Advisory Board and Editors Data Mining & Machine Learning
Md Zia Uddin
DR. MD ZIA UDDIN received his bachelor’s degree in computer science and engineering from International Islamic University Chittagong, Bangladesh, in 2004. He then completed his MS Leading to PhD degree in Biomedical Engineering from Kyung Hee University, South Korea, in 2011. Currently, he is a senior research scientist
in the human-computer interaction group at SINTEF Digital, Oslo, Norway, where he continues contributing to his research field. His research primarily focuses on data and feature analysis, physical and mental healthcare, human-machine interaction, pattern recognition, deep learning, and artificial intelligence. His innovative work has been published in prestigious journals such as Information Fusion, IEEE Transactions on Consumer Electronics, and Future Generation Computer Systems, showcasing his peers’ high regard for his research. His research outcomes have earned him best/outstanding paper awards at several peer-reviewed international conferences. He received a Gold Medal Award in 2008 for academic excellence in his undergraduate studies. He was also awarded the Korean Government IT Scholarship and the Kyung Hee University President Scholarship from March 2007 to February 2011 to pursue his PhD. He has extensive teaching experience, having taught more than 20 computer science-related courses at various academic levels, from bachelor’s to PhD, and supervised many students’ research works at these levels as well. He is a senior member of IEEE. He has been editors any several prestigious journals such as PLOS One, Sensors, IEEE Access, and the International Journal of Computers and
Applications, Frontiers in Human Neuroscience, and a keynote speaker at various international conferences. Dr. Zia has over 170 research publications (around half as the leading author), including international journals, conferences, book chapters, and single-authored books. His Google Scholar citations are more than 6000. He has led work packages and tasks in many national and international research projects. His significant contributions
have earned him recognition in the World’s Top 2% Scientists (career-long and single-year-based), a list by Stanford University and Elsevier BV.
Ana Tereza Ribeiro Vasconcelos
Ana Tereza Vasconcelos is Senior Researcher Scientist at the National Laboratory for Scientific Computing and coordinator of the Bioinformatics Laboratory and the Computational Genomics Unit Darcy Fontoura de Almeida at National Laboratory of Scientific Computation (LNCC). Her team has experience in the area of Bioinformatics and Computational Biology. Using High Performance Computing and AI working on the following topics: Genomics, Development of software applications in Bioinformatics and computational tools applied assembly, annotation and comparison of genomes, metagenomics, exomes and transcriptomics applied to many different model organisms. Since 2020 he has worked in the generation and analysis of SARS-CoV-2 genomes, mainly in the identification of new lineages.
Eleni Vasilaki
I am Professor of Bioinspired Machine Learning at the Faculty of Engineering, University of Sheffield and the head the Machine Learning group. Prior to my Academic appointment in Sheffield, I was Scientific Collaborator in the groups of Prof. Wulfram Gerstner at the Ecole Polytechnique Fédérale de Lausanne (EPFL) and Prof. Walter Senn at the University of Bern. I hold a PhD in Computer Science and Artificial Intelligence (University of Sussex), a Masters in Microelectronics (University of Athens) and a Bachelors degree (with distinction) in Informatics & Telecommunications (University of Athens). I am a Chartered Engineer, registered with the Engineering Council UK in membership of the Institution of Engineering and Technology.
Shravan Vasishth
Professor of Psycholinguistics at the Department of Linguistics, University of Potsdam, Germany. Specialization in computational models of sentence comprehension; sentence processing in aphasia; working memory and language comprehension; Bayesian statistics.
Sebastian Ventura
Sebastián Ventura is professor of Computing Science and Artificial Intelligence at the University of Córdoba. His teaching is devoted to computer programming, machine learning and data mining in undergraduate and graduate studies. His research labor is developed as head of the "Knowledge Discovery and Intelligent Systems" (KDIS) research group, and it is focused on machine learning, data mining, big data, computational intelligence and its applications.
Chaman Verma
Dr. Chaman Verma is an Assistant Professor at the Department of Media and Educational Informatics, Faculty of Informatics, Eötvös Loránd University. He is also the project leader and chief researcher of his project sponsored by National Research, Development and Innovation (NRDI) Hungary. He also won a young educator scholarship for novel research sponsored by the EKÖP, NRDI Fund, and the Hungarian Government.
He pursued a post-doctorate at the Faculty of Informatics, Eötvös Loránd University, Budapest, Hungary, sponsored by UNKP, MIT (Ministry of Innovation and Technology), the National Research, Development and Innovation (NRDI) Fund, and the Hungarian Government. He received a Ph.D. in informatics from the Doctoral School of Informatics, Eötvös Loránd University, Budapest, Hungary, with the Stipendium Hungaricum Scholarship funded by the Tempus Public Foundation, Government of Hungary. During his Ph.D., he won the EFOP Scholarship, co-founded by the European Union Social Fund and the Government of Hungary, as a professional research assistant in a real-time system from 2018 to 2021. He also received the Stipendium Hungaricum Dissertation Scholarship of Tempus Public Foundation, Government of Hungary, from 2021 to 2022.
He has been awarded several Erasmus Scholarships for conducting international research and academic collaboration with European and non-European universities. He received the best scientific publication award from the Faculty of Informatics, Eötvös Loránd University, Budapest, Hungary, In the years 2021-2024. He has also been awarded the ÚNKP scholarship for research by the Ministry of Innovation and Technology and the National Research, Development and Innovation (NRDIO) Fund, Government of Hungary, 2021-2023.
He has around ten years of experience in teaching and industry. He has over 150 scientific publications in the IEEE, Elsevier, Springer, IOP Science, Walter de Gruyter and MDPI. His research interests include data analytics, feature engineering, real-time systems, and educational informatics. He is a life member of ISTE, New Delhi, India. He is a member of the editorial board and a reviewer of various international journals and scientific conferences. He was the leading guest editor of the special issue Advancement in Machine Learning and Applications in Mathematics, IF- 2.25, MDPI, Basel, Switzerland, in 2022. He was also a guest editor in two Springer journals. He is a co-editor in the series of conference proceedings of ICRIC-2021-24 published by Springer, Singapore. He reviews many scientific journals, including IEEE, Springer, Elsevier, Wiley, and MDPI. He has Scopus citations of 1603 with an H-index of 24. He has Web of Science citations of 355 with an H-index of 13.
Ramana Vinjamuri
Ramana Vinjamuri received his undergraduate degree in Electrical Engineering from Kakatiya University (India) in 2002. He received his MSc in Electrical Engineering from Villanova University in 2004, specializing in Bioinstrumentation. He received his Ph.D. in Electrical Engineering from University of Pittsburgh in 2008, specializing in Dimensionality Reduction in Control and Coordination of the Human Hand. He worked as a postdoctoral fellow (2008-2012) in the field of Brain-Machine Interfaces (BMI) to control prosthesis in the School of Medicine, University of Pittsburgh. He worked as a Research Assistant Professor in the Department of Biomedical Engineering at the Johns Hopkins University (2012-2013). He worked as an Assistant Professor in the Department of Biomedical Engineering at Stevens Institute of Technology (2013-2020). He was the recipient of the Harvey N Davis Distinguished Teaching Award in 2018 at Stevens. His research at Stevens was supported by Research and Innovation grants from the New Jersey Health Foundation. He received the NSF CAREER Award in 2019 and NSF IUCRC Planning Grant Award in 2020 respectively. He also holds a secondary appointment as an Adjunct Assistant Professor at the Indian Institute of Technology, Hyderabad, India. His research interests are in the areas of – brain-computer interfaces, neuroprosthetics and exoskeletons, machine learning, and signal processing.
Stefan Wagner
Stefan Wagner is full professor of software engineering at the Technical University of Munich in the TUM School of Communications, Information and Technology. He studied computer science in Augsburg and Edinburgh and psychology in Hagen. He holds a doctoral degree in computer science from TU Munich, where he also worked as a post-doc. Previously, he was a full professor at the University of Stuttgart. His main research interests are empirical studies, software quality, human factors, AI-assisted software engineering, AI-based software and automotive software. He is a member of GI and a senior member of ACM and IEEE.
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 14 years of experience in machine learning, bioinformatics, and computational biology, Dr. Wan has published >50 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 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 including Frontiers in Immunology, Frontiers in Cell and Developmental Biology, Frontiers in Pharmacology, Biology, Frontiers in Genetics, and Genes.
Dr Wan is a 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, ISCB and ACM and an IEEE Senior Member.
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.
Lei Wang
Professor of Geography at Louisiana State University. Research interests include Geocomputation, GeoAI, Remote Sensing of water, Spectroscopic analyses, and mapping flood hazards.