Advisory Board and Editors Data Mining & Machine Learning
Gillian Dobbie
Gill worked in industry for a couple of years before doing research at the University of Melbourne, Victoria University of Wellington and the National University of Singapore. Her main areas of interest pertain to databases and the web. She has worked in the foundations of database systems, defining logical models for various kinds of database systems, and reasoning about the correctness of algorithms in that setting. She publishes her research in high ranking conferences and journals.
Ahmed Elazab
Ahmed Elazab received his Ph.D. degree in pattern recognition and intelligent systems from Shenzhen Institutes of Advanced Technology, University of Chinese Academy of Sciences, China, Jan 2017. He was a postdoctoral research fellow from Jan 2018 to April 2020 at the School of Biomedical Engineering, Shenzhen University, Shenzhen, China where he is currently a research associate since Jan 2021. Dr. Elazab has authored and co-authored more than 80 peer-reviewed papers and has been a reviewer in prestigious peer-reviewed international journals. His main research interests include machine and deep learning, medical image analysis, brain anatomy analysis, and computer-aided detection and diagnosis.
Charles P. Elkan
Professor of computer science at the University of California, San Diego, and also Amazon Fellow.
Andrea Esuli
Andrea Esuli is a researcher of the Italian National Research Council. His research interests are in the fields of multimedia information retrieval, machine learning, and text classification.
Carlos Fernandez-Lozano
Dr. Carlos Fernandez-Lozano is an Associate Professor at the University of A Coruña (UDC). He is a biomedical data scientist with a deep interest in discovering the complex relationships between different biological levels. His research track is multidisciplinary as he is trained in computer science, machine learning, bioinformatics, and biostatistics. His research line is focused on how biological interactions are manifested at the disease level through the use, development, and application of kernel-based computational approaches that integrate different levels of biological data on the microorganism, gene, protein, and medical imaging axis.
Pedro G Ferreira
Pedro G. Ferreira graduated in Systems and Informatics Engineering from the University of Minho in 2002 and obtained his Ph. D. in Artificial Intelligence from the same University in 2007. From 2008 to 2012, he was a Postdoctoral Researcher at the Bioinformatics and Genomics Laboratory, Centre for Genomic Regulation, Barcelona. From 2012 to 2014, he was a Postdoctoral Fellow the Functional Population Genomics and Genetics of Complex Traits group, School of Medicine, University of Geneva. He has been involved in several large international consortia including: ICGC-CLL, ENCODE, GEUVADIS, SYSCOL and GTEx. He published several papers in high impact journals, including the multidisciplinary journals: Nature, Science, Nature Communications, Scientific Reports, PNAS and eLife. Other papers have been published in high impact specialized journals including Genome Biology, Genome Research, American Journal of Human Genetics, Nature Cell Biology, RNA or Leukemia. He is the author of 3 book chapters and 2 books. He has an h-index of 31, with a total > 32 000 citations. In 2015, he was awarded an FCT Investigator Starting grant and he joined Ipatimup/i3s. He was awrded the Research Award 2015 and 2019 from Portuguese Society of Human Genetics - SPGH and the Microsoft Azure Research Award for Data Science 2017. He is a partner in a bioinformatics data analysis company with national and international clients, including hospitals, diagnostic clinics and research centres. From 2015 to 2018, he was an invited assistant professor at the Department of Informatics at the University of Minho, where he taught bioinformatics and data analysis at master's level. He has been involved in the final supervision of 1 postdoctoral fellow, 2 PhD students, 22 Masters students and 3 research assistants, and in the ongoing (main and co-) supervision of 5 PhD students and 5 Masters students. He was the director of the Masters and Specialisation in Bioinformatics and Computational Biology (2020-2023). He has experience in the genomics start-up environment, where he developed information systems for personal genomics data interpretation. He is currently an Assistant Professor (since 02/2019) with Habilitation (since 10/2022) at Department of Computer Science, Faculty of Sciences of the University of Porto and a Senior Researcher at the Artificial Intelligence and Decision Support Group at INESCTEC. He is currently the Director of the Bachelor in Bioinformatics and Adjunct Director of the Bachelor in Artificial Intelligence and Data Science. His main research focus is on developing methods for a variety of problems in genomic data science. In particular, he is interested in unravelling the role of genomics in human health and disease. To achieve this goal, he applies and develops data analysis models using machine learning and probabilistic methods to analyse and interpret diverse, complex and large-scale genomic datasets.
Daniel Fischer
I studied Statistics and Computer Sciences at the Technical University of Dortmund, Germany. During that time, my interest was particularly in mathematical statistics with a focus on high-dimensional extensions of the univariate median. After graduating, I moved to Tampere, Finland and completed my PhD in at the University of Tampere in Biostatistics with minor Bioinformatics.
While still being enrolled as PhD student at the University I started to work as a researcher in Bioinformatics at the MTT, Jokioinen, Finland. Since 2015 I am working at the Natural Resources Institute Finland (Luke) where I finalized my PhD.
My published articles in peer-reviewed journals cover a wide range of applications as well as statistical theory. My areas of expertise are target gene detection, biomarker identification and novel gene detection with a special focus on long non-coding RNAs. Further, I have experiences in the development of statistical methods for DE testing as well as deriving novel non-parametrical tests for (e)QTL analyses. I published and maintain currently six R-packages, i.e. for (e)QTL testing, cross-species ortholog detection and dimension reduction methods.
Alicia Fornes
Alicia Fornés is a Staff Scientist in the Document Analysis Group within the Computer Vision Center at the Universitat Autònoma de Barcelona.
Her research interests include document image analysis, graphics recognition, digital humanities, handwriting recognition, historical documents and optical music recognition.
Atsushi Fukushima
I am a professor at Kyoto Prefectural University. My current research interests focus on characterization of metabolic regulatory networks and integrated analysis of multi-omics data in plants. I am a member of the editorial board for BMC Genomics, Plant Methods, Frontiers in Plant Science, Plants, BioTech, and PeerJ.
Tarek Gaber
Tarek Gaber is a Senior Lecturer (Associate Professor) at the University of Salford (UK) and a Full Professor of Computer Science at Suez Canal University (Egypt). He has over two decades of academic and research experience across cybersecurity, artificial intelligence (AI), secure systems, and Safe AI. His work focuses on developing resilient AI models, secure digital infrastructures, and innovative applications for industry and public sector transformation. Dr. Gaber has authored over 100 scholarly publications, including journal articles, conference papers, book chapters, and edited volumes — with more than 40 published in Q1 journals. He has led or co-led research projects exceeding £6 million in funding, supported by Innovate UK, UKRI, Research England, and UKAEA. His research excellence has earned him recognition among Stanford University’s top 2% of scientists globally. He has served as Programme Leader for the MSc Cyber Security programme at Salford, contributed to several Knowledge Transfer Partnerships (KTPs), and engaged in interdisciplinary projects with SMEs to deploy secure and explainable AI solutions. Dr. Gaber is a Fellow of the UK Higher Education Academy (FHEA), a member of IEEE, and frequently serves as a keynote speaker, journal reviewer, and editorial board member in his field.
Xiao-Zhi Gao
Prof. Xiao-Zhi Gao is a Professor in the Faculty of Science and Forestry, School of Computing at the University of Eastern Finland, Finland.
His research interests include soft computing, machine learning, data mining and communications networks.
Noushin Ghaffari
Dr. Noushin Ghaffari is a senior member of the bioinformatics team at Texas A&M AgriLife Genomics and Bioinformatics (TxGen), where she is involved in various projects from planning experiments to data analysis. She is also focused on method development and application projects that will impact scientific community. Her research activities have encompassed various areas of computational biology and have enabled her to study and learn more about the characteristics of multiple species. Furthermore, she intensely pursues her theoretical interests focusing on applications of mathematics in solving biological problems. Dr. Ghaffari has led numerous genome and transcriptome assembly projects for novel species such as cattle tick, gene discovery research though RNA-Seq studies, studying microbiome communities via metagenomics research and etc. Dr. Ghaffari has vast teaching experiences and continues to educate Texas A&M faculty/students/researcher on high performance computing, data analysis and bioinformatics.