Advisory Board and Editors Data Mining & Machine Learning
Barry W Brook
Barry Brook, a conservation biologist and modeller, is an ARC Australian Laureate Professor and Chair of Environmental Sustainability at the University of Tasmania. Leader of the Dynamics of Eco-evolutionary Patterns (DEEP) research group and the UTAS node of CABAH, Barry is a highly cited scientist, having published three books, over 350 refereed papers, and many popular articles. His awards include the 2006 Australian Academy of Science Fenner Medal, the 2010 Community Science Educator of the Year and 2013 Scopus Researcher of the Year. He focuses on global change biology, ecological dynamics, paleoenvironments, energy systems, and statistical-simulation models.
Andrea Brunello
I am an Assistant Professor (tenure-track) at the Department of Humanities and Cultural Heritage (DIUM) of the University of Udine. In addition, I am part of the Data Science and Automatic Verification Laboratory, at the Department of Mathematics, Computer Science and Physics (DMIF) at the same University. As a figure straddling the two departments, I am part of the board of directors of the AI4CH Initiative, and I am interested in both practical aspects of Artificial Intelligence and philosophical issues. I am and have been a core member of several national and international projects with both institutional and corporate partners, such as u-blox, SAL Silicon Austria Labs, GAP srlu, and beanTech.
Alberto Cano
Alberto Cano is an Associate Professor with the Department of Computer Science, Virginia Commonwealth University, Richmond, Virginia, United States, where he heads the High-Performance Data Mining laboratory. His research is focused on machine learning, data mining, big data, evolutionary computation, general-purpose computing on graphics processing units, and distributed computing.
Marco Cavalli
Marco Cavalli obtained the PhD in Environmental Watershed Management in 2009 at the TeSAF (University of Padova) with a thesis on "Hydrological and morphological characterization of mountain basins by means of airborne LiDAR technology”. Since 2009 Marco Cavalli is Researcher at CNR-IRPI of Padova. His research interests include: Geomorphometry, Airborne Laser Scanning technology (LiDAR) and high-resolution DTMs applications, Geomorphic processes in mountain catchments, Post Flash flood investigation, analysis of historical information, GIS and surface hydrology. Currently, his main interest is related to sediment connectivity assessment through geomorphometric approaches.
He is\was scientific responsible or coordinator of CNR IRPI in several National and European projects (SedAlp, GESTO, Gadria Project, KINOFLOW). Since 2011 he is teaching a course for PhD and post doc researchers entitled 'Geomorphometry: quantitative analysis of earth surface' at the University of Padova. He is\was supervisor of three research grants at CNR IRPI, co-advisor of two PhD and several B.S. and M.S. theses of the University of Padova, Udine, Wageningen, Stockholm on geomorphology and hydrology fields. He is author and co-author of more than 50 papers in international journals.
Tianfeng Chai
Tianfeng Chai is an Associate Research Scientist at CICS-MD and the Department of Atmospheric & Oceanic Science, University of Maryland, College Park, Maryland, USA. He got his master and bachelor degrees from Tsinghua University in Beijing, majoring in Fluid Mechanics, Engineering Mechanics, and Environmental Engineering. He earned his Ph.D. at the University of Iowa, with his dissertation of "Four-Dimensional Variational Data Assimilation Using Lidar Data" focusing on atmospheric boundary flow. He then worked with Dr. Greg Carmichael to develop chemical transport model adjoints and computational framework for data assimilation applications before moving to working on the NOAA National Air Quality Forecast Capability (NAQFC) project in 2007. He currently works on the inverse modeling problems using HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory Model) to support several projects at NOAA Air Resources Laboratory.
Jyotismita Chaki
Jyotismita Chaki, PhD. is an Associate Professor in School of Computer Science and Engineering at Vellore Institute of Technology (VIT University), Vellore, India. She has done her PhD (Engg) from Jadavpur University, Kolkata, India. Her research interests include: Computer Vision and Image Processing, Pattern Recognition, Medical Imaging, Soft computing, Artificial Intelligence and Machine learning. She has authored and edited many international conferences, journal papers and books. Currently she is the editor of Engineering Applications of Artificial Intelligence Journal, Elsevier, academic editor of PLOS ONE journal and associate editor of Array journal, Elsevier, IET Image Processing and Machine Learning with Applications journal, Elsevier.
Prasenjit Chatterjee
Dr. Prasenjit Chatterjee is currently a Professor of Mechanical Engineering and Dean (Research and Consultancy) at MCKV Institute of Engineering, West Bengal, India. He has over 4700 citations and 120 research papers in various international journals and peer reviewed conferences. He has authored and edited more than 25 books on intelligent decision-making, fuzzy computing, supply chain management, optimization techniques, risk management and sustainability modelling.
Li Chen
I am a tenure-track Assistant Professor of Biostatistics and a member in Center for Computational Biology and Bioinformatics at Indiana University School of Medicine. I received a MS in Biostatistics and another MS in Computer Science from the Johns Hopkins University, and PhD in Computer Science and Informatics from Emory University. I also interned in CareerBuilder Data Science and Amazon Machine Learning.
Hao Chen
Dr. Chen's group uses behavioral genetics methods to study addiction related traits. The main behavioral models are intravenous nicotine self-administration and oral oxycodone self-administration in rats. Another area of focus is the identification of genomic variants in inbred strains of rats. A third area of research is the design of open source instruments and software for measuring rat behavior.
Aswani Kumar Cherukuri
Dr. Aswani Kumar Cherukuri is a Professor at Vellore Institute of Technology (VIT), India. His research interests include information security and machine learning. Aswani Kumar earned the Young Scientist Fellowship from Tamilnadu State Council for Science and Technology and was awarded the Inspiring Teacher Award from The Indian Express (India’s leading English daily newspaper). He has worked on various research projects funded by the Government of India’s Department of Science and Technology, the Department of Atomic Energy, and the Ministry of Human Resources Development. Aswani Kumar has published more than 150 refereed research articles in various national/international journals and conferences and is an editorial board member for several international journals. He is a Senior Member and distinguished speaker of the Association for Computing Machinery (ACM), a member of the Institute of Electrical and Electronics Engineers (IEEE), and Vice-Chair of the IEEE Taskforce on Educational Data Mining. Aswani Kumar earned a PhD in informational retrieval, data mining, and soft-computing techniques from VIT.
Davide Chicco
Davide Chicco is a scientific researcher at the University of Toronto. He received his PhD. from Politecnico di Milano in 2014, and his MSc. in Computer Science from the University of Genoa, Italy in 2010. From September 2018 to January 2020 he was a researcher at the University Health Network (Toronto, Ontario, Canada). Davide Chicco's research centres on biomedical informatics and machine learning.
Vincent A Cicirello
Dr. Vincent A. Cicirello is a Professor and Chair of Computer Science at Stockton University. He is also among the founding faculty of Stockton University's interdisciplinary Behavioral Neuroscience program. Dr. Cicirello earned his Ph.D. in Robotics from Carnegie Mellon University in 2003, and his M.S./B.S. in Computer Science and B.S. in Mathematics from Drexel University in 1999. His research interests include artificial intelligence, evolutionary computation, algorithms, machine learning, and computational intelligence. Dr. Cicirello is an ACM Senior Member, IEEE Senior Member, AAAI Life Member, and a member of SIAM.