Advisory Board and Editors Data Science
Robert H McDonald
Robert H. McDonald is Dean of University Libraries and Professor of Library Administration. He is responsible for leading the Boulder campus library system in fulfilling their mission to inspire learning, research, and discovery by connecting knowledge, information, and people.
His expertise and interests include teaching and learning technologies that enable libraries to better support researchers at all levels, open source software development, scholarly communications, and new model publishing. Robert has also been an active proponent of diversity initiatives in libraries throughout his career and is committed to creating library spaces that are welcoming, diverse and inclusive for all of our Library users.
Monique Messié
Research specialist at the Monterey Bay Aquarium Research Institute (MBARI) working on physical/biological interactions in the oceans.
My research combines satellite products, models and in situ data to study ecosystem processes and physical/biological interactions in the coastal and open oceans. Current areas of research include physical and biological variability at regional and global scales, ecosystem response to climate and ocean change, bioluminescence in the upper ocean, marine hotspots in the California Current, connections between surface, midwater and benthic communities, and the effect of tropical islands on phytoplankton biomass and biodiversity.
Dezső Módos
I am a medical doctor and a systems biologist. During my scientific carrier, I have tried to understand diseases and find novel approaches to treat them with drugs, whether it is cancer or UC. I finished the Semmelweis University Doctor of Medicine course on 2012 and then started my PhD in network biology. I was involved in developing multiple biological network databases transcription factor-target layers such as SignaLink, AutophagyRegulatory Network or the NRF2Ome. My main project was to understand signalling networks in cancer and how the different paralogues of a protein can act in the signalling network.
Since then I have been a Postdoctoral Research Associate at Cambridge University, where my main focus was how can we use networks to predict mechanisms of action of compound combinations. I used various chemical informatics techniques besides network biology such as chemical fingerprints, machine learning and gene expression-based toxicity prediction.
Currently, I am working at the Earlham Institute and Quadram Institut in Norwich researching inflammatory bowel disease and using network biology to decipher the pathogenesis of complex disorders.
I have recently moved to Imperial College, London to go through the therapeutic celling in IBD using systems biology.
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
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.
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.
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.