Keynote Speakers
Prof. Hongmei (Mary) He
University of Salford, Manchester, UK
Title: The Challenges and Opportunities of Human-Centered AI for Trustworthy Robots and Autonomous Systems
Bio:
Discover the work of Hongmei (Mary) He, a Professor specializing in Future Robotics, Engineering, and Transport Systems at the University of Salford. With advanced degrees from Loughborough University, UK, and a background as a senior embedded system engineer at Motorola, China, Dr. Hongmei is at the forefront of AI research. Her expertise spans Cognitive Robotics, Cyber Security, Data/Sensor Fusion, and the safety of autonomous systems. An accomplished researcher, she has led numerous projects funded by top-tier institutions and has an extensive publication record. Dr. Hongmei also plays a significant role in the academic and professional community through her involvement with IEEE, the EPSRC peer-review college, and as a reviewer for the EU H2020 ICT Robotics Programme.
The trustworthiness of robots and autonomous systems (RAS) is at the centre of many research agendas on AI driven autonomous systems. This research systematically investigates for the first time the key aspects of human-centred AI (HAI) for trustworthy RAS in terms of safety, security, human-machine interaction, system health and ethics by identifying the challenges in implementing trustworthy autonomous systems with respect to the five key facets and exploring the role of AI in relation to the five facets of trustworthy RAS. It also presents a new acceptance model for RAS as a framework for human-centred AI requirements, promoting machine intelligence that augments human capabilities and places humans at the centre to achieve trustworthy RAS by design.
Prof. Bruno Agard
École Polytechnique, Université de Montréal, Canada
Title: Making Demand Predictions from Noisy Datasets
Bio:
He is currently a Professor in Department of Mathematics and Industrial Engineering, Ecole Polytechnique de Montréal, Canada. He received his doctoral degree at National School of Industrial Engineering – National Polytechnic Institue of Grenoble in Grenoble, France. And then, he became Assoc. Prof. at Department of Mathematics and Industrial Engineering, Ecole Polytechnique de Montreals in Montreal, Quebec, Canada from 2018-2014.
He has nearly 190 publications including journal articles, conference papers, book chapters or technical reports. So far, he has got 10 times of Meritas Prize from 2004 to 2022 and 3 Paper Awards which are: (2ème place à la compétition du jeune chercheur Prix Laurent Villeneuve), (Best Young researcher Paper Award) and (2ème au prix Mayoux-Dauriac 2011).
In the area of Industry 4.0, most companies plan to use artificial intelligence to enhance various internal processes that IA is supposed to learn directly from the databases. The knowledge is supposed to be in the dataset, but in many cases, the data itself contains a certain amount of noisy information (missing data, errors, …). In this context, we will show some strategies that have been implemented with real industrial partners in order to handle such situations. After a certain level of data preparation, the data is clustered in groups that share certain similarities, then a model is learned for the group and the prediction of the group is formatted for each specific element in the group.
Dr. Bill Wu (Wei William Wu)
Distinguished professor of Hangzhou Dianzi University, CEO of Cynoware
Title: AIoT: AI and IoT Integration
Bio:
Professor Wei Wu earned his Ph.D. in Industrial Computing from Université de Lille, France, and his Bachelor’s and Master’s degrees in Electrical Engineering from Wuhan University. With 35 years of experience in the U.S., France, and China, he has worked across both industry and academia. Currently, he is a distinguished professor at Hangzhou Dianzi University and remains actively engaged in both academic and industry sectors.
AI and IoT Integration elves into the powerful synergy between Artificial Intelligence (AI) and the Internet of Things (IoT) to develop smarter, more efficient systems. Attendees will explore key trends, such as edge computing, and examine practical applications across various industries, including hospitality, manufacturing, and agriculture. The workshop features case studies on using SIP phones for hotel room management, AIoT in textile manufacturing for process optimization, and AI-driven fruit recognition in supermarkets. Additionally, it addresses challenges like data privacy and scalability while offering insights into future trends, providing participants with the knowledge needed to drive innovation in their respective fields.
Prof. Xianyi Zeng
ENSAIT Textile Engineer School, GEMTEX, University of Lille, France
Title: Development of intelligent garments for online monitoring of human health
Bio:
Xianyi Zeng is a full professor (exceptional class – grade 2) at ENSAIT Textile Engineer School – University of Lille, France, and Director of the GEMTEX National Laboratory.
He has been an IEEE senior member since 2011 and led the Theme on Human-Machine Systems in GRAISyHM (regional association of Researchers on Automation) since 2013. He has had the French National Knight’s title in the Order of the Academic Palms since 2019 and was the holder of the Innovation R&D Award from the France-China Committee, and the EU Key Innovation Team Award from the EU Innovation Radar, both in 2021. He was awarded Top-10 Innovation Leader of Overseas Chinese in Europe in 2022. In ENSAIT, he has been a leader of the Department of Fashion and Service Engineering since 2009.
Xianyi Zeng has published more than 160 papers in peer-reviewed international journals, presented more than 260 papers at international conferences, and supervised more than 40 PhD students. In addition, as a principal investigator, he has led three European projects (Asia-Link: 2004-2008), SMDTex – European Joint Doctorate Program on Textile Sustainable Design and Management (Erasmus Mundus Program: 2013 – 2021), FBD_BModel – Fashion big data and business model (H2020 Program: 2017-2021) and several national and regional research projects such as IOTFetMov (ANR Program: 2015 – 2019), Camille 3D (FUI Program: 2012 – 2015), SUCRE (ARCIR Program: 2013 – 2017) and industrial projects in France and Europe.
In this presentation, we propose a series of principles for designing intelligent and connected garments for online human health monitoring, including textile/garment design, electronic devices integration, local decision support system development. These principles will permit to enhance product autonomy and intelligence level and fully integrate devices into textiles. The proposed garment design process can be more adapted to customized body shapes of the target population and is capable of selecting the most relevant fabrics and garment patterns for minimizing signal attenuation and improving wearer’s comfort. Also, the integrated physiological sensors are connected to a centralized microcontroller, on which an intelligent algorithm is implemented for filtering noises, extracting relevant features from measured signals and intelligently interacting with the cloud platform. Two specific applications (i.e. fetal movement monitoring and COVID-19 symptom evaluation) have been proposed to show how intelligent garments are integrated into the patient’s lifestyle for long-term continuous health care.
Prof. Victor Chang
Aston University, United Kingdom
Title: Development of intelligent garments for online monitoring of human health
Bio:
Prof. Victor Chang is currently a Professor of Business Analytics at Aston Business School, Aston University, UK. He was a Professor of Data Science and Information Systems at SCEDT, Teesside University, Middlesbrough, UK, between September 2019 and May 2022. He was a Senior Associate Professor, Director of Ph.D. (June 2016- May 2018) and Director of MRes (Sep 2017 – Feb 2019) at International Business School Suzhou (IBSS), Xi’an Jiaotong-Liverpool University (XJTLU), Suzhou, China, between June 2016 and August 2019. He was also a very active and contributing key member at Research Institute of Big Data Analytics (RIBDA), XJTLU. He was an Honorary Associate Professor at University of Liverpool. Previously he was a Senior Lecturer at Leeds Beckett University, UK, between Sep 2012 and May 2016. Within 4 years, he completed Ph.D. (CS, Southampton) and PGCert (Higher Education, Fellow, Greenwich) while working for several projects at the same time. Before becoming an academic, he has achieved 97% on average in 27 IT certifications. He won a European Award on Cloud Migration in 2011, IEEE Outstanding Service Award in 2015, best papers in 2012, 2015 and 2018, the 2016 European special award and Outstanding Young Scientist 2017. He is a visiting scholar/Ph.D. examiner at several universities, an Editor-in-Chief of IJOCI & OJBD journals, former Editor of FGCS, Associate Editor of IEEE TII, JGIM, IJBSR, IJEBM & Cyber Security & Apps. He’s also an Editor of Information Fusion, IDD and Scientific Reports journal, a founding chair of two international workshops and founding Conference Chair of IoTBDS and COMPLEXIS since Year 2016. He is the founding Conference Chair for FEMIB since Year 2019. He published 3 books as sole authors and the editor of 2 books on Cloud Computing and related technologies. He gave 48 keynotes at international conferences. He is widely regarded as one of the most active and influential young scientists and experts in IoT/Data Science/Cloud/security/AI/IS, as he has experience developing 10 different services for multiple disciplines.
