Dr. Hooman Samani
University of Hertfordshire, UK
Biography: Dr. Hooman Samani is a Senior Lecturer in Robotics and Artificial Intelligence at the University of Hertfordshire, United Kingdom. He is the Fellow of Higher Education Academy (FHEA). He has worked as a Lecturer in Machine Learning, AI for Robotics at the, University of Plymouth, United Kingdom; Associate Professor and the founder and director of the AIART Lab (Artificial Intelligence and Robotics Technology Laboratory) at National Taipei University of Taiwan; Research Fellow at the Keio-NUS CUTE Centre, a joint research centre between National University of Singapore and Keio University of Japan; Engineer at Posco, South Korea and Robotics Researcher at Philips, The Netherlands and Fraunhofer, Germany. He holds a PhD degree in Robotics from the National University of Singapore.
Research Area:
Robotics
Artificial intelligence
AI for Robotics
Dr. Majid Taghavi
Imperial College London / Department of Bioengineering
Biography: Majid Taghavi recently joined Imperial College London to establish his interdisciplinary research group on Soft Robotic Transducers at the Department of Bioengineering. He aims to deliver the new generation of soft multifunctional actuators, sensors, and energy harvesting technologies, enabling monolithic soft robots for health applications. Prior to this, Majid was a postdoctoral researcher in SoftLab, university of Bristol, where he introduced multiple artificial muscle technologies. Majid was awarded his PhD in BioRobotics from Scuola Superiore Sant'Anna with the highest honor, receiving the Italian Institute of Technology scholarship, where he developed various electromechanical and bioelectrochemical energy harvesting and self-powered sensing technologies. He has background in Electronics and Micro-Electro-Mechanical Systems from K.N.Toosi and Tabriz universities in Iran, respectively.
Research Area:
Soft Robotics
Soft Transducers
Health Technologies
Smart Materials/Structures
Dr. Maria Elena Giannaccini
University of Aberdeen, UK
Biography: Dr Maria Elena Giannaccini's is a Lecturer in Robotics at the University of Aberdeen. She has a BEng and MSc in biomedical engineering and she obtained her PhD in Robotics at the Bristol Robotics Laboratory, UK as part of the Marie-Curie ITN project INTRO. Her research interests span the fields of robotics, mechatronics, variable stiffness structures for safety, and robot sensing applied to heathcare. During her decade of first-hand research activities she successfully designed and built robotic platforms for robotics, including co-designing an artificial implantable larynx at the University of Bristol. She was part of the team that won the 2016 Harvard Soft Robotics Toolkit Design Competition and she was editor and co-organiser of the 2018 Towards Autonomous Robotics Systems (TAROS) Conference. As PI she was awarded the University of Bristol Research Priming Funding, the Binks Trust funding for tactile sensing research with the Technical University of Munich, the Standard Innovation Voucher for wearable sensing devices and the follow-on KEC funded project. Elena was also Co-Investigator on the successful EPSRC Impact Acceleration bid for Neuromorphic Tactile Sensing and in the ESRC Steers Competition 2020/21, which resulted in the recruitment of a PhD student. She is currently supervising a PhD project focused on the design of a wearable device for the upper limb to rehabilitate stroke patients.
Research Area:
Soft robotics
Variable stiffness robotic systems
Assoc. Prof. Junliang Wang
Donghua University, China
Biography: Junliang Wang is an associate professor at Institute of Artificial Intelligence, Donghua University (DHU). He is the deputy director of Textile Industry Production Big Data Research Center of CTES, the deputy secretary general of the Industrial Big Data and Intelligent Systems Chapter of CMES, the committee member of Intelligent Simulation Optimization and Scheduling Chapter of CSF, the committee member of the Digital Twin Chapter of CGS.
His research interests mostly lie in the big data and intelligent manufacturing fields, by leveraging cutting-edge information technology and artificial intelligence techniques, to enable industries digital and intelligent transformation. He has continued to conduct in-depth research in the field of industrial big data analytics and has been funded by the Young Elite Scientists Sponsorship Program by CAST, the Natural Science Foundation of China, the Shanghai Sailing Program, the Shanghai Science and Technology Project and the Shanghai Chenguang Program. After receiving basic research fund, he has published more than 40 journal papers, authorized 11 Chinese patents and 11 software copyright. He has won two awards from provincial and ministerial science and technology progress and the Pearl award of the 4th China artificial intelligence and robot developers conference.
Research Area:
Machine Learning
Industrial Big Data
Intelligent Manufacturing Systems
Computer Vision and Pattern Recognition
Rongwei Jiang, Vice President
Valley Of Science And Technology Of China
Biography: Dr. Rongwei Jiang, co-founder and vice president of Valley Of Science And Technology Of China, executive director of Valley New Engineering Industry College, head of the cooperation project of Industry-University-Research Collaborative Education of the Ministry of Education, head of the training center of Valley Of Science And Technology Of China Teacher Research Institute. He has participated in many projects of National Natural Science Foundation of China and Anhui Provincial Key Fund, and personally owns many national invention patents and published more than ten papers in academic journals at home and abroad. He was the manager of product department of Texas Instruments (TI) Semiconductor Technology Co. He has rich experience in product design, marketing, school-enterprise cooperation and guidance of university students' electric competition, and has organized more than one hundred joint laboratories of schools and enterprises in key universities.
Research Area:
Robotics and Intelligent Manufacturing Engineering Talent Training
