Abstract Number:
1767
Submission Type:
Topic-Contributed Panel Session
Participants:
Jiayi wang (1), Hengrui Cai (2), Wenzhuo Zhou (3), Ruonan Li (4), Jiayi wang (1)
Institutions:
(1) University of Texas at Dallas, N/A, (2) University of California Irvine, N/A, (3) University of Illinois Urbana-Champaign, N/A, (4) Merck & Co., N/A
Chair:
Panelist(s):
Session Organizer:
Session Description:
In this session, we will delve into recent developments in natural language processing and computer vision from a statistical perspective, encompassing advancements in both theory and practical applications. Researchers from both academia and industry will present three compelling projects. Given the rapid evolution of technology, the session's focus on natural language processing and computer vision is both timely and essential. The proposed talks not only delve into cutting-edge theories but also showcase real-world applications, making the session appealing to a broad audience, including researchers, practitioners, and industry professionals.
Session Timeline:
1. Title: Actor-Critic Graph Neural Networks: A Comprehensive Recipe for Neural Decoding
Speaker: Wenzhuo Zhou (UIUC)
2. Title: Towards Trustworthy Machine Learning: A Focus on Explainability
Speaker: Hengrui Cai (UCI)
3. Title: Statistical Computer Vision for Medical Research
Speaker: Ruonan Li (Merck & Co.)
Each talk is allocated 20 minutes, followed by a 5-minute Q&A session. After the three talks, we will dedicate 15 minutes to peer discussion, fostering collaboration and knowledge exchange.
Sponsors:
Committee on Women in Statistics 2
International Chinese Statistical Association 1
Section on Statistical Learning and Data Science 3
Theme:
Statistics and Data Science: Informing Policy and Countering Misinformation
Yes
Applied
Yes
Estimated Audience Size
Small (<80)
I have read and understand that JSM participants must abide by the Participant Guidelines.
Yes
I understand and have communicated to my proposed speakers that JSM participants must register and pay the appropriate registration fee by June 1, 2024. The registration fee is nonrefundable.
I understand