Advisory Board and Editors Data Mining & Machine Learning

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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

Artificial Intelligence Data Mining & Machine Learning Data Science

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.

Artificial Intelligence Biochemistry Bioinformatics Biophysics Computational Biology Computer Vision Data Mining & Machine Learning Databases Genomics Molecular Biology Natural Language & Speech Text Mining

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.

Bioinformatics Computational Biology Data Mining & Machine Learning Genomics Network Science & Online Social Networks

Jun Pang

Research interests: Formal methods, security and privacy, big data analytics, computational systems biology

Computational Biology Data Mining & Machine Learning Security & Privacy Social Computing Software Engineering Theory & Formal Methods

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.

Biochemistry Biodiversity Bioinformatics Biosphere Interactions Computational Biology Conservation Biology Data Mining & Machine Learning Data Science Ecology Environmental Contamination & Remediation Environmental Impacts Environmental Sciences Evolutionary Studies Freshwater Biology Genetics Genomics Global Health Omics Technologies Scientific Computing & Simulation Toxicology Zoology

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.

Artificial Intelligence Data Mining & Machine Learning Data Science Security & Privacy

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.

Data Mining & Machine Learning Data Science Digital Libraries Human-Computer Interaction Network Science & Online Social Networks Social Computing Spatial & Geographic Information Systems World Wide Web & Web Science

Jian Pei

Jian Pei is currently Professor of Computing Science at the School of Computing Science at Simon Fraser University, Canada.

Data Mining & Machine Learning Data Science Databases

Barbara Pes

Barbara Pes obtained her laurea degree in Physics from the University of Cagliari (Italy) in 2001. From 2002 to 2005 she collaborated with the Database and Data Mining Group at the Department of Mathematics and Computer Science, University of Cagliari. Since 2006 she has been working at the same department as a University Researcher (permanent position). Here she teaches/taught Foundations of Computer Science, Database and Data Mining courses.

Barbara Pes has participated in several research projects on Web-based Information Systems, Service-Oriented Architectures, Data Integration, High-dimensional Data Analysis, and Bioinformatics. Currently, her main research interests are in the field of Data Mining and Machine Learning, Classification of High-dimensional Data, Feature Selection. She is author of more than 60 papers published in international conferences, books and journals.

Data Mining & Machine Learning

Marco Piangerelli

Dr. Marco Piangerelli had his M.Sc. in Bioengineering from the University of Bologna and got his Ph.D. in Computer Science from the University of Camerino, where he is currently a Research Associate. His research interests are mainly on Unsupervised techniques for Machine Learning and Data Science in Manufacturing and Bio Science, Self-Adaptive Systems, and Topological Data Analysis. He is the author of many publications and was a PC member for many conferences and Workshops (AAAI-MAKE 2022-23-24 Spring Symposium, SACAIR 2023, DESRIST 2023, ATDA2019). He co-organized the 9th International Workshop on Engineering Energy Efficient InternetWorked Smart seNsors (E3WSN ) hosted by the 37th International Conference on Advanced Information Networking and Applications (AINA) at the Federal University of Juiz de Fora, Brazil. He has experience in Technological transfer projects and actively collaborates with international companies (INGKA, Schnell S.p.A., Sigma S.p.A., and Nuova Simonelli S.P.A.) and Italian ones (Syeew S.r.l). In 2024, he will be a Visiting Researcher at Addis Ababa University (Ethiopia) to work on topics related to his research fields.

Adaptive & Self-Organizing Systems Artificial Intelligence Brain-Computer Interface Computer Vision Data Mining & Machine Learning Data Science Natural Language & Speech Neural Networks

Stephen R Piccolo

He earned a B.S. degree in Management Information Systems from BYU in 2001 and then worked as a software engineer for five years at Intel Corporation in Chandler, Arizona. In 2011, he received a PhD in Biomedical Informatics from the University of Utah (advised by Dr. Lewis J. Frey). From 2011-2014, he was postdoctoral researcher jointly at the University of Utah (Department of Pharmacology and Toxicology, advised by Dr. Andrea H. Bild) and Boston University School of Medicine (Division of Computational Biomedicine, advised by Dr. W. Evan Johnson). He teaches classes in biology and bioinformatics.

The Piccolo lab's overarching goal is to use advanced computational approaches to act on large and complex data sets in an interdisciplinary approach. As such, the lab integrates knowledge and techniques across biology, computer science, medicine, and statistics using "dry lab biology'' to take advantage of massive, publicly available databases.

Bioinformatics Computational Biology Computational Science Computer Education Data Mining & Machine Learning Data Science

Brett E Pickett

Dr. Brett Pickett is an Assistant Professor in the Microbiology and Molecular Biology Department at Brigham Young University. He completed his B.S degree in Microbiology from BYU in 2005, his Ph.D. training in Microbiology at the University of Alabama at Birmingham, and his postdoctoral training in Pathology at the University of Texas Southwestern Medical Center at Dallas. He then obtained additional experience in industry, and at the J. Craig Venter Institute, where he led investigative studies in viral comparative genomics and the human transcriptional response during viral infection. His research develops data mining methods, applies machine learning techniques, and use advanced statistical workflows to better understand how human cells respond during infection.

Bioinformatics Computational Biology Data Mining & Machine Learning Data Science Databases Evolutionary Studies Genetics Genomics Infectious Diseases Microbiology Molecular Biology Oncology Virology