Advisory Board and Editors Robotics
Takayuki Kanda
Takayuki Kanda is a Group Leader at ATR Intelligent Robotics and Communication Laboratories, Kyoto, Japan. He is one of the starting members of Communication Robots project at ATR. He has developed a communication robot, Robovie, and applied it in daily situations, such as peer-tutor at elementary school and a museum exhibit guide. His research interests include human-robot interaction, interactive humanoid robots, and field trials.
Lydia E Kavraki
Lydia Kavraki received her B.A. in Computer Science from the University of Crete in Greece and her Ph.D. in Computer Science from Stanford University. Her research contributions are in physical algorithms and their applications in robotics as well as in computational structural biology and biomedciine. Kavraki is the recipient of the ACM Grace Murray Hopper Award; a Fellow of ACM, IEEE, AAAS, AAAI, and AIMBE; and a member of the Institute of Medicine of the National Academies.
Bilal Khalid
Dr. Bilal Khalid received a Ph.D. in Industrial Business Administration from KMITL Business School, Bangkok, and a master’s in International Business Management from Stamford International University, Bangkok. Dr. Khalid's research interests include leadership and negotiations, digital transformations, gamification, eLearning, blockchain, big data, decarbonization, green entrepreneurial orientation, corporate social responsibility, sustainable management practices, and management of information technology. Dr. Bilal Khalid also serves as an academic editor at Journal of Computer Networks and Communication, Education Research International, and a reviewer for multiple international journals.
Yangming Lee
Dr. Lee is an Assistant Professor with Rochester Institute of Technology,
Rochester, NY, USA. Before this appointment, he held the positions as an Acting Instructor with the University of Washington, Associate Professor with the Institute of Intelligent Machines, Chinese Academy of Sciences, and Post Doc with the University of Michigan.
Pengcheng Liu
Pengcheng Liu is a member of IEEE, IEEE Robotics and Automation Society (RAS), IEEE Control Systems Society (CSS) and International Federation of Automatic Control (IFAC). He is also a member of the IEEE Technical Committee on Bio Robotics, Soft Robotics, Robot Learning, and Safety, Security and Rescue Robotics. Dr Liu is an Associate Editor of IEEE Access, PeerJ Computer Science, and he received the Global Peer Review Awards from Web of Science in 2019, and the Outstanding Contribution Awards from Elsevier in 2017. He has published over 70 papers on flagship journals and conferences. He was nominated as a regular Funding/Grants reviewer for EPSRC, NIHR and NSFC and he has been leading and involving in several research projects and grants, including EPSRC, Newton Fund, Innovate UK, Horizon 2020, Erasmus Mundus, FP7-PEOPLE, NSFC, etc. He serves as reviewers for over 30 flagship journals and conferences in robotics, AI and control. His research interests include robotics, machine learning, automatic control and optimization.
Federico Manuri
Federico Manuri received the B.Sc., M.Sc., and Ph.D. degrees in computer engineering from Politecnico di Torino, Torino, Italy, in 2008, 2011, and 2017, respectively all in computer engineering. He is currently an Assistant Professor with the Department of Control and Computer Engineering, Politecnico di Torino.
Qinggang Meng
Dr. Qinggang Meng is a Professor of Robotics and Artificial Intelligence in the Department of Computer Science, Loughborough University. He obtained his PhD from the Department of Computer Science, UWA in the area of AI and robotics.
Dr. Meng's research interests in robotics, unmanned aerial vehicles, driverless vehicles, networked systems, ambient assisted living, computer vision, AI and pattern recognition, machine learning and deep learning, both in theory and applications.
Mario Negrello
Mario Negrello obtained a mechanical engineering degree in Brazil (1997), and later after a period in the industry (VW 1999-2004) including RD and Prototypes, obtained his Masters degree (2006) and PhD (summa cum laude) in Cognitive Science at the University of Osnabrück in Germany in 2009. At that time, in the Fraunhofer Institute in Sankt Augustin (Germany) for Intelligent Dynamics and Autonomous Systems, he researched artificial evolution of neural network controllers for autonomous robots (2007/08). This work was awarded a scholarship by the International Society of Neural Networks (INNS) to sponsor an eight-month period (2008/09) as a visiting researcher at the Computational Synthesis Lab at the Aerospace Engineering department of the Cornell University in USA (with Hod Lipson). In his first post doctoral period he acted a group leader at the Computational Neuroscience laboratory at the Okinawa Institute of Science and Technology (with Erik De Schutter). He now heads a neuroscience lab that combines empirical research and computational methods (with Chris De Zeeuw). He has published in the fields of Machine Learning and Cognitive Robotics, Artificial Life, Evolutionary Robotics, Neuroethology and Neuroscience, as well as a monograph published by Springer US in the Series Cognitive and Neural systems entitled Invariants of Behavior (2012).
Kok Yew Ng
I received the BEng (Hons) in Electrical and Computer Systems Engineering and the Ph.D. in Fault Diagnosis and Control Systems from Monash University in 2006 and 2009, respectively. I am currently a Reader in Mechatronics Engineering and Control at the School of Engineering, Ulster University, UK, and I am attached to the Engineering Research Institute.
My research interests include fault diagnosis, mathematical modelling, digital twin, and data analytics for anomaly detection and classification.
In 2014–2015, I was a postdoctoral researcher at the Division of Vehicular Systems, Linköping University, Sweden, where I worked with Volvo Car Corporation (VCC) on advanced fault diagnosis schemes in vehicular engines using model-based and data-driven methods. For this research, I was instrumental in developing a Digital Twin/Simulation Testbed on the MATLAB/Simulink platform for realistic simulation and testing of residuals generation and fault diagnosis methods. This research work was published in the IEEE Control Systems Magazine and the Digital Twin/Simulation Testbed can be downloaded via the main hosting site or its mirror at Linköping University.
Throughout my career, I have secured more than £6.5 million in research grants from various funders such as the Engineering and Physical Sciences Research Council (EPSRC), UK Research and Innovation (UKRI), Global Challenges Research Fund (GCRF), and the Northern Ireland Department for the Economy in the UK; the Fundamental Research Grant Scheme (FRGS), Exploratory Research Grant Scheme (ERGS), and EScienceFund from the Ministry of Higher Education in Malaysia; and industries such as Volvo Car Corporation in Gothenburg, Sweden.
Overall, I have successfully supervised no less than 2 postdoctorals, 8 PhD, and 3 Master’s by Research candidates.
I am also currently attached to the Digital Catapult as an awardee of the EPSRC Innovation Launchpad Network+ (ILN+) Researcher in Residence Scheme. This research project aims to develop an energy mapping Digital Twin technology that contributes towards net zero in wind turbine energy. This technology encompasses the entire energy lifecycle, from mining through storage to utilisation in Northern Ireland (NI). This project also involves collaboration with the Offshore Renewable Energy Catapult.
Other highlights include being a co-investigator in SAFEWATER, a £5 million project funded by UKRI-GCRF, where I led the development and the optimisation of embedded algorithms to control low-cost water disinfection technologies used in the rural areas in South America.
In addition, during the COVID-19 pandemic, I led the Modelling and Forecast Task Force at Ulster where we worked with the Southern Health and Social Care Trust to provide analysis to the Government Specialist Modelling Response Expert Group (SMREG) in Northern Ireland. The main purpose of the project was to validate and inform the SMREG as well as help governing bodies in Northern Ireland to better plan for intervention measures and ultimately flatten the curve. I was also a member of the COVID-19 Task Force set up by the IEEE Region 8 community. In addition, I led a team of researchers and data scientists from Ulster and Queen’s University Belfast to work with the Incident Controller for the State Health Incident Control Centre and Deputy Chief Health Officer of the Department of Health in Western Australia to model the outbreak of COVID-19 on commercial cargo vessels.
I am a Senior Member of the IEEE and I am currently the Vice-Chair of the IEEE Control Systems Society (CSS), UK and Ireland Chapter.
I am the Moderator for the IEEE TechRxiv, the Associate Editor for IEEE Access, Editor for PeerJ Computer Science, and Section Editor for Sage Science Progress.
I am also an Adjunct Senior Research Fellow with Monash University Malaysia where I served as a Lecturer from 2009, and subsequently as Senior Lecturer till 2017.
Stefano Nolfi
Stefano Nolfi is one of the founders of Evolutionary Robotics and the director of one of the most active research lab in this area. His research activities focus on the evolution and development of behavioural and cognitive skills in natural and artificial embodied agents (robots). He authored/co-authored more than 150 peer-reviewed scientific publications including a monograph book on Evolutionary Robotics published by MIT Press in 2000 (more than 1400 citations).
Hae-Won Park
Hae-Won Park is an Assistant Professor of Mechanical Engineering at the Korea Advanced Institute of Science and Technology (KAIST). He received B.S. and M.S. degrees from Yonsei University, Seoul, Korea, in 2005 and 2007, respectively, and the Ph.D. degree from the University of Michigan, in 2012, all in mechanical engineering. His research interests lie at the intersection of control, dynamics, and mechanical design of robotic systems, with special emphasis on legged locomotion robots. He is the recipient of the 2018 National Science Foundation (NSF) CAREER Award, NSF most prestigious awards in support of early career faculty.
Waqar Shahid Qureshi
Dr. Waqar Shahid Qureshi is an applied AI researcher and engineer with over 22 years of professional experience across academia, research, and industry. His interdisciplinary expertise lies in artificial intelligence, computer vision, robotics, and intelligent sensing systems, with a strong emphasis on real-world deployment in precision agriculture, consumer electronics, and civil infrastructure.