Prof. Dan Pan

Guangdong Polytechnic Normal University, China

Introduction: Dan Pan, male, holds a Ph.D. in Circuits and Systems with concentration on Intelligent Computer from South China University of Technology, as well as an MBA from Sobey School of Business, Canada.

Currently, serving as a Full Professor in Signal and Information Processing, Senior Engineer, and Master’s Supervisor, Dr. Pan teaches in the Department of Intelligent Science and Technology at the School of Electronics and Information, Guangdong Polytechnic Normal University. His research focuses on artificial intelligence and its applications across various domains, including biomedical engineering and manufacturing. Dr. Pan has long been engaged in theories, methods, and applications in artificial intelligence, machine learning, big data, and software engineering.

He is also a committee member of the Alzheimer's Disease Division of the Guangdong Society of Precision Medicine Applications and previously held the same role in the Medical Robotics and Artificial Intelligence Division of the Guangdong Society of Biomedical Engineering. He currently serves as an external supervisor for master's students at the School of Computer Science and Technology, Guangdong University of Technology, and an enterprise advisor for master's students in electronic information at the Guangzhou Institute of Xi'an University of Electronic Science and Technology.

Title: Deep Learning for Brain MRI Confirms Patterned Pathological Progression in Alzheimer’s Disease

Abstract: Deep learning (DL) on brain magnetic resonance imaging (MRI) data has shown excellent performance in differentiating individuals with Alzheimer’s disease (AD). However, the value of DL in detecting progressive structural MRI (sMRI) abnormalities linked to AD pathology has yet to be established. In this study, an interpretable DL algorithm named the Ensemble of 3-dimensional convolutional neural network (Ensemble 3DCNN) with enhanced parsing techniques is proposed to investigate the longitudinal trajectories of whole-brain sMRI changes denoting AD onset and progression. A set of 2,369 T1-weighted images from the multi-centre Alzheimer’s Disease Neuroimaging Initiative and Open Access Series of Imaging Studies cohorts are applied to model derivation, validation, testing, and pattern analysis. An Ensemble-3DCNN-based P-score is generated, based on which multiple brain regions, including amygdala, insular, parahippocampal, and temporal gyrus, exhibit early and connected progressive neurodegeneration. Complex individual variability in the sMRI is also observed. This study combining non-invasive sMRI and interpretable DL in detecting patterned sMRI changes confirmed AD pathological progression, shedding new light on predicting AD progression using whole-brain sMRI. 

Prof. Xu Chen

Winner of National Science Fund for Distinguished Young Scholars of China

Zhongshan University, China

Introduction: 陈旭，中山大学计算机学院教授、担任先进网络与计算系统研究所所长以及国家地方联合工程实验室副主任，入选德国洪堡学者、国家级青年人才项目和广东省高层次人才项目。承担包括国家自然科学基金联合重点项目、NSFC-广东省大数据中心项目、国家重点研发计划、广东省创新团队等项目与课题。曾获得IEEE Distinguished Lecturer、香港青年科学家奖、IEEE计算机学会年度最佳论文奖亚军， IEEE INFOCOM/IWQoS/ICC最佳论文奖项等学术荣誉。目前担任国际知名期刊IEEE JSAC Series、TWC、TVT、中国工程院信息院刊等编委。

Title: 高效边缘大模型协同推理与微调技术

Abstract: 以ChatGPT为代表的AIGC应用崛起，在全球范围内掀起了一场关于大模型的竞速赛，由此导致AI算力需求急速攀升。边缘算力在成本、时延、隐私上具有天然优势，可作为云端算力的补充可，更好支撑大模型赋能千行百业。本报告将介绍边缘大模型多设备高效协同推理和分布式微调技术，以及边缘大模型赋能的网联智能无人系统应用。

Prof. Xuemiao Xu

Vice Dean of the School of Computer Science and Engineering

South China University of Technology, China

Introduction: 徐雪妙博士,现为华南理工大学计算机科学与工程学院教授、博导、副院长，广州国际校区峻德书院副院长，广东省大模型与生成式人工智能工程技术研究中心主任，广东省卓越青年团队牵头人，广东省特支青年拔尖人才，珠江科技新星。徐教授博士毕业于香港中文大学，研究方向为视觉智能、图形图像处理，及其在智能制造、智能交通等领域的应用。近年在国际重要期刊和会议发表论文100余篇，其中以第一或通信作者发表CCF A/Trans.论文50余篇，ESI高被引论文3篇；主持国家重点研发、国家自然科学基金、广东省及广州市重大专项等项目共15项，以第一完成人获得2022年中国图象图形学会科技进步二等奖，及2021年广东省科技进步二等奖。

Title: 基于知识引导的场景智能理解和生成技术

Abstract: 数据与知识的双轮驱动已成为人工智能发展的重要趋势之一。报告将面向工业场景，围绕视觉技术在实际应用中面临的场景复杂多变、数据缺失且质量不可控等难题，介绍一系列基于知识引导的场景智能理解和生成创新技术。

Prof. David Bassir

Dongguan University of Technology, China

Introduction: David BASSIR is as Professor at the French University of Technology UTBM and also a Senior Research at Ecole Normal Superieur ENS- Paris Saclay University. Previously, he was the dean of IUT at the University of Lorraine (France), Consult for Science and Technology at the French Embassy to serve at the Consulate General of France in Guangzhou (China), General Director of Research at the Ecole Spéciale des Travaux Publics, du Batiment et de l'Industrie (Paris) and Space Craft engineer at GECI Technology in different space agencies such as Arianespace and Astrium Group. He joined the mechanical department of the UTBM as associate professor in 2001 and the Chair Aerospace Structures in 2008 at Technical University of Delft as visiting professor. He holds a Master and a PhD degree in structural optimization from the University of Franche-Comté (France). He has published more than 150 papers in journals, books and conference proceedings, including more than 56 articles in indexed journals. He is also the Editor-in-Chief of the Int. journal IJSMDO (Scopus, EI) that is published by EDP Sciences.