Advisory Board and Editors Data Mining & Machine Learning
Shibiao Wan
Dr. Shibiao Wan is currently an Assistant Professor in the Department of Genetics, Cell Biology and Anatomy, and the Co-Director for the Bioinformatics and Systems Biology (BISB) PhD Program at University of Nebraska Medical Center (UNMC). He is also an Assistant Professor (courtesy) in the Department of Biostatistics at UNMC.
With more than 15 years of experience in machine learning, bioinformatics, and computational biology, Dr. Wan has published >60 articles in top-tiered journals such as Genome Research, Nature Communications, Science Advances, Circulation Research, Briefings in Bioinformatics, and Bioinformatics. Dr. Wan is the Editor-in-Chief for Current Proteomics, and an Associate Editor/Academic Editor/Editorial Board Member for a series of prestigious journals such as Briefings in Functional Genomics, Heliyon, BMC Bioinformatics, International Journal of Microbiology, PeerJ Computer Science, BioMed Research International, and Computational and Mathematical Methods, and a guest associate editor for multiple high-impact journals.
He is a Scientific Program Committee (SPC) member for American Medical Informatics Association (AMIA) Annual Symposium and a Technical Program Committee (TPC) member for >20 machine learning related international conferences including IEEE ICTAI. Dr. Wan is also a reviewer for >70 prestigious journals including Nature Biotechnology, Nature Methods, Nature Communications, Nature Computational Science, Science Advances, Nucleic Acids Research, Advanced Science, Cancer Research, Genome Biology, and Genome Medicine. Dr. Wan has received a number of accolades including the Springer Nature Editor of Distinction Award in 2025 by Springer Nature, the New Investigator Award in 2024 by UNMC, the FIRST Award in 2023 by Nebraska EPSCoR, the Outstanding Young Alumni Award in 2022 by HK PolyU as well as the Global Peer Review Awards (top 1%) in “Cross-Field” and “Biology and Biochemistry” in 2019 by Clarivate. Dr. Wan is a member of AACR, AMIA, ISCB and ACM and an IEEE Senior Member.
Jingbo Wang
Prof Wang's research spans several disciplines including quantum dynamics theory, quantum computation and information, atomic physics, and computational science. She has published extensively, including a recent book published by Springer, four book chapters, and numerous journal papers. Prof Wang currently leads the quantum dynamics and computation group at The University of Western Australia. She and her research team have developed advanced numerical techniques to solve problems in both quantum and classical domain.
Kezhi Wang
Kezhi Wang received his Ph.D. degree from the University of Warwick, U.K. He was a Senior Research Officer in University of Essex, U.K. Currently He is a Senior Lecturer with Department of Computer Science, Brunel University, U.K.
Shuo Wang
Shuo Wang is an Assistant Professor in the School of Computer Science, at the University of Birmingham, UK. Her research interests include data stream classification, class imbalance learning and ensemble learning approaches in machine learning, and their applications in social media analysis, software engineering and fault detection. Her work has been published in internationally renowned journals and conferences, such as IEEE Transactions on Knowledge and Data Engineering and International Joint Conference on Artificial Intelligence (IJCAI). In addition, she was a guest editor of Neurocomputing and Connection Science and the workshop organizer of IJCAI'17 and ECML/PKDD'21, '22. She is currently in the editorial board of International Journal of Computational Intelligence and Applications.
Dapeng Wang
Dr Dapeng Wang is a Senior Bioinformatician in Integrative Analysis at the COMBAT consortium at the University of Oxford using multi-omics techniques in combination with the cutting-edge bioinformatic approaches and statistical methods to explore the pathogenesis of COVID-19 and stratification of patients as well as inform the treatment strategy based on genomics information.
Dr Wang received a bachelor’s degree in mathematics from the Shandong University in 2006 and obtained a PhD degree in bioinformatics from the Beijing Institute of Genomics of the Chinese Academy of Sciences in 2011. After his graduation, he continued to conduct research at the same institute from 2011 to 2014 and afterwards moved to the UK to take up various roles at the Cancer Institute at the University College London (2014-2016), the Department of Plant Sciences at the University of Oxford (2016-2018) and the LeedsOmics at the University of Leeds (2018-2020).
Shuihua Wang
Shuihua Wang received her B.S. Degree in information science and engineering from Southeast University in Nanjing, China, in 2008; the M. S. degree in Electrical Engineering from the City College of New York, USA in 2012, and the Ph. D degree in Electrical Engineering from Nanjing University, Nanjing, China, in 2017. She visited Kyushu Institute of Technology in 2017. From 2013 to 2018 she joined Nanjing Normal University, and worked as an assistant professor. From 2018-2019, she served in Loughborough University. She is now working as a research associate at the University of Leicester. Her research interests focus on Machine learning, Deep learning, biomedical image processing. She has published over 30 papers in peer-reviewed international journals and conferences in these research areas. She was serving as a professional reviewer for many well-reputed journals and conferences including IEEE Transactions on Neural Networks and Learning Systems, Neuron Computing, Pattern recognition, scientific reports, and so on. She is currently serving as Guest Editor-in-Chief of Multimedia Systems and Applications, Associate editor of Journal of Alzheimer’s Disease and IEEE Access. She is a member of the IEEE.
Jingzhe Wang
Jingzhe Wang received his Ph. D in Cartography and Geographic Information System from Xinjiang University, Urumqi, China, in 2019. He is now working as a research associate at MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area, Shenzhen University. His research interests focus on Earth observation and remote sensing, spectral modeling, quantitative estimation of soil properties, digital soil mapping, GIS, spatial analysis, and environmental sustainability. He has published over 60 papers in peer-reviewed international journals in these related research areas and has served as a reviewer for many journals and conferences including Remote Sensing of Environment, Ecological Indicators, Computers and Electronics in Agriculture.
Lei Wang
Professor of Geography at Louisiana State University. Research interests include Geocomputation, GeoAI, Remote Sensing of water, Spectroscopic analyses, and mapping flood hazards.
Easton R White
I am a quantitative marine ecologist who uses mathematical and statistical tools, coupled with experiments and field observations, to answer questions in ecology, conservation science, sustainability, and ecosystem management. Most of my work is focused on marine systems, especially fisheries and spatial planning. I am a new Assistant Professor in the Department of Biological Sciences at the University of New Hampshire. Prior to joining UNH, I was a research associate at the University of Vermont with the QuEST program, a NSF-funded PhD traineeship focused on quantitative skills, interdisciplinary work, as well as diversity and inclusion.
I currently conduct research on assessing the effectiveness of protected area networks, improving species monitoring programs, and modeling socio-ecological systems in the context of fisheries. My work centers on how environmental variability, in particular rare events (e.g., hurricanes, COVID-19 pandemic), affects ecosystems and those that depend on them. My current work is funded through a NSF grant focused on interdisciplinary approaches to study coupled natural-human systems with Madagascar fisheries as a case study.
Matthew D Wilson
Matthew (Matt) Wilson is a Professor in Spatial Information and Director of the Geospatial Research Institute Toi Hangarau at the University of Canterbury in Christchurch, New Zealand. He is a surface water hydrologist and geographical information scientist with specialisations including flood risk, surface water dynamics, water resources, remote sensing, numerical model development, uncertainty analysis and the assessment of the potential impacts of climate change. Previous research has included the assessment of the potential impacts of climate change on flood risk and water resources in the Caribbean and the analysis of surface water hydrodynamics on a 300 km reach of the Amazon River in Brazil. In New Zealand, his current research includes leading the uncertainty theme for a national scale flood risk assessment, the creation of a digital twin for flood resilience, and the creation of algorithms for processing of novel airborne GNSS reflectometry measurements for estimation of soil water content.
Zhijin Wu
I develop statistical methodology and software for the analysis of -omics data. I am particularly interested in the regulation of transcription: the molecular mechanism as well as its association with disease.