Committee

Conference Chairs
Sanyang Liu Xidian University, China		Wanyang Dai Nanjing University, China		Fary Ghassemlooy Northumbria University, UK
Patrick Siarry Université Paris-Est Créteil, France
Conference Co-Chair
Qiwei Zhan Zhejiang University, China
Program Chairs
Abdul Ghani Albaali Princess Sumaya University for Technology, Jordan		Zaixing He Zhejiang University, China		Can Wan Zhejiang University, China
Program Committee
Ran Gao Beijing Institute of Technology, China		Liguo Wang Harbin Engineering University, China		Dariusz Jacek Jakóbczak Koszalin University of Technology,  Poland
Riadh Robbana Carthage University, Tunisia		Jinwei Liu University of Central Florida, USA		Michael N. Vrahatis University of Patras, Greece

Local Chair

Wanyang Dai Nanjing University, China

Keynote Speaker Ⅰ

Prof. Wang Han

Fellow of SCAAST, Senior Member IEEE

Xiamen University Malaysia, China

Biography: Prof Wang Han is a Fellow of the Singapore-China Association for Advancement of Science and Technology (SCAAST), Senior Member IEEE, and Dean of the School of Electrical Engineering & Artificial Intelligence, Xiamen University Malaysia. He served as chair and finace chair for the IEEE Robotics&Automation chapter. He received the bachelor's degree in computer science in 1982 from Northeast Heavy Machinery Institute, Qinhuangdao, China, and the Ph.D. degree in computer vision in 1990 from the University of Leeds, Leeds, U.K. He has been teaching in Nanyang Tech. Univ. Singapore for 30 years. He organized and served as the General Chair for many conferences, such as the 10th Pacific-Rim Symposium on Image and Video Technology on 26th Nov 2022, Future Smart City IEREK on 18th Nov 2022, and as a Co-Chair for the upcoming 10th IEEE International Conferences on Cybernetics and Intelligent Systems and Robotics, Automation and Mechatronics (CIS-RAM) 2023. He has authored or co-authored more than 300 top-quality international conference and journal papers. His research interests include computer vision, artificial intelligence, and robotics.

Speech Title: Towards Vision Guided Unmanned Bus

Abstract: The talk is about unmanned bus using vision. The modules include:

? The objective  is to develop and implement a high speed, high accuracy stereo vision system and apply it onto an Unmanned Ground Vehicle (UGV).

? Currently UGV mainly uses expensive active sensors such as Lidar and Radar to provide ranging sensing.

? This project aims to deploy obstacle detection, recognition and tracking system, road feature detection, self-localization and mapping system into the all weather, all terrain unmanned autonomous vehicles with the help of stereo camera and graphics processing unit (GPU), so that it can run at speed from 15 km/h to 60 km/h.

Keynote Speaker Ⅱ

 Prof. Albert Bifet

University of Waikato, New Zealand

Biography: Albert Bifet is the Director of the Te Ipu o te Mahara AI Institute at the University of Waikato and Co-chair of the Artificial Intelligence Researchers Association (AIRA). His research focuses on Artificial Intelligence, Big Data Science, and Machine Learning for Data Streams. He is leading the TAIAO Environmental Data Science project and co-leading the open source projects MOA Massive On-line Analysis, StreamDM for Spark Streaming and SAMOA Scalable Advanced Massive Online Analysis. He is the co-author of a book on Machine Learning from Data Streams published at MIT Press. He is one of the winners of the best paper award at the ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT) 2023, and he will be the general co-chair of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) 2024.

Speech Title: Green AI

Abstract: AI is enhancing problem-solving capabilities in many sectors and augmenting research efficiency. However, as AI continues to grow in prevalence and power, it's crucial that we harness this technology in a manner that aligns with sustainability goals. Our presentation aims to provide a detailed overview of the latest research and future possibilities in Green AI. We will focus in the two main approaches to Green AI, using AI to solve sustainability challenges and using AI more sustainably. For the first approach, we will present the TAIAO research project in New Zealand, that is focused on solving environmental data science problems. The second approach to Green AI involves using AI in a more sustainable way, and we will introduce methods for machine learning for data streams, that are energy efficient.

Keynote Speaker Ⅲ 

 Prof. Weifeng Gao

Xidian University, China