Advisory Board and Editors Artificial Intelligence
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.
Nageswara Rao Moparthi
Dr. M. Nageswara Rao is a Professor within the Dept. of Computer Science and Engineering, K L University, India. He has over 19 years of experience in the S/W industry and academia. Dr. M. Nageswara Rao has published over 20 articles in reputed international journals, written 2 books and filed 2 Indian patents. He is a reviewer for a number of SCI/SCIE journals, including IEEE Access and Journal of Big Data(JBD) Journal of Database Management, Cluster Computing , NHIB and Information Sciences; and Scopus journals, such as IJAIP, IJDS, CIT and IJECE. Dr. M. Nageswara Rao is also an associate TPC member for the following International conferences: ICACII-2019-Springer (India), ICCET-2020-IEEE/WOS (New Zealand), ITIoT/ICCCS 2020-Shanghai (China), JCICE-Sydney (Australia), BDET-2020-ACM Digital Library (Singapore) and ICCMA 2019-IEEE (TU Delft, Netherlands).
Dr. M. Nageswara Rao's research areas are listed below:
1.Data Mining
2. Data Analytics
3.Machine Learning
4. Software Engineering
5. Artificial Intelligence
Alejandro Moreo
Alejandro Moreo received a PhD in Computer Sciences and Information Technologies from the University of Granada in 2013. He is a tenured researcher at Istituto di Scienza e Tecnologie dell’Informazione "A. Faedo", which is part of the National Research Council (CNR). His research interests include learning to quantify, deep learning, and representation learning.
Christopher J Mungall
I am a Computer Research Scientist in the Environmental Genomics and Systems Biology division at Lawrence Berkeley Laboratory. My work focuses on computational methods for representing and interpreting complex biological data, in particular through the development and application of knowledge representation structures such as ontologies.
Maria Navarro-Caceres
Dr. Maria Navarro-Caceres is an Associate Professor and Computer Scientist at the University of Salamanca.
She is interested in ML and DL proposals, and also in the application of computing technologies to artistic and musical perspectives.
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.
Peter A. Ng
Dr. Peter Ng is Professor of Computer Science at Purdue University Fort Wayne and Fellow of the Society for Design and Process Science (SDPS). He has served as the Chair and Professor of Computer Science in the College of Information Science and Technology at the University of Nebraska at Omaha, NE (1998-2000), and in the College of Science and Arts at the New Jersey of Institute of Technology, Newark, NJ (1985-1998). He has served as the Executive Director for Global e-Learning Project at the International Programs and Studies of the University of Nebraska-Omaha (2000-2003) and as the Vice President for Fudan International Institute for Information Science and Technology, Shanghai, China (1999-2000). Dr. Ng received his Ph.D. in Computer Science from the University of Texas at Austin in 1974.
Anh Nguyen
Dr. Anh Nguyen-Duc is a Professor at the Department of Business and IT, University of South Eastern Norway. He works as Professor 2 at Norwegian University of Science and Technology. His research interests include Empirical Software Engineering, Data Mining, Software Startups Research and Cybersecurity.
Binh P. Nguyen
Senior Lecturer in Data Science at the School of Mathematics and Statistics in Victoria University of Wellington (New Zealand). Former Scientist at the Institute of High Performance Computing, A*STAR (Singapore). Former Research Fellow at Duke-NUS Medical School and National University of Singapore (Singapore).
Duc D Nguyen
Dr. Duc Nguyen is an Assistant Professor in the Department of Mathematics at the University of Kentucky. His research interests lie at the interface of data science, mathematical biology, and scientific computing. He has developed several popular online servers for drug design communities such as FRI, RI-Score, DG-GL, and AGL-Score. By integrating mathematics and deep learning, Dr. Nguyen won the most number of contests in the past three D3R Grand Challenges, an annual worldwide competition series in computer-aided drug design. That success has stimulated his partnerships with Bristol-Myers Squibb for developing quantitative systems pharmacological models and with Pfizer for drug de novo hit identification.
Hoang Nguyen
Dr. Hoang Nguyen is a Lecturer (Computational biologist, data scientist, and computer scientist) within the School of Innovation, Design, and Technology at the Wellington Institute of Technology in New Zealand.
His research interests include Applied Data Science, Machine Learning, Deep Learning, Computer-aided Drug Design, Bioinformatics, and Health informatics.