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Samsung AI Forum 2022

Samsung
AI Forum 2022
Samsung
AI Forum 2022

Samsung
AI Forum 2022

On-demand video On-demand video On-demand video

Samsunng AI Forum 2022 Highlight Video

About the Forum About the Forum About the Forum

Participants Participants Participants

Anyone with an interest in AI technology including undergraduate and graduate students, university faculty members, researchers, and etc.

Anyone with an interest in AI technology including undergraduate and graduate students, university faculty members, researchers, and etc.

Anyone with an interest in AI technology including undergraduate and graduate students, university faculty members, researchers, and etc.

Registration Registration Registration

October 18 (Tue.) ~

October 18 (Tue.) ~

October 18 (Tue.) ~

Date Date Date

November 8 (Tue.) 09:30 ~ 16:50

November 8 (Tue.) 09:30 ~ 16:50

November 8 (Tue.) 09:30 ~ 16:50

Location Location Location

Seoul, Korea (Intercontinental Seoul COEX)

Seoul, Korea (Intercontinental Seoul COEX)

Seoul, Korea (Intercontinental Seoul COEX)

※ Online streaming on Samsung YouTube
Speakers Speakers Speakers

Jong Hee Han
Jong Hee Han
Samsung Electronics

Yoshua Bengio
Yoshua Bengio
Montreal Univ.

Changkyu Choi
Changkyu Choi
Samsung

Young Sang Choi
Young Sang Choi
Samsung

Jae-Joon Han
Jae-Joon Han
Samsung

Simon Lacoste-Julien
Simon Lacoste-Julien
Samsung

Minjoon Seo
Minjoon Seo
KAIST

Hyun Oh Song
Hyun Oh Song
Seoul National Univ.

Alan Gara
Alan Gara
Former IBM and Intel Fellow

Robert William Wisniewski
Robert William Wisniewski
Samsung

Seungwon Lee
Seungwon Lee
Samsung

Program Program Program

09:30 - 09:35

Opening Remarks

Jong Hee Han
Vice Chairman & CEO, Samsung Electronics
09:35 - 10:20

Why we need amortized, causal and Bayesian world models

Yoshua Bengio
University of Montreal
Session 1. AI for R&D Innovation Session 1. AI for R&D Innovation Session 1. AI for R&D Innovation
10:20 - 10:35

AI Transformation for Semiconductor R&D

Changkyu Choi
Corporate EVP, Samsung Advanced Institute of Technology
10:35 - 10:50

Materials Design Accelerated by AI

Young Sang Choi
Corporate VP, Samsung Advanced Institute of Technology
10:50 - 11:05

Trustworthy Computer Vision for Semiconductor Manufacturing

Jae-Joon Han
VP of Technology, Samsung Advanced Institute of Technology
Session 2. Recent Advances of AI Algorithms Session 2. Recent Advances of AI Algorithms Session 2. Recent Advances of AI Algorithms
11:25 - 11:40

Learning Causal Representations

Simon Lacoste-Julien
VP of SAIT AI Lab. Montreal
11:40 - 12:00

Generative Search Engine

Minjoon Seo
Korea Advanced Institute of Science & Technology
12:00 - 12:20

Learning with Combinatorial Structures for Efficient Machine Learning

Hyun Oh Song
Seoul National University
12:20 - 13:40

Lunch

Session 3. Large Scale Computing for AI and HPC Session 3. Large Scale Computing for AI and HPC Session 3. Large Scale Computing for AI and HPC
13:40 - 14:00

The Evolution of HPC and ramifications for the future of AI

Alan Gara
Former IBM and Intel Fellow
14:00 - 14:15

Innovating the Next Discontinuity

Robert William Wisniewski
SVP of SAIT Systems Architecture Lab. San Jose
14:15 - 14:30

Single Large Job Acceleration with GPU and Processing-in-memory (PIM)

Seungwon Lee
VP of Technology, Samsung Advanced Institute of Technology
14:40 - 15:30

Panel Discussion

15:50 - 15:55

Awards Ceremony

Samsung AI Researcher of the Year -
Samsung AI Challenge
15:55 - 16:45

Awardee's Contribution Speech

16:45 - 16:50

Closing Remarks

Gyoyoung Jin
Corporate President, Samsung Advanced Institute of Technology

Samsung AI Researcher 2022 Awardee Samsung AI Researcher 2022 Awardee Samsung AI Researcher 2022 Awardee

Danqi Chen
Danqi Chen
Princeton Univ.

one of the pioneers of deep learning for NLP. She was one of the first's to show that deep learning can have high impact on NLP by proposing a deep learning based parser. Since then she's been pushing the boundary of deep learning for NLP.


one of the pioneers of deep learning for NLP. She was one of the first's to show that deep learning can have high impact on NLP by proposing a deep learning based parser. Since then she's been pushing the boundary of deep learning for NLP.


one of the pioneers of deep learning for NLP. She was one of the first's to show that deep learning can have high impact on NLP by proposing a deep learning based parser. Since then she's been pushing the boundary of deep learning for NLP.

Tengyu Ma
Tengyu Ma
Stanford Univ.

one of the pioneers of modern theoretical understanding of deep learning. He worked on analyzing and studying challenging, real-world algorithms doing works leading to better theoretical understanding of neural methods.


one of the pioneers of modern theoretical understanding of deep learning. He worked on analyzing and studying challenging, real-world algorithms doing works leading to better theoretical understanding of neural methods.


one of the pioneers of modern theoretical understanding of deep learning. He worked on analyzing and studying challenging, real-world algorithms doing works leading to better theoretical understanding of neural methods.

Simon Shaolei Du
Simon Shaolei Du
Univ. of Washington

a very productive researcher who authored many strong papers in theory of deep learning and reinforcement learning



a very productive researcher who authored many strong papers in theory of deep learning and reinforcement learning



a very productive researcher who authored many strong papers in theory of deep learning and reinforcement learning

Mohit Iyyer
Mohit Iyyer
Univ. of Massachusetts Amherst

co-authored one of the most influential, seminal papers on contextualized word embeddings, ELMO. He also contributed in the areas of open-ended question answering and language generation.


co-authored one of the most influential, seminal papers on contextualized word embeddings, ELMO. He also contributed in the areas of open-ended question answering and language generation.


co-authored one of the most influential, seminal papers on contextualized word embeddings, ELMO. He also contributed in the areas of open-ended question answering and language generation.

Aditya Grover
Aditya Grover
Univ. of California Los Angeles

a productive researcher in probabilistic deep learning. Other than theoretical side, he also contributed to socially important applications such as improving battery materials


a productive researcher in probabilistic deep learning. Other than theoretical side, he also contributed to socially important applications such as improving battery materials


a productive researcher in probabilistic deep learning. Other than theoretical side, he also contributed to socially important applications such as improving battery materials

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