Advisory Board and Editors Data Mining & Machine Learning
Maya Gokhale
Distinguished Member of Technical Staff, Lawrence Livermore National Laboratory, Phi Beta Kappa, IEEE Fellow.
Bruno Duarte Gomes
My primary area of research is in brain decoding using machine learning and deep learning, particularly in the context of epilepsy, Parkinson's disease, and cognitive processes in healthy individuals. My research also includes studying human and non-human primates visual system using psychophysics, visual evoked potentials and cortical extracellular recordings.
Education:
Ph.D., Neuroscience and Cell Biology, Federal University of Para
M.Sc., Neuroscience and Cell Biology, Federal University of Para
B.Sc., Biological Sciences, Federal University of Para
Shawn M Gomez
Professor and Associate Chair for Research in the Joint Department of Biomedical Engineering at UNC-CH and NCSU and Professor in the Department of Pharmacology at UNC-CH. Previous Florence Gould Scholar and Pasteur Foundation Fellow. Current research interests in systems and synthetic biology, bioimage informatics, and network science applied to biology. Broader interests in translational medicine and the fostering of innovative solutions to problems in healthcare.
Andrew R Gray
I am a biostatistician in the Biostatistics Centre at the University of Otago, a role I have held since 2004. Most of my work involves collaborating on a wide range of research projects in the health sciences, particularly in paediatric obesity, sleep, and physical activity; respiratory epidemiology, mostly asthma and COPD; dentistry; and health systems. I also work on statistical methods research, mostly topics inspired by these collaborations.
Prior to my current position I was a software metrics and machine learning researcher in the Department of Information Science at the same institution.
Fanglin Guan
Prof. Fanglin Guan is Dean at Xi'an Jiaotong University. He is engaged in the integrated biological research of complex diseases, including tumor microenvironment and novel immunotherapeutic modalities, and research on the mechanisms and medical applications related to tumor cell vaccines, especially for the exploration of the mechanism of determining the biomarkers of complex diseases.
Stefan Güttel
Stefan Güttel is Professor of Applied Mathematics at the University of Manchester. His work focuses on computational mathematics, including numerical algorithms for large-scale linear algebra problems arising with differential equations and in data science. He has been awarded the 2021 SIAM James H. Wilkinson Prize in Numerical Analysis and Scientific Computing, the 2023 Taussky–Todd Prize of the International Linear Algebra Society, and holds a Royal Society Industry Fellowship.
Jeonghwan Gwak
Dr. Jeonghwan Gwak received his Ph.D. degree in Machine Learning and Artificial Intelligence from Gwangju Institute of Science and Technology, Gwangju, Korea in 2014. From 2002 to 2007, he worked for several companies and research institutes as a Researcher and a chief technician. From 2014 to 2016, he worked as a Postdoctoral Researcher in GIST, and from 2016 to 2017 as a Research Professor. From 2017 to 2019, he was a Research Professor in Biomedical Research Institute & Department of Radiology at Seoul National University Hospital, Seoul, Korea. From 2019, he joined Korea National University of Transportation (KNUT) as an Assistant Professor and since 2021, he is an Associate Professor. He is the Director of the Algorithmic Machine Intelligence laboratory. His current research interests include deep learning, computer vision, image and video processing, AIoT, fuzzy sets and systems, evolutionary algorithms, optimization, and relevant applications of medical and visual surveillance systems.
Jin-Kao Hao
Distinguished Professor of Computer Science, Université d'Angers (France); Senior Fellow of the French "Institut Universitaire de France", Working on computational methods for large scale and complex combinatorial optimization problems.
Thomas Hartung
Professor of Toxicology (Chair for Evidence-based Toxicology), Pharmacology, Molecular Microbiology and Immunology at Johns Hopkins Bloomberg School of Public Health, Baltimore, and University of Konstanz, Germany; Director of their Centers for Alternatives to Animal Testing (CAAT). Former Head of the European Center for the Validation of Alternative Methods (ECVAM), Ispra, Italy.
Enrique Herrera-Viedma
Member of the BoG in IEEE SMC. Associate Editor of several ISI journals: IEEE TSMC, Systems; Knosys; Soft Comp.; Applied Soft Comp., J. of Intillegent Fuzzy Syst.; Fuzzy Opt. and Dec. Making, and Inf. Science. h-index is 45 and over 7500 citations (WoS). Highly Cited Researcher(Thom. Reu) and Top Author in Computer Science according to the Microsoft Acad. Interest: computing with words, fuzzy decision making, consensus, aggregation, social media, recommender systems, libraries, bibliometrics.
Catherine F Higham
Dr. Catherine Higham works at the interface between mathematics, deep learning and experimental science. Her first degree was in mathematics and her PhD involved mathematical modelling and statistical inference applied to somatic genetic mutations arising in myotonic dystrophy and Huntington's disease. Subsequent areas of research include Bayesian inference in nonlinear ODEs and the circadian clock. Currently, she is developing and applying deep learning techniques to inverse problems arising in novel quantum imaging technologies such as the single pixel camera and lidar. She also has an interest in quantum machine learning and framing problems for quantum annealing.
Harry Hochheiser
My research has covered a range of topics, including human-computer interaction, information visualization, bioinformatics, universal usability, security, privacy, and public policy implications of computing systems. I am currently working on a variety of NIH-funded projects, including areas such as bioinformatics research portals, visualization for review of chart records, and tools for aiding the discovery of animal models of human diseases.