Advisory Board and Editors Data Mining & Machine Learning
Marc-André Delsuc
Marc-André Delsuc activity is mostly oriented toward the use and improvement of spectroscopies, in particular NMR and more recently FT-MS. This includes new experiment design, development of data processing methods, development of software programs. I have been deeply involved in field as diverse as protein structural analysis, protein-ligand screening, complex mixture analysis, quantum mechanic details of the NMR phenomenon, automatic data analysis, fractal dimension of proteins and polymers, etc.
Peter Denning
Distinguished professor of computer science at Naval Postgraduate School. Past president of ACM. Past editor in chief of Communications of ACM. Currently editor of ACM Ubiquity. Author of ten books, most recent Great Principles of Computing (MIT Press 2015). Author of over four hundred scientific papers and articles.
Gopikrishna Deshpande
Prof. Gopikrishna Deshpande is a Professor of Electrical and Computer Engineering at Auburn University. He obtained his Ph.D. in Medical Imaging from Georgia Institute of Technology and his M.S. in Electrical and Computer Engineering from the Indian Institute of Science.
Prof. Deshpande's research interests and expertise include neuroimaging, functional magnetic resonance imaging (fMRI), brain connectivity, signal/image processing and machine learning.
Antonio Jesus Diaz-Honrubia
Antonio J. Díaz-Honrubia is an Associate Professor at Universidad Politécnica de Madrid, to which he joined after holding an Assistant Professorship at Universidad de Oviedo and a part time Professorship at Universidad de Castilla-La Mancha (a job that he combined with a position in the R&D department of a private company in the telecommunications field).
He received his Ph.D. in 2016 from the Universidad de Castilla-La Mancha, where he had also received his B.Sc. (Spanish National Extraordinary Award) and M.Sc. in Computer Science and Engineering.
His research interests include video transcoding, perceptual video coding, multimedia standards, scalable video coding, and simultaneous video coding. More recently, he is moving forward to the topic of data analysis and validation.
He has been a visiting researcher at Ghent University (Belgium) for 4 months, the Florida Atlantic University (USA) for 3 months, and the Technische Informationsbibliothek (TIB) (Germany) for 6 months.
He has more than 30 publications in these areas in international refereed journals and conference proceedings.
Trang Do
Dr. Trang Do earned her PhD degree from the National University of Singapore in 2013. She is a proactive and motivated educator and data scientist, showcasing a track record of effectively managing expansive and intricate projects alongside engagements with stakeholders and government agencies. Her expertise spans data and computer science, coupled with a foundation in economics and bioinformatics, driving an ongoing pursuit of professional development. Her research interests encompass a wide scope within data science, intelligent systems, and interdisciplinary computing. Presently, her primary focus centers on machine learning, deep learning, explainable AI, data analysis, and visualization, particularly within the realms of health informatics, drug discovery, bioinformatics, tourism, and intelligent systems.
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.