Advisory Board and Editors Data Mining & Machine Learning
Anh Nguyen
Dr. Anh Nguyen-Duc is a Professor at the Department of Business and IT, University of South Eastern Norway. He works as Professor 2 at Norwegian University of Science and Technology. His research interests include Empirical Software Engineering, Data Mining, Software Startups Research and Cybersecurity.
Binh P. Nguyen
Senior Lecturer in Data Science at the School of Mathematics and Statistics in Victoria University of Wellington (New Zealand). Former Scientist at the Institute of High Performance Computing, A*STAR (Singapore). Former Research Fellow at Duke-NUS Medical School and National University of Singapore (Singapore).
Duc D Nguyen
Dr. Duc Nguyen is an Assistant Professor in the Department of Mathematics at the University of Kentucky. His research interests lie at the interface of data science, mathematical biology, and scientific computing. He has developed several popular online servers for drug design communities such as FRI, RI-Score, DG-GL, and AGL-Score. By integrating mathematics and deep learning, Dr. Nguyen won the most number of contests in the past three D3R Grand Challenges, an annual worldwide competition series in computer-aided drug design. That success has stimulated his partnerships with Bristol-Myers Squibb for developing quantitative systems pharmacological models and with Pfizer for drug de novo hit identification.
Hoang Nguyen
Dr. Hoang Nguyen is a Lecturer (Computational biologist, data scientist, and computer scientist) within the School of Innovation, Design, and Technology at the Wellington Institute of Technology in New Zealand.
His research interests include Applied Data Science, Machine Learning, Deep Learning, Computer-aided Drug Design, Bioinformatics, and Health informatics.
Feiping Nie
Feiping Nie's research interests are machine learning and its application. He has published more than 100 papers in the following journals and conferences: TPAMI, IJCV, TIP, TNNLS/TNN, TKDE, TKDD, TVCG, TCSVT, TMM, TSMCB/TC, Machine Learning, Pattern Recognition, Medical Image Analysis, Bioinformatics, ICML, NIPS, KDD, IJCAI, AAAI, ICCV, CVPR, SIGIR, ACM MM, ICDE, ECML/PKDD, ICDM, MICCAI, IPMI, RECOMB. According to Google scholar, his papers have been cited more than 2000 times.
Una May OReilly
Principal Research Scientist, Computer Science and Artificial Intelligence Lab, MIT. Leader, AnyScale Learning for All (ALFA) group. Vice-Chair ACM SigEvo, Fellow of ISGEC, 2013 EvoStar Award for Outstanding Achievements in Evolutionary Computation in Europe
Krishna Dev Oruganty
I can best describe myself as a simulation biologist. I am interested in simulating life processes at multiple scales. From the atomic scale to understand protein function to cellular or systems scale to understand physiological processes. My main tool is the computer which I use to analyze, understand and predict biology. Secondary tools are in vitro biochemistry and biophysics experiments that I use to validate my predictions.
Vera Pancaldi
I was trained as a physicist at Imperial College London and soon found my way in systems and computational biology. Since 2018 I lead a computational biology team at the Cancer Research Center of Toulouse (CRCT) working on modelling cancer and its interactions with the immune system.
I have worked on various projects on stress response in fission yeast and prediction of protein interactions (in the group of Jurg Bahler at Sanger Institute/University College London), epigenomics and hybrid vigour in plants (with David Baulcombe at Cambridge University) and integrative epigenomics in cancer (with Alfonso Valencia at CNIO, Madrid and Barcelona Supercomputing Center). My main current focus is understanding the relationship between genome architecture and heterogeneity at various levels and relating heterogeneity of tumour infiltrating immune cells to patient's prognoses in different cancers. I also co-founded Cambridge Networks Network in 2011, an online forum for scientists interested in networks in Cambridge in beyond.
Jun Pang
Research interests: Formal methods, security and privacy, big data analytics, computational systems biology
Thiago Parente
Scientist in Public Health at the Laboratory of Functional Genomics and Bioinformatics at the Oswaldo Cruz Institute (IOC, Fiocruz), Rio de Janeiro, Brazil. Scientific coordinator of the Institutional Bioinformatics Platform. CNPq Level 2 Research Productivity Scholar (Genetics). Permanent professor at the Graduate program on Systems and Computational Biology IOC, Fiocruz. Graduated in Biological Sciences - Genetics major - from the Federal University of Rio de Janeiro (2006), with a Master's degree in Cell and Molecular Biology from the IOC (2008) and PhD in Biophysics from UFRJ (2012). Through high performance technologies for DNA sequencing and computational data analysis, I investigate the effects of pollution on fauna, using fish as model organisms, and their responses and genetic adaptations to pollutants, especially those involved in the xenobiotic biotransformation system.
Mohammad Zavid Parvez
Mohammad Zavid Parvez is a scholar in computer science with over 16 years of academic and research experience spanning machine learning, biomedical signal processing, cybersecurity, and federated learning. He earned his PhD in Computer Science from Charles Sturt University, Australia, where his research focused on epileptic seizure detection and prediction using EEG signals, and has since held research positions at Charles Sturt University and the ISI Foundation (Italy). He has published extensively in leading journals, including IEEE Transactions on Biomedical Engineering, IEEE Transactions on Neural Systems and Rehabilitation Engineering, and Neurocomputing. He also serves as Topic Editor for Frontiers in Medicine. His current research interests include cyber threat intelligence, privacy-preserving medical data analysis, and AI-driven healthcare solutions.
Gabriella Pasi
Gabriella Pasi is Full Professor at the University of Milano Bicocca, Italy, where she leads the Information Retrieval research Lab within the Department of Informatics, Systems and Communication. Her research activity mainly addresses the definition of models and techniques for a personalized access to information (in particular related to the tasks of information Retrieval and Filtering). She is also working on the analysis of user generated content in social media.