Summer School 2021 (Virtual) - Advances and Challenges of Artificial Intelligence in the Internet-of-Things Era

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Internet-of-Things (IoT) is a paradigm shifting technology that advances various aspects in our life in recent years. The proliferation of Artificial Intelligence (AI) opens up the possibility of integrating intelligence into various IoT devices, which creates many smart and efficient solutions in areas such as healthcare, security surveillance, self-drive car, human activity recognition, transportation, robots in manufacturing, and risk management to name a few. The IoT devices range from high-end computers to mobile devices and low-end microcontroller, wherein many of them are resource-constrained in computation power and storage. Due to this reason, it is challenging to apply deep learning (mostly computationally extensive and requiring high storage space) into resource-constrained IoT devices. To address these challenges, various approaches have been proposed to make deep learning lightweight and optimized for resource-constrained devices. In this workshop, we will review and discuss the representative techniques on the hardware level (hardware acceleration techniques) as well as on the software level (model compression techniques). We will also deal with the fundamental aspects of reinforcement learning, challenges and progresses in face recognition, biometric applications and federated learning. Interesting research areas are presented to design future networks based on AI.

*The detailed information about this workshop is available at https://ai-security.github.io/summer-school-2021.



  Date and Time

  Location

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  • Start time: 15 Jul 2021 09:30 AM
  • End time: 16 Jul 2021 12:20 PM
  • All times are Asia/Seoul
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  • Co-sponsored by Institute of Electronics and Information Engineers, Korea






Agenda

15 July 2021

Time

Program

Speaker

09:30 – 10:20

Reinforcement Learning and Stochastic Optimization: A unified framework for sequential decisions Part 1

Prof. Warren Powell, Princeton University, USA

10:20 – 11:00

New Challenges to Face Recognition: Low-Resolution Face Recognition and Periocular Recognition

Dr. Cheng-Yaw Low, Yonsei University, Korea

11:00 – 11:40

AI for Information-Centric Networks as a Future Network Technology

Prof. Byung Seo Kim, Hongik University, Korea

11:40 – 12:20

Deep Review of Model Compression in Knowledge Distillation Side

Prof. Byung Chul Ko, Keimyung University, Korea

12:20 – 14:00

Lunch break

 

14:00 -14:40

Biometric Cryptosystem: Progress and Challenge

Prof. Andrew Beng-Jin Teoh, Yonsei University, Korea

14:40 – 15:20

Maritime, Underwater IoT and AI-based First-order logic TUM-IoT Digtital Twin

* TUM-IoT : Terristrial, Underwater, Maritime - IoT

Prof. Soohyun Park, Kookmin University, Korea

15:20

End

 

 

16 July 2021

Time

Program

Speaker

09:30 – 10:20

Reinforcement Learning and Stochastic Optimization: A unified framework for sequential decisions Part 2

Prof. Warren Powell, Princeton University, USA

10:20 – 11:00

Overview of Model Compression and Quantization in Deep Learning

Dr. Jin-Chuan See, Universiti Tunku Abdul Rahman, Malaysia

11:00 – 11:40

Edge Federated Learning: Recent Advances and Open Research Problems

Dr. Rehmat Ullah, Queen's University, UK

11:40 – 12:20

Hardware Acceleration and Optimization of Deep Neural Networks

Prof. William Song, Yonsei University, Korea

12:20

End