Advisory Board and Editors Data Science
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.
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).
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.
Feiping Nie
Feiping Nie's research interests are machine learning and its application. He has published more than 100 papers in the following journals and conferences: TPAMI, IJCV, TIP, TNNLS/TNN, TKDE, TKDD, TVCG, TCSVT, TMM, TSMCB/TC, Machine Learning, Pattern Recognition, Medical Image Analysis, Bioinformatics, ICML, NIPS, KDD, IJCAI, AAAI, ICCV, CVPR, SIGIR, ACM MM, ICDE, ECML/PKDD, ICDM, MICCAI, IPMI, RECOMB. According to Google scholar, his papers have been cited more than 2000 times.
Corey Nislow
Corey Nislow's laboratory develops and uses cutting edge tools to address this central question: how can we understand the biological commonalities in all of the life sciences; from embryonic development, to the spread of infectious diseases to better ways to treat cancer. Each of these disciplines can be explained in the context of competition, interaction and evolution. His lab studies the interface between genes and the environment using parallel genome-wide screens, high throughput cell-based assays and next generation sequencing. Most recently, he and his scientific partner, Dr. Guri Giaever, are exploring how laboratory experiments can co-opt evolutionary processes to understand drug action. He enjoys teaching all aspects of biotechnology, genomics and drug discovery. He got his PhD from the University of Colorado, worked at several Biotechnology companies and was at Stanford and University of Toronto before joining UBC in 2013. He has published 161 papers and run 19 marathons.
Nicole Nogoy
Former Executive Editor at GigaScience, with a PhD in Natural Science (Georg-August Universitat, Goettingen). I have 14 years experience in Open Science and FAIR publishing, and was the launch Managing Editor of Genome Medicine.
Alexander C Nwala
Dr. Alexander C. Nwala is an assistant professor of Data Science at William and Mary (W&M). Before joining W&M, he was a postdoc at the Observatory on Social Media, Indiana University, Bloomington, with a research focus on dis/misinformation diffusion, detection, and countering of online manipulation. He received his PhD in Computer Science at Old Dominion University and has contributed multiple important tools and datasets to the data/web science, social media, (local) news, and web archiving communities.
Dr. Nwala has taught Computer Science courses to High School, Undergraduate, and Graduate students and has collaborated across disciplines and institutions, including with computer scientists/journalists at IU, archivists at the National Library of Medicine, and lawyers at Harvard. And his research has been published in multiple peer-reviewed Journals and Conferences.
Una May OReilly
Principal Research Scientist, Computer Science and Artificial Intelligence Lab, MIT. Leader, AnyScale Learning for All (ALFA) group. Vice-Chair ACM SigEvo, Fellow of ISGEC, 2013 EvoStar Award for Outstanding Achievements in Evolutionary Computation in Europe
Thiago Parente
Scientist in Public Health at the Laboratory of Functional Genomics and Bioinformatics at the Oswaldo Cruz Institute (IOC, Fiocruz), Rio de Janeiro, Brazil. Scientific coordinator of the Institutional Bioinformatics Platform. CNPq Level 2 Research Productivity Scholar (Genetics). Permanent professor at the Graduate program on Systems and Computational Biology IOC, Fiocruz. Graduated in Biological Sciences - Genetics major - from the Federal University of Rio de Janeiro (2006), with a Master's degree in Cell and Molecular Biology from the IOC (2008) and PhD in Biophysics from UFRJ (2012). Through high performance technologies for DNA sequencing and computational data analysis, I investigate the effects of pollution on fauna, using fish as model organisms, and their responses and genetic adaptations to pollutants, especially those involved in the xenobiotic biotransformation system.
Mohammad Zavid Parvez
Mohammad Zavid Parvez is a scholar in computer science with over 16 years of academic and research experience spanning machine learning, biomedical signal processing, cybersecurity, and federated learning. He earned his PhD in Computer Science from Charles Sturt University, Australia, where his research focused on epileptic seizure detection and prediction using EEG signals, and has since held research positions at Charles Sturt University and the ISI Foundation (Italy). He has published extensively in leading journals, including IEEE Transactions on Biomedical Engineering, IEEE Transactions on Neural Systems and Rehabilitation Engineering, and Neurocomputing. He also serves as Topic Editor for Frontiers in Medicine. His current research interests include cyber threat intelligence, privacy-preserving medical data analysis, and AI-driven healthcare solutions.
Gabriella Pasi
Gabriella Pasi is Full Professor at the University of Milano Bicocca, Italy, where she leads the Information Retrieval research Lab within the Department of Informatics, Systems and Communication. Her research activity mainly addresses the definition of models and techniques for a personalized access to information (in particular related to the tasks of information Retrieval and Filtering). She is also working on the analysis of user generated content in social media.