Prof. Robert Minasian, IEEE Life Fellow, OSA Fellow, Fellow of The Royal Society of NSW
The University of Sydney, Australia

Professor Minasian is a Chair Professor with the School of Electrical and Information Engineering at the University of Sydney, Australia. He is also the Founding Director of the Fibre-optics and Photonics Laboratory. His research has made key contributions to microwave photonic signal processing. He is recognized as an author of one of the top 1% most highly cited papers in his field worldwide. Professor Minasian has contributed over 420 research publications, including Invited Papers in the IEEE Transactions and Journals. He has over 100 Plenary, Keynote and Invited Talks at international conferences. He has served on numerous technical and steering committees of international conferences. Professor Minasian was the recipient of the ATERB Medal for Outstanding Investigator in Telecommunications, awarded by the Australian Telecommunications and Electronics Research Board. He is a Life Fellow of the IEEE, a Fellow of the European Academy of Sciences, a Fellow of the Optical Society of America (now Optica), and a Fellow of The Royal Society of NSW.

(Online) Speech Title: Progress in Integrated Photonic Signal Processing and Sensing

Prof. Shuqiang Jiang, University of CAS, China

Professor JIANG Shuqiang, is a researcher and doctoral supervisor with Institute of Computing Technology, Chinese Academy of Sciences (CAS), and professor in University of CAS. His research interests include multimedia content analysis and retrieval, multimodal embodied AI and food computing. He has authored or coauthored more than 200 papers and 20 authorized patents. He was supported by National Science Fund for Distinguished Young Scholars in 2021, NSFC Excellent Young Scientists Fund in 2013, Young top-notch talent of Ten Thousand Talent Program in 2014. He successively serves as editorial broad member of IEEE Transactions on Multimedia (IEEE TMM), ACM Transactions on Multimedia Computing Communications and Applications (ACM ToMM), IEEE Multimedia, Journal of Computer Research and Development, Journal of Computer Science and Technology etc.. He is the vice chair of IEEE CAS Beijing Chapter and vice chair of ACM SIGMM China chapter. He is the deputy director of CCF TC-Multimedia Technology, CAAI PC-Intelligent Service, CAA TC-Network Computing.

蒋树强，中国科学院计算技术研究所研究员，博士生导师，国家杰出青年科学基金获得者，先后担任期刊《IEEE TMM》、《ACM ToMM》、《IEEE Multimedia》、《计算机研究与发展》、《JCST》、《CAD学报》编委，中国计算机学会多媒体专委会副主任、中国人工智能学会智能服务专委会副主任、中国自动化学会网络计算专委会副主任、ACM SIGMM中国分会副主席。主要研究方向是多媒体内容分析、多模态具身智能技术和食品计算。主持承担科技创新2030-“新一代人工智能”重大项目、国家自然科学基金等项目20余项，发表论文200余篇，获授权专利20余项，多项技术应用到实际系统中，先后获省部级或学会奖励5项。

(Onsite) Speech Title: Visual Navigation in Embodied Intelligence
Abstract: Embodied intelligence refers to intelligence achieved through interactions between the body and the environment, which has the characteristics of proactivity, interactivity and contextualization. It is an important manifestation of artificial intelligence in real physical scenarios, with significant potential applications in autonomous systems and human-machine collaboration systems within dynamic and open environments. Visual navigation is one of key tasks in embodied intelligence and fundamental capabilities for intelligent systems operating in the real world. In static and fully explorable environments, with the help of map positioning, intelligent systems can achieve satisfactory navigation performance. However, in dynamic and unknown environments, existing technologies struggle to navigate efficiently due to the lack of accurate maps.
Compared to machines, humans rely on prior knowledge of targets, and can efficiently search for and navigate to target objects in unknown dynamic environments. Additionally, physiological studies show that human, in navigation, not only depend on current exploratory observations but can also anticipate unobserved environments based on previous memories. That is, humans continuously refine and improve their understanding of the environment by combining exploration with anticipation.
This talk will first introduce the research background, current status, and trends in embodied intelligence, followed by an overview of advancements in visual navigation technology. Topics covered will include category-level/instance-level object navigation, single-object/multi-object navigation, object navigation/vision-language navigation, and embodied navigation that combines exploration with anticipation. Additionally, it will discuss the adaptation of object navigation from virtual to real environments and provide demonstrations.

Prof. Chong SHEN, Deputy Dean, School of Electronics Science and Technology
Principle Investigator, State key lab of marine resource utilisation of South China Sea
Hainan University, China

Member IEEE, Senior member IET/IEEE VTS, China State Council special allowance receiver. He gets BE of Telecommunications from Wuhan University China 2003, EEE MPhil from University of Strathclyde Scotland 2005 and EEE PhD from Munster Technological University Ireland 2008, respectively. He also serves as a Post-doc researcher at Tyndall National Institute Ireland 2009 and senior research engineer at Bell Labs Dublin Ireland 2020. He joined School of Electrical Engineering Wuhan University as a lecturer and now with Hainan University as Full time Level 2 Professor about 12 years. His research interests include micro-systems, indoor locationing chips development, coordinated marine communications, IoT and etc. Now he has published more than 150 research papers including IEEE trans on VT, IEEE trans on Coms, IEEE Sensors Journal and etc. He also owns more than 50 IPs and serves as PI of 40 plus International, national projects. He also receives 2nd place Hainan province Science and Technology Awards(1 candidate) 2015,  2nd place Hainan province Science and Technology Awards(1 candidate) 2018 ，1st place Hainan province Science and Technology Awards(1 candidate) 2021and 1st place Hainan province Science and Technology Awards(4 candidate) 2022.

(Onsite) Speech Title: UWB Indoor Locationing Chip Design and Applications

Abstract: Ultra-Wide-Band (UWB) technology is an advanced wireless communication method that enables high data transmission rates and precise localization by utilizing a broad frequency spectrum. As UWB technology continues to evolve, its 2B market is becoming increasingly saturated. However, there is a promising outlook for consumer-oriented applications, particularly in smart home systems and smart wearable products and so on. Leveraging its robust replicability, significant demand, and exceptionally low operating costs, its market potential is board.
We aim at the smart hardware market by utilizing System-in-Package (SiP) technology to integrate various technologies such as BLE and UWB. This approach has enabled us to develop a series of chips designed for multiple application scenarios, including smart remote controls, smart homes, and wearable devices. Simultaneously, we ensure that these chips maintain lower costs and smaller sizes, aligning with the prevailing market demands.

Prof. Jun Wan, National Laboratory of Pattern Recognition, CASIA

Jun Wan (http://www.cbsr.ia.ac.cn/users/jwan or http://people.ucas.ac.cn/~jwan) received his B.S. degree from the China University of Geosciences, Beijing, China, in 2008, and the PhD degree from the Institute of Information Science, Beijing Jiaotong University, Beijing, China, in 2015. Since January 2015, he has been a Faculty Member with the National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China, where he currently serves as a professor. His main research interests include computer vision and machine learning, especially for biometrics security, gesture/action recognition and facial attribution analysis. He is an associate editor of the IEEE Transactions on Information Forensics & Security (2024-) and IET Biometrics (2020-). He has served as co-editor of special issues in IEEE TPAMI, IJCV, and IEEE TBIOM. He also has served as the Area Chair of ICME 2021-2024, MM 2024, ICME 2024, ICPR 2024 and Senior Program Committee of AAAI 2022. He is the member of the board of directors of ChaLearn. He has been involved in the organization of several challenges and workshops collocated with top venues in computer vision, like ICCV 2017, CVPR 2019, CVPR 2020, ICCV2021, CVPR 2023, CVPR 2024.

(Onsite) Speech Title: TBA

Di Guo, Beijing University of Posts and Telecommunications, China

Di Guo is a Professor with the School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing. Her research interests include intelligent robot, computer vision, and machine learning. She serves as the Associate Editor of ICRA and IROS. She is an Area Chair of RSS.

(Onsite) Speech Title: Embodied Multi-robot Collaboration 

Abstract: In recent years, multi-robot system has received increasing attention and has been widely used in many scenarios such as logistics, industrial manufacturing, etc. Compared with single robot, multi-robot system is more robust to complicated tasks and dynamic environment. This talk will introduce typical embodied multi-robot collaboration tasks from the aspects of task decomposition, task allocation, and task planning.

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