Advisory Board and Editors Data Science
Yonghong Peng
Dr. Peng is a Professor of Data Science at the University of Sunderland. He is a Principal Investigator in Bioinformatics and Systems Biology and Medicine, and Principal Data Scientist working on Big Data Integration, Data Mining and Computational Intelligence. Dr. Peng's Data Science and BioMedical informatics (DS & BMI) research group focuses on development of innovative data analytics approaches to enable systematical analysis of biological data, medical images, and healthcare data and to gain new knowledge and insights from the integrative analytics of diverse data sources.
Silvio Peroni
I hold a Ph.D. degree in Computer Science and I am an Associate Professor at the Department of Classical Philology and Italian Studies, University of Bologna, where I teach 'Basic Informatics' and 'Computational Thinking and Programming'.
I am an expert in document markup and semantic descriptions of bibliographic entities using OWL ontologies. I am one of the main developers of the SPAR (Semantic Publishing and Referencing) Ontologies, Co-Director of OpenCitations, and founding member of the Initiative for Open Citations (I4OC).
I am an Editorial Board member of Data Science, PeerJ Computer Science, and I am member of the Digital Humanities Advanced Research Centre (/DH.arc), part of the Advisory Board of DBLP and Qeios, Ambassador of Figshare and PeerJ, and member of the Association for Computing Machinery, of the International Society for Scientometrics and Informetrics, and of the Associazione per l’Informatica Umanistica e la Cultura Digitale.
Among my research interests are Semantic Web technologies, markup languages for complex documents, design patterns for digital documents and ontology modelling, and automatic processes of analysis and segmentation of documents. In particular, my recent works concern the empirical analysis of the nature of scholarly citations, bibliometrics and scientometrics studies, visualisation and browsing interfaces for semantic data, and the development of ontologies to manage, integrate and query bibliographic information.
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.
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.
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.
Douglas Pires
Douglas Pires is a Senior Lecturer in Digital Health in the School of Computing and Information Systems at the University of Melbourne. Previously, he was a group leader and researcher in public health at Oswaldo Cruz Foundation/Brazil. He was also a postdoctoral researcher fellow at the University of Cambridge and University of Melbourne. He received a PhD in Bioinformatics from the Universidade Federal de Minas Gerais/Brazil and a BSc in Computer Science, both with highest honours, by the same university. His research interests include: Computational Biology, Translational Bioinformtaics and Machine Learning.
Alessandro Sebastian Podda
Alessandro Sebastian Podda is a tenure-track Assistant Professor (RTT) at the Department of Mathematics and Computer Science of the University of Cagliari, and he is accredited by the Italian Ministry of University and Research for Associate Professor positions in the scientific sectors 01/B1 (Informatics) and 09/H1 (Computer Engineering). He received a master's degree in Computer Science from the University of Cagliari (cum laude) in 2014 and he got a PhD in Mathematics and Computer Science with a thesis entitled "Behavioural contracts: from centralized to decentralized implementations" in 2018. In 2017, he has been visiting scientist at the Laboratory of Cryptography and Industrial Mathematics of the University of Trento. In 2021, he was formally commissioned to a six month collaboration with the Ispra Joint Research Center (JRC) of the European Commission under the research tender ref. JRC/IPR/2020/VLVP/2916.
Currently, Alessandro Sebastian Podda is Research Unit Coordinator (AI for eHealth and Smart Cities) at the Artificial Intelligence and Big Data Laboratory and former member of the Blockchain Laboratory. He has been also the Work Package Lead of the Doutdes and Sardcoin projects and participates/d in several research projects including AlmostAnOracle, Nomad, Safespotter, Social Glue and Mister. To date, he has been the co-author of no. 18 articles in international journals in the field of computer science, no. 16 conference and workshop proceedings, and 1 book chapter, for which he has over 1450 citations on Google Scholar and over 900 on Scopus, as well as a speaker (eg. LOD 2022, ICCSA 2021, PerAwareCity 2021, MaDaIN 2020, FACS 2015, etc.), co-chair (AISC 2021/2022, HUMAD 2024) and program committee member at numerous international scientific events (eg. HT2022, LOD 2021/2022/2023/2024, IEEE HPCC 2022, IEEE CPS-COM 2021, etc.).
Alessandro Sebastian Podda has been a Member of the Association of Computing Machinery (ACM) and of the Institute of Electrical and Electronics Engineers (IEEE).
Joram M Posma
Lecturer in Cancer Informatics at Imperial College London and Fellow at Health Data Research (HDR) UK. Fellow of the Higher Education Academy (FHEA) and Member of the Royal Society of Chemistry (MRSC).
Michela Quadrini
Current research is focused on Artificial Intelligence, Bioinformatics, Formal methods and Languages for the modelling, analysis and verification of Distributed Systems.
Aaron R Quinlan
Aaron Quinlan, Ph.D., is an Associate Professor in the Departments of Human Genetics and Biomedical Informatics at the University of Utah. He obtained his bachelor’s degree from the College of William and Mary and his Ph.D. from Boston College where he focused on population genetics, new methods for emerging DNA sequencing technologies, and the discovery and characterization of genetic variation. He performed a postdoctoral fellowship at the University of Virginia where he developed expertise in structural variation of mammalian genomes and somatic genome mutation. He started his laboratory at the University of Virginia in 2011 and began his faculty position at the University of Utah in early 2015. Broadly speaking, his research is focused on the development and application of new computational and statistical techniques for understanding the biology of the genome. His team tackles problems with practical importance to understanding genome variation, chromosome evolution and mining genetic variation related to human disease. Understanding the genome is a hard problem: we try to develop new approaches to gain insight into genome evolution in the context of disease.
Sven Rahmann
Prof. Sven Rahmann is professor of Algorithmic Bioinformatics at the Center for Bioinformatics, Saarland University, Saarbrücken, Germany. Previously, Sven was UA Ruhr Professor of Computational Biology and Genome Informatics at the Faculty of Medicine at Duisburg-Essen University (2011-2021), associate professor for Bioinformatics for High-Throughput Technologies at the Chair of Algorithm Engineering, Computer Science Department, TU Dortmund (2007-2011). Sven wrote his doctoral thesis on oligonucleotide design for microarrays in the Computational Molecular Biology group at the Max Planck Institute for Molecular Genetics in Berlin.
Maria Valeria Raimondi
Prof. Dr. Maria Valeria Raimondi, PhD is Assistant Professor in Medicinal Chemistry, University of Palermo, Italy.
In 2018 and 2020, Dr. Raimondi's was a visiting Scientist in Medicinal Chemistry at the University of Vienna and the University of Hamburg respectively. Prior to this Dr. Raimondi was Assistant Professor in Medicinal Chemistry at the University of Palermo
Her scientific interests include:
-Synthesis and antimicrobial evaluation of new compounds with phenoxyacetamidic and iodobenzamidic structure
-Synthesis and antiproliferative activity of new derivatives with triazenic, tetrazepinonic and indazolocarboxyamidic structure
-Design and synthesis of new derivatives with a 4-quinazolinone structure, potential inhibitors of folate receptors
-Synthesis of new pyrrole derivatives related to pyrrolomycin inhibitors of Sortase A
-Synthesis of pyrazole and indazole derivatives, potential inhibitors of CDK1
-Identification of new sigma receptor ligands. Design and synthesis of a beta-aminoketones drug discovery library
-Microwave-assisted organic synthesis (MAOS) of compounds with potential antitumor activity
-Synthesis of polycyclic structures with marked antitumor activity in vitro
-Qualitative and quantitative analysis of industrial hydrocolls from the citrus industries
http://orcid.org/0000-0003-3143-738X
Scopus Author ID: 7006063479