（一）
报告时间：3月26日（星期三）上午 11:00-11:30
报告地点：东湖国际会议中心
报 告 人：Jianye Hao，Huawei Noah's Ark Decision-Making and Reasoning LAB, China
报告题目：Reinforcement Learning in the Era of Large Models
内容简介：This talk will first introduce the background and fundamentals of traditional reinforcement learning, followed by emerging learning paradigms for decision-making models in the era of large models. It will explore how reinforcement learning facilitates decision-making models, including associated challenges and solutions, while showcasing practical applications in autonomous driving, EDA chip design, embodied intelligence, and other domains.
报告人简介：Jianye Hao is the Director of Huawei Noah's Ark Decision-making and Reasoning Lab and a Professor at Tianjin University. His research focuses on deep reinforcement learning and multi-agent systems. He has published over 150 papers in top AI conferences and journals and authored two monographs. He has received prestigious grants, including the NSFC Excellent Young Scholar Program and China’s national AI major projects. His work has earned three Best Paper Awards and multiple championships in NeurIPS competitions. His research has been applied in areas such as industrial software, autonomous driving, game AI, recommendation systems, 5G optimization, and logistics scheduling.
（二）
报告时间：3月26日（星期三）上午 11:30-12:00
报告地点：东湖国际会议中心
报 告 人：Pengcheng Huang，ABB, Switzerlan
报告题目：Advancing Industrial Analytics: A Story of Optimized Sensor Analytics and Intelligent Services
内容简介：Industrial data primarily originates from two sources: sensory data from device monitoring and documents from products and workflows. Sensory data is crucial for predictive maintenance, while document data supports the development of knowledge bases and intelligent services. This presentation highlights ABB’s research efforts to advance industrial analytics in both areas. We explore strategies to optimize sensor analytics for industrial devices, addressing constraints in memory, energy, and computational resources. Additionally, we demonstrate how industrial documents can be utilized to build comprehensive knowledge databases, enabling more advanced intelligent services. We will discuss the challenges and opportunities in both domains, emphasizing potential synergies for future exploration.
报告人简介：Pengcheng Huang is an Industrial Scientist at ABB. His work primarily focuses on automating cost-effective edge analytics for industrial asset management and developing intelligent industrial services utilizing language models. He holds a PhD from ETH Zurich.
（三）
报告时间：3月26日（星期三）上午 12:00-12:30
报告地点：东湖国际会议中心
报 告 人：Daniel Chu，Optikom, China
报告题目：ENAS - An AI Driven Next Generation Industrial Control System
内容简介：ENAS (Edge Networking Automation System) is a newly-designed and developed cloud-edge coordinating industrial control system tailored for mobile applications of large-scale, mega-scale manufacturing enterprises with multiple sites and complicated processes to streamline high efficient operation and management business. It is empowered with fast data collecting and protocol decoding applications, and algorithm processing applications such as small-scale APC, 2-dimension APC for cross section control, AI NN training with multiple choices of hardware support of computing capabilities. Meanwhile at cloud-side, a full-feature data center acting as interface for multiple edge applications with cloud-SaaS service. Furthermore, cloud-side also provides device management and smart industrial applications such as modelling, process simulation, optimization, intelligent control, expert scripts, group scheduling services. ENAS with flattened architecture, and flexible configuration with edge and cloud functions, not only improves the stability, reliability and scalability of industrial control system, but also speed-up implementation time span and saves cost with built-in registration and software automation for configuration of ECMs. The ENAS product family consists of ECMs (with five types), Cloud-management (ENAS backend), system application service (ENAS front-end), ENAS mobile configuration App and ECM mobile monitor App. With decentralized design philosophy to replacing traditional PLC/DCS, ENAS deployment is truly pocket control center. Optikom’s ENAS family of products has been deployed in multiple industrial sectors, such as new energy, railway transportation, nuclear material, food manufacturing, motor factories, with closed-loop control, modelling, simulation, and AI based model training and service.
报告人简介：Daniel Chu is the founder and CEO of Xiamen Optimal Process Control Technology Ltd. Co. (a.k.a Optikom), a Professor-level Senior Engineer, an adjunct Professor and Ph.D. supervisor of Harbin Inst. of Technology, an adjunct professor and master supervisor of XAUST. He is also been awarded as “Top one hundred Entrepreneur of Fujian Province” and “Top two hundred entrepreneur of Xiamen City”, a Senior IEEE member, Professional Engineer of BC. Dr. Chu has been approved 6 US Invention Patents, 12 Chinese Invention Patents, 5 Chinese Utility model patents, and published above 20 core research papers in top control journals. Dr. Chu graduated from University of Alberta in year 2006 with his doctor degree on industrial control systems, and joined Honeywell Canada right after graduation as a senior research scientist for 8 years. He has been worked on model predictive control and other intelligent control algorithm development and industrial implementation. During his 8 years with Honeywell, he has led multiple international cross disciplinary projects in Canada, United States, Finland, Sweden and Mexico. Developed software with advance algorithms was deployed in thousands of projects generating million dollars of profit for multiple customers. Dr. Chu left Honeywell Canada as chief research scientist in paper a pulp business unit in 2013, and founded Xiamen Optikom. He has led an energetic R&D team and marketing team, learning the technology demand of domestic customers and developed a full-suite of software and hardware products for industrial control applications, including intelligent control and optimization algorithms, cloud-based platform, smart sensors.
（四）
报告时间：3月27日（星期四）上午 10:30-11:00
报告地点：东湖国际会议中心
报 告 人：Zhiwu Zhang，China Metallurgical Geology Bureau, China
报告题目：Presentation Title: Advances and Prospects in Future Exploration Systems
内容简介：In response to current challenges in solid mineral exploration, the China Metallurgical Geology Bureau, the sole central state-owned enterprise specializing in geological exploration—has initiated the development of the Future Exploration System. This innovative framework integrates digitalization, informatization, and artificial intelligence (AI) to revolutionize traditional exploration methodologies. Key focuses include Green and intelligent transformation of conventional techniques such as geological, geophysical, geochemical, and remote sensing surveys; Automation and intelligence in analytical testing and drilling technologies; Smart management of geological big data; AI-driven prospecting prediction for enhanced accuracy and efficiency. The system aims to achieve disruptive advancements in mineral exploration by prioritizing sustainability, precision, efficiency, and deep-earth capabilities, thereby elevating the quality and productivity of the geological exploration industry.
报告人简介：Zhiwu Zhang is a Senior Engineer and holds a Ph.D. degree. He currently serves as the General Manager of the Science and Technology Innovation Department at China Metallurgical Geological Bureau (CMGB). He acts as Secretary-General of the Metallurgical Geology Branch of the Chinese Society for Metals and Deputy Director of the Science and Technology Information Special Committee of the Geological Society of China. Dr. Zhang has led and participated in over ten national and provincial-level scientific research projects, including those under the 12th Five-Year Plan and the National Natural Science Foundation of China. He has authored more than 20 publications indexed in SCI and EI journals and was honored with the "Top Ten Scientific and Technological Advancements of 2019" award by the Geological Society of China.
（五）
报告时间：3月27日（星期四）上午 11:00-11:30
报告地点：东湖国际会议中心
报 告 人：Jiandong Wang，Shandong University of Science and Technology
报告题目：Optimal Design of Multivariate Alarm Systems Based on Normal Operating Zones
内容简介：For modern industrial processes, normal or abnormal operating conditions can be revealed from multiple correlated process variables. Thus, it is indispensable to take the relationship among these process variables in the optimization design of alarm systems. Doing so can also reduce false alarms or missed alarms from univariate alarm systems. Based on the mechanism knowledge, historical data, and safety requirements of industrial processes, a geometric space is obtained as the allowable variation range of multiple process variables under normal operating conditions, and a normal operating zone model is established for the geometric space together with its uncertainty ranges. A multivariable alarm system is designed based on the normal operating zone to monitor the safety and economy performance of industrial processes. The effectiveness and practicality of the designed alarm system are illustrated via experimental and industrial examples on a three-water tank experimental device and a thermal power generation unit.
报告人简介：Jiandong Wang is presently a full professor of College of Electrical Engineering and Automation at the Shandong University of Science and Technology, Qingdao, China. He received a B.E. in automatic control from Beijing University of Chemical Technology, Beijing, China, in 1997, and an M.Sc and Ph.D. in Electrical and Computer Engineering from the University of Alberta, Canada, in 2003 and 2007, respectively. From 1997 to 2001, he was a Control Engineer with the Beijing Tsinghua Energy Simulation Company, Beijing, China. From February 2006 to August 2006, he was a Visiting Scholar at the Department of System Design Engineering at the Keio University, Japan. From December 2006 to October 2016, he was an assistant/associate/full Professor with the College of Engineering, Peking University, China. His research interests include system identification, industrial alarm systems, optimal scheduling and their applications to industrial problems. Dr. Wang has served as an Associate Editor/Guest Editor for Journal of the Franklin Institute, Systems and Control Letters, and Control Engineering Practice.
（六）
报告时间：3月27日（星期四）上午 11:30-12:00
报告地点：东湖国际会议中心
报 告 人：Youzhen Zhang，CCTEG Xi’an Research Institute (Group) Co. Ltd., China
报告题目：Intelligent Optimization and Control Technology for Drilling Process of Underground Coal Mines
内容简介：The study was conducted from intelligent identification of lithology of coal-bearing formation, intelligent optimization of drilling parameters and their intelligent control, focusing on the key technology for control of drilling process of underground coal mine.
报告人简介：Youzhen Zhang received the B.S. degree from Xian University of Science and Technology in 1999, the M.S. degree from Xian University of Science and Technology in 2005, and the Ph.D. degree from China Coal Research Institute in 2012. Since 2015, he has been a Research fellow in CCTEG Xian Research Institute (Group) Co., Ltd.
（七）
报告时间：3月28日（星期五）上午 10:30-11:00
报告地点：东湖国际会议中心
报 告 人：Honglin Li，Dongfeng Motor Company, China
报告题目：AI-Driven Evolution of Intelligent Driving Technologies
内容简介：This presentation will analyze how AI technologies are reshaping the trajectory of intelligent driving systems. We begin by reviewing key milestones in autonomous driving, emphasizing paradigm shifts driven by AI breakthroughs—from modular rule-based architectures to end-to-end AI systems and vision-language-action models (VLMs) that enable semantic scene understanding (e.g., traffic sign interpretation, intent prediction). It will then introduce Dongfeng Motor Company's strategic planning and practical implementations in the field of intelligent driving, sharing its exploratory achievements in deploying autonomous driving technologies and advancing embodied intelligence in vehicles. Finally, we will outline future trends in intelligent driving by addressing industry challenges and opportunities, and discuss how technological innovation and cross-sector collaboration can drive continuous progress across the intelligent driving ecosystem.
报告人简介：Honglin Li is currently the chief engineer of intelligent vehicle technology at Dongfeng Motor Corporation. With 22 years of experience in the automotive industry, he has extensively worked on vehicle design and intelligent driving system. He has led the development of intelligent driving systems for multiple vehicle models at Dongfeng. Currently, he serves as the chair of the professional technical committee on Intelligent and Connected Vehicle. He is also an expert on the National Automotive Standardization Technical Committee's Intelligent and Connected Vehicle Subcommittee WP.29 GRVA International Standards and Regulations Coordination, a standing member of the IEEE China Technical Committee PES Subcommittee, and a professional master's advisor at Wuhan University of Technology.
（八）
报告时间：3月28日（星期五）上午 11:00-11:30
报告地点：东湖国际会议中心
报 告 人：Kang Liu，Mutus-tech, UK
报告题目：Mutus-tech: Pioneering AI Solutions for Agriculture 4.0
内容简介：Mutus-tech is a leading agricultural AI company specializing in precision farming, pest management, and sustainable agriculture through advanced machine learning, computer vision, and IoT technologies. With multiple Innovate UK-funded projects, the company has developed cutting-edge solutions for mobile pest detection, climate-smart fertilization, and real-time soil health monitoring to enhance productivity while reducing environmental impact. Collaborating with major UK agricultural players like ADAS and Velcourt, Mutus-tech is driving the transformation of traditional farming into a technology-driven ecosystem. Their AI-powered solutions are not only reshaping UK agriculture but also expanding globally to regions such as India, Africa, and Argentina. At ICIT, Mutus-tech will showcase its latest innovations, highlighting AI’s role in the future of sustainable farming.
报告人简介：Kang Liu received the Ph.D. in Control Science and Engineering from the University of Science and Technology of China. He is currently a Senior Research Scientist at Mutus-tech in the UK. Before joining Mutus-tech, he was a Research Fellow in the Department of Computer Science at the University of Sheffield, UK. He is currently focused on integrating AI technology, intelligent control, and autonomous robotics to advance applications in smart agriculture, building inspection, and other fields. His work aims to drive industry-wide intelligent transformation, enhance productivity, and promote sustainability.
（九）
报告时间：3月28日（星期五）上午 11:30-12:00
报告地点：东湖国际会议中心
报 告 人：Jianbo Zhai，China ENFI Engineering Corporation, China
报告题目：Exploration and Practice of Intelligent Mine Construction Model
内容简介：China ENFI, a subsidiary of China Minmetals Corporation, has pioneered the MIM+ system (Mining Information Modeling) — an integrated framework encompassing digital design, digital delivery and CoPlat, digital twins, and other core technologies across exploration, design, construction, and operational phases. The company proposed the “1+1+N” intelligent mine architecture, which synergizes 3D geological modeling, automated mining equipment, unmanned transport systems, centralized intelligent control centers, and multi-source data fusion networks to deliver a comprehensive digital solution spanning the entire lifecycle of mining operations. This model has been successfully implemented multiple engineering applications, including unmanned underground operations, intelligent control systems, integrated operational platforms, real-time safety risk monitoring, and digital delivery solutions used in both domestic and international mining projects. These innovations are accelerating the mining industry’s transition toward “transparent, digitized, and intelligent”, enhancing safety, efficiency, and sustainability across the mine life cycle.
报告人简介：Jianbo Zhai has been engaged in mining consulting, design and general contracting projects at China ENFI Engineering Corporation. He has successively taken charge of the management of more than 20 projects and served as lead engineer in charge for the design of over 60 projects, and participated in more than 10 technical research & development and business construction tasks, including national key research and development projects. He has successively won 1 first prize, 3 second prizes, and 2 third prizes at the ministerial level, and has applied for 26 patents, published 22 papers, compiled 3 standards, and obtained 5 national registration certificates.
