Advisory Board and Editors Data Mining & Machine Learning

Journal Factsheet
A one-page PDF to help when considering journal options with co-authors
Download Factsheet
I told my colleagues that PeerJ is a journal where they need to publish if they want their paper to be published quickly and with the strict peer review expected from a good journal.
Sohath Vanegas,
PeerJ Author
View author feedback

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.

Animal Behavior Bioinformatics Data Mining & Machine Learning Genetics Genomics Neuroscience

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.

Artificial Intelligence Blockchain Cryptography Data Mining & Machine Learning Neural Networks Quantum Computing Security & Privacy Theory & Formal Methods

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.

Artificial Intelligence Bioinformatics Cardiology Computational Biology Data Mining & Machine Learning Data Science Diabetes & Endocrinology Epidemiology Gastroenterology & Hepatology Health Policy Public Health Women's Health

Angelo Ciaramella

Angelo Ciaramella received the Laurea degree (cum laude) in Computer Science and he is Full Professor at the University of Naples “Parthenope”. The main research interests of Angelo Ciaramella are Soft Computing, Machine Learning and Data Mining. In particular he is interested in statistical and Machine Learning approaches for Blind Source Separation, Sparse Coding, Compressive Sensing and Dictionary Learning, for signal processing (i.e., audio, streaming, astrophysical and geological) and feature extraction. Moreover, he has been working on fuzzy and neuro-fuzzy systems for structured and unstructured data. Recently, he is interested for developing Fuzzy Decision Support Systems in risk assessment. He also studied and developed new methodologies for pre-processing, clustering, visualization and assessment of biological, air quality and social network data (e.g., twitter). Recently, he is also interested in signal processing by Deep Learning methodologies in Brain Computer Interfaces. He is associate editor of international journals (i.e., Information Sciences, Soft Computing, International Journal on Artificial Intelligence Tools). He has been co-general Chair (BBCC2023, ITADATA2023, PDP2023, IDCS2019), technical chair (CIBB2018) and organizer chair of Special Sessions. He is in the Program Committee of international conferences. He is a Fellow Member of IEEE and member IEEE Computational Intelligence Society, IEEE Signal Processing, SIREN, GIRPR, AIxIA.

Artificial Intelligence Bioinformatics Brain-Computer Interface Computer Vision Data Mining & Machine Learning Multimedia

Stefano Cirillo

Stefano Cirillo is an Assistant Professor at the Department of Computer Science of the University of Salerno, Italy.

His research interests include Data Profiling, Data Mining, Artificial Intelligence, Data Privacy, and Social Networks, in which he has published several articles in international journals, books, and conference proceedings.

He graduated in Computer Science (cum laude) in 2018, at the Department of Computer Science of the University of Salerno. In 2022 he received the Ph.D. in Computer Science at the University of Salerno, with a Ph.D. course funded by the Programma Operativo Nazionale (PON) 2014-2020.

In 2018 he worked at the Centro Regionale Information Communication Technology (CeRICT) scrl based in Benevento, Italy, for designing, implementing, and developing an intelligent search engine for call-for-tenders in the e-procurement domain. In 2019 he was a visiting researcher at the Datonix SpA in Naples (NA), aimed at the design and development of algorithms for the extraction of profiling metadata from relational and non-relational databases. In 2020 he spent a research period at the Information Systems group of the Hasso Plattner Institute (HPI) affiliated with the University of Potsdam, Germany.

From 2022 to 2023 he was a Research Fellow at the University of Salerno for the research activity within the project "Profiling Data Streams for Anomaly Detection And Online Learning".

In 2022 he was an adjunct professor for the course of Databases, II year, for the Degree course in Computer Science at the Department of Computer Science of the University of Salerno.

Since 2023 he is an Assistant Professor at the University of Salerno for the project "Security and Rights in the CyberSpace (SERICS)".

He was Program Co-Chair of the International DMS Conference on Visualization and Visual Languages (2021) and Conference Co-Chair of the International DMS Conference on Visualization and Visual Languages (2022).

He is the Local Arrangements Chair of the international EDBT/ICDT 2024 Joint Conference and is a member of the program committee of several national and international conferences, including the International Conference On Computer, Software And Modeling (ICCSM), International Conference on Computing Science, Communication and Security (COMS2), International Conference on Big Data Computing Service and Machine (BIGDATASERVICE), International Conference on Advanced Information Science and System (AISS), International Conference on Applications and Systems of Visual Paradigms (VISUAL), International Conference on Networks, Communications and Information Technology (CNCIT), and International Conference on Big Data and Artificial Intelligence (ICBDAI).

He is an Associate Editor of the Journal Multimedia Tools and Applications (Springer) and of the Journal of Visual Language and Computing (JVLC). He is an Editorial Board Member of several international journals, including journal Data Science and Management (DSM), International Journal of Computer Science and Management, and Research Reports on Computer Science (RRCS). He was Lead Guest Editor for the Special Issue "Sentient Multimedia Systems and Universal Visual Languages" [1225] on Multimedia Tools and Applications (Springer) and Guest Editor of several Special Issues published in international journals.

He is a reviewer of several international journals, including Intelligent Systems (IEEE), Expert Systems with Applications (Elsevier), Information and Processing Management (Elsevier), Journal of Data and Information Quality (ACM), and Neural Computing and Applications (Elsevier).

Artificial Intelligence Data Mining & Machine Learning Data Science Databases

Giulia Cisotto

Giulia Cisotto is an Assistant Professor (tenure-track) at the Department of Mathematics, Informatics, and Geosciences of the University of Trieste (Italy). She is an IEEE Senior member and a GRIN member. Her research activity is mainly focused on the processing and modeling of complex systems via machine learning and deep learning techniques, with particular expertise in multi-dimensional electroencephalographic (EEG) time-series. She has always been collaborating with several companies and research Hospitals to promote the impact of academic research into the Society. She is also active in the dissemination of science (as a member of the Association "La Via delle Scienze", Italy) and in the promotion of innovative teaching of science in the Academia.

Artificial Intelligence Brain-Computer Interface Computational Science Data Mining & Machine Learning Data Science Neural Networks Neuroscience

Edith Cohen

Edith Cohen is (visiting) full professor at Tel Aviv University. Until 2014 she was a Principal Researcher at Microsoft Research (Silicon Valley) and between 1991 and 2012 she was at AT&T Labs. She received a Ph.D in Computer Science from Stanford University in 1991. Her research interests include algorithms, mining and analysis of massive data, optimization, and computer networking. She is a winner of the IEEE ComSoc 2007 Bennett prize, and an author of 20+ patents and 100+ publications.

Algorithms & Analysis of Algorithms Data Mining & Machine Learning Data Science Databases Network Science & Online Social Networks

Daniele Filippo Condorelli

Degrees M.D.: University of Catania (Italy), 1974-1980. Specialist in Neurology: University of Catania, 1980-1984. Ph.D. in Medical Biochemistry and Biology: University of Bari and Catania, 1984-1986.
Professional positions: 2001- today: Full professor of Biochemistry, School of Medicine, University of Catania; 1988-2000: Associate Professor of Biochemistry, University of Catania;. 2005-2009: Director of the School of Clinical Biochemistry; 2007-2013 coordinator of the PhD School in Translational Biomedicine.
Scientific publications.
1981-2018: 134 scientific papers in international peer-reviewed journal and 25 book chapters. Citations (years 1985-2018): 4612; without self-citations: 4367 (Web of Science, ISI); h-index 40
Research training abroad: 1983: Research associate at the MRC Developmental Neurobiology Unit. London (Dir.: Prof. R. Balazs); 1989-1990: Research associate at the Neurobiochemistry Group of the Mental Retardation Center, UCLA, Los Angeles (Dir.: Prof J. De Vellis)
Research interests: Neurotransmitter and neurotrophin receptors in glial cells; structure and expression of the glial fibrillary acidic gene; molecular biology of neuronal connexins; Experimental therapy of glioma tumors; Cancer genomics; Transcriptomics.
Council of International Scientific Societies:
2000-2004: elected member of the Council of the International Society for Developmental Neuroscience. 2007-2011: elected member of the Council of the International Society for Neurochemistry.

Bioinformatics Cell Biology Data Mining & Machine Learning Gastroenterology & Hepatology Genomics Molecular Biology Omics Technologies Oncology

Fabio Cumbo

Fabio Cumbo is a Postdoctoral Researcher at the Center for Computational Life Sciences of the Cleveland Clinic's Lerner Research Institute in Cleveland, OH.

He received his Ph.D. in Computer Science and Automation Engineering from the University of Roma Tre in 2019, and his BSc. and MSc. in Software Engineering from the same University in 2012 and 2014 respectively. From November 2018 to December 2021 he was a Postdoctoral Researcher at the Department of Cellular, Computational and Integrative Biology (CIBIO) of the University of Trento, Italy. Fabio

Cumbo's research mainly focuses on Bioinformatics, Metagenomics, Machine Learning, and Hyperdimensional Computing.

Algorithms & Analysis of Algorithms Artificial Intelligence Bioinformatics Computational Biology Data Mining & Machine Learning Distributed & Parallel Computing

Daniel de Oliveira

Daniel de Oliveira is a professor of computer science at Universidade Federal Fluminense in Brazil. His current research interests include scientific workflows, provenance, cloud computing, data scalable and intensive computing, high-performance computing, and distributed and parallel databases. He serves or served on the program committee of major international and national conferences (VLDB, IPAW, IEEE eScience, SBBD, etc.) and is a member of IEEE, ACM, and the Brazilian Computer Society. He has published many technical papers and is a co-author of the book “Data-Intensive Workflow Management For Clouds and Data-Intensive and Scalable Computing Environments” published by Morgan & Claypool in 2019.

Data Mining & Machine Learning Data Science Databases Distributed & Parallel Computing Scientific Computing & Simulation

Ana Tereza Ribeiro de Vasconcelos

Ana Tereza Vasconcelos is Senior Researcher Scientist at the National Laboratory for Scientific Computing and coordinator of the Bioinformatics Laboratory and the Computational Genomics Unit Darcy Fontoura de Almeida at National Laboratory of Scientific Computation (LNCC). Her team has experience in the area of Bioinformatics and Computational Biology. Using High Performance Computing and AI working on the following topics: Genomics, Development of software applications in Bioinformatics and computational tools applied assembly, annotation and comparison of genomes, metagenomics, exomes and transcriptomics applied to many different model organisms. Since 2020 he has worked in the generation and analysis of SARS-CoV-2 genomes, mainly in the identification of new lineages.

Bioinformatics COVID-19 Data Mining & Machine Learning Data Science Genomics Molecular Biology

María José Del Jesus

She received the M.Sc. and Ph.D. degrees in Computer Science from the University of Granada, Spain, in 1994 and 1999, respectively.
She is an Associate Professor with the Department of Computer Science, University of Jaén, Spain.
Her current research interests include evolutionary fuzzy systems, subgroup discovery, data preparation, neural networks, knowledge extraction based on evolutionary algorithms, and data science.
Director of the Intelligent Systems and Data Mining Research Group.

Artificial Intelligence Data Mining & Machine Learning Data Science Visual Analytics