervised learning:
1) improves generalization in unseen environments;
2) creates counterfactuals to augment observational data;
3) enables transfer learning for challenging settings.

Best regards, Ruth Franklin, IEEE Central, Coast Chair

Please REGISTER NOW below



  Date and Time

  Location

  Hosts

  Registration



  • Date: 15 Jun 2022
  • Time: 06:00 PM to 08:30 PM
  • All times are (UTC-08:00) Pacific Time (US & Canada)
  • Add_To_Calendar_icon Add Event to Calendar
  • Rusty's Pizza
  • 5934 Calle Real
  • Goleta, California
  • United States
  • Room Number: Event Room

  • Starts 24 May 2022 06:30 PM
  • Ends 15 June 2022 05:15 PM
  • All times are (UTC-08:00) Pacific Time (US & Canada)
  • No Admission Charge


  Speakers

Professor Wang Professor Wang of UCSB - CS

Topic:

Self-Supervised Language-and-Vision Reasoning

A key challenge for Artificial Intelligence research is to go beyond static observational data, and consider more challenging settings that involve dynamic actions and incremental decision-making. In this talk, Dr. Wang will introduce his team's recent work on visually-grounded language reasoning via the studies of vision-and-language navigation. In particular, he will emphasize three benefits of self-supervised learning:
1) improves generalization in unseen environments;
2)  creates counterfactuals to augment observational data;
3) enables transfer learning for challenging settings.
I will conclude by briefly introducing other reasoning problems that my groups are working on recently.

Biography:

William Wang (PhD, CMU) is the Duncan and Suzanne Mellichamp Chair in Artificial Intelligence and Designs, and an Associate Professor in the Department of Computer Science at UCSB. He is the Director of UCSB's Natural Language Processing group, and Center for Responsible Machine Learning. He has broad interests in machine learning approaches to data science, including statistical relational learning, information extraction, computational social science, speech, and vision. He has published more than 100 papers at leading NLP/AI/ML conferences and journals, and received best paper awards (or nominations) at ASRU 2013, CIKM 2013, EMNLP 2015, and CVPR 2019, a DARPA Young Faculty Award (Class of 2018), IEEE AI's 10 to Watch (2020), NSF CAREER Award (2021), two Google Faculty Research Awards (2018, 2019), three IBM Faculty Awards (2017-2019), two Facebook Research Awards (2018, 2019), an Amazon AWS Machine Learning Research Award, a JP Morgan Chase Faculty Research Award, an Adobe Research Award in 2018, and the Richard King Mellon Presidential Fellowship in 2011. His work and opinions appear in major tech media outlets such as Wired, VICE, Scientific AmericanFortune, Fast Company, NPR, NASDAQ, The Next Web, Law.com, and Mental Floss. He is an elected member of IEEE Speech and Language Processing Technical Committee (2021-2023) and a member of ACM Future of Computing Academy.

Address:United States