Prof. Danica Kragic (IEEE Fellow)

Royal Institute of Technology KTH, Sweden

Speech title: Learning for interaction in robotic tasks

Danica Kragic is a Professor at the School of Computer Science and Communication at the Royal Institute of Technology, KTH. She received MSc in Mechanical Engineering from the Technical University of Rijeka, Croatia in 1995 and PhD in Computer Science from KTH in 2001. She has been a visiting researcher at Columbia University, Johns Hopkins University and INRIA Rennes. She is the Director of the Centre for Autonomous Systems. Danica received the 2007 IEEE Robotics and Automation Society Early Academic Career Award. She is a member of the Royal Swedish Academy of Sciences, Royal Swedish Academy of Engineering Sciences and Young Academy of Sweden. She holds a Honorary Doctorate from the Lappeenranta University of Technology. Her research is in the area of robotics, computer vision and machine learning. She received ERC Starting and Advanced Grant. Her research is supported by the EU, Knut and Alice Wallenberg Foundation, Swedish Foundation for Strategic Research and Swedish Research Council. She is an IEEE Fellow.

Prof. Kiyoshi Ohishi (IEEE Fellow)

Nagaoka University of Technology, Japan

His research interests include mechatronics, robotics, and power electronics. He is an administration comittee member of the IEEE Industrial Electronics Society (IEEE IES), the Institute of Electrical Engineers of Japan (IEEJ), the Robotics Society of Japan (RSJ), the Society of Instrument and Control Engineers (SICE), and the Japan Society of Mechanical Engineers (JSME).

Jingsong Li

Dalian University of Technology, China

Jingsong Li, male, born in 1987, received the Ph.D. degree from the Hebei University of Technology, Tianjin, China, in 2017, and became a Postdoctoral Fellow with Tsinghua University, Beijing, China, during 2017-2019, all in electrical engineering. He is currently an associate professor in Dalian University of Technology, Dalian, China. His research interests include Energy Storage Transformer, Submarine Cable Detection, magnetic losses characteristics modeling and measurement analysis and application of magnetic materials in electrical engineering, and analysis of high-frequency electromagnetic vibration and noise characteristics of electrical equipment. He was selected as Outstanding Young Scientific and Technological Talents of Liaoning Province in 2022. Focusing on the major national demand for large-scale energy storage and advanced manufacturing of intelligent equipment in multi-application scenarios and multi-objective planning in the new energy power system, he is committed to the research and development of theories, technologies, software and hardware systems for electrical equipment performance evolution, load matching, energy conservation and consumption reduction, and have presided over or completed more than 10 projects (topics) such as the National Natural Science Foundation of China, China Postdoctoral Science Fund, provincial (ministerial), municipal and enterprise cooperation projects. Over the past five years, the total amount of funding has reached more than ¥13 million. He has published more than 20 relevant academic papers, 8 authorized national patents (including 3 invention patents), 6 invited reports at international (domestic) academic conferences, participated in the formulation of 2 industry standards, and 1 unique technology application has been gradually put into the market.

A. Prof. Qiushi Cui

ChongqingUniversity, China

Dr. Qiushi Cui, Vice Chair of Web Forum Task Force, Big Data Analytics Committee, IEEE Power and Energy Society, and Founding Chair of Big Data Mentoring Forum Series. He graduated from Illinois Institute of Technology (IIT) and McGill University (McGill) in 2012 and 2017, respectively, and has worked as R&D engineer and postdoctoral researcher at Opal Real Time Simulation (OPAL-RT) in Canada and Arizona State University (ASU) in USA. His research is closely integrated with artificial intelligence, big data, power system and new energy grid integration, and his main research interests include power system artificial intelligence, power system protection and control, integrated energy system, electric vehicle grid integration, and grid real-time simulation and modeling.

Prof. Xiaomin Kang,

University of South China, China

He achieved his bachelor and Ph.D degree in Material Sciecne and Engineering, Southwest Jiaotong University in 2011 and 2017, respectively. After graduation, he further served as a postdoctor and research fellow in Prof. Luo Jinglli’s group (Fellow of the Canadian Academay of Engineering) to fulfil his job in the research of next generation energy conversion and storage devices, with an emphasis on exploring the oxygen evolution/reduction reaction and electrochemical carbon dioxide conversion at room temperatures. In 2022, he worked as an Associated Professor in School of Mechanical Engineering, South China University. Till now, He is hosting a National Natural Science Foundation of China, Shenzhen Postdoctral innovatiove research progam, respectively. As a core-participant, he is a member in Shenzhen Innovative Research Team Program:  Hydrogen energy and fuel cell electrocatalytic materials and Innovative project of Shenzhen graphene manufacturing innovation center: Development of graphene based materials for anti-corrosion and antifouling of marine equipment and facilities, respectively. Besides, he once hosted a China Postocroral Science Foundation in 2019. Till now, he has published over 15 papers and 4 patents in Chemical Communication, Polymer Chemistry, Journal of Material Chemistry A, Journal of Alloys and Compounds, etc.