Academic Editors
The following people constitute the Editorial Board of Academic Editors for PeerJ Computer Science. These active academics are the Editors who seek peer reviewers, evaluate their responses, and make editorial decisions on each submission to the journal. Learn more about becoming an Editor.
Christopher J Mungall
I am a Computer Research Scientist in the Environmental Genomics and Systems Biology division at Lawrence Berkeley Laboratory. My work focuses on computational methods for representing and interpreting complex biological data, in particular through the development and application of knowledge representation structures such as ontologies.
Mauro Birattari
A Research Director of the Belgian Fonds de la Recherche Scientifique—FNRS at IRIDIA, Université libre de Bruxelles.
Dr. Birattari co-authored more than 100 peer-reviewed scientific publications in the field of computational intelligence. His research interests focus on swarm intelligence, collective robotics, machine learning, and on the application of artificial intelligence techniques to the automatic design of algorithms.
Sandra Gesing
Scientific Outreach and DEI Lead at the Discovery Partner Institute, University of Illinois Chicago
Before: Associate Research Professor (Dep. of Computer Science and Engineering and Center for Research Computing) at the University of Notre Dame, USA
Research associate in the Data-Intensive Research Group at the University of Edinburgh, UK; Research Associate in the Applied Bioinformatics Group at the University of Tübingen, Germany.
Perennial experience in industry as head of a system programmer group, project manager, system developer.
Yuan Shang
Dr. Yuan Shang works on Alzheimer's Disease (AD) at the University of Arizona. He combines any potential methods and data to search potential therapeutic opportunities for AD. He is an expert on omics data analysis, multi-omics integrations, network-based pattern recognition, and machine learning-based biomarker discoveries.
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).
Rajeev Agrawal
Big data Analytics, Cloud Computing, Topic Modelling, and Geo Spatial information systems. Member of IEEE, ACM, and ASEE. Published more than 100 referred journal and conference papers and 4 book chapters.
Andrea Esuli
Andrea Esuli is a researcher of the Italian National Research Council. His research interests are in the fields of multimedia information retrieval, machine learning, and text classification.
Ashutosh Dhar Dwivedi
Ashutosh Dhar Dwivedi is an Assistant Professor in Cybersecurity Group, Aalborg University, Copenhagen, Denmark. His research field includes Machine Learning, Cryptography, Post Quantum Cryptography, Security and Blockchain.
He completed his PhD from the Polish Academy of Sciences, Poland in March 2020. He received the B.Sc. degree from the University of Allahabad, Prayagraj, India, and the MCA degree from the Amity School of Computer Sciences, Noida, India.
Prior to joining Aalborg University, he worked as Postdoctoral Researcher at Department of Digitalization, Copenhagen Business School, Denmark, DTU Compute (Cyber Security Section), Technical University of Denmark, full time Visiting Researcher at the University of Waterloo, Ontario, Canada, Research Associate at the Brandon University, Manitoba, Canada, Research Employee and PhD at Polish Academy of Sciences, Warsaw, Poland and Research Scholar at the Military University of Technology, Warsaw, Poland.
He has a rich industry experience as well. He was an Intern (under his master's project) with the prestigious organization "Center for Railway Information Systems, New Delhi," governed by the Ministry of Railways, India. He was with organizations related to software development projects for two years. In 2015, he moved to Poland and started a career in cryptography research.
Chenghong Gu
Dr Chenghong Gu currently is a Lecturer with the Department of Electronic and Electrical Engineering, University of Bath, Bath, UK. Previously, he was EPSRC Research Fellow with the University of Bath. He received the Master’s degree from the Shanghai Jiao Tong University, Shanghai, China, in 2007 and PhD degree from the University of Bath, U.K, in 2010, both in electrical engineering. His major research interest is in the multi-vector energy system, smart grid planning and operation, power economics and markets. Dr Gu’s research has been supported by UK funding agency (EPSRC), the industry (NPG, NGC, and WPD), and the UK government (DECC). He now is the Subject Editor IET Smart Grid.
Tony Givargis
Tony Givargis is a Computer Science Professor at the University of California, Irvine (UCI) where he is currently serving as the Department Chair. From 2011 until 2016, he served as the Associate Dean for Student Affairs in the School of Information & Computer Sciences at UCI. He received his BS and PhD in Computer Science from the University of California, Riverside in 1997 and 2001, respectively. He Co-Founded a VC-backed technology startup in 2013 and has served as an expert witness in a number of high profile legal proceedings. Professor Givargis conducts research in the general area of embedded systems with an emphasis on system software, advanced compilation for targeted applications, computational storage devices, accelerators and high dimensional computing. He has authored over 120 peer reviewed papers, is a named inventor on 13 issued US patents and has co-authored two popular textbooks on embedded systems design. Professor Givargis has received numerous teaching, service and research awards, including the Frederick Emmons Terman Award, presented annually to an outstanding young electrical engineering educator by the Electrical and Computer Engineering Division of the American Society for Engineering Education.
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.
Rossano Schifanella
Rossano Schifanella is an associate professor of computer science at the University of Turin and a researcher at ISI Foundation, where he is a member of the Data Science for Social Impact and Sustainability group. His research embraces the creative energy of a range of disciplines across machine learning, urban science, computational social science, complex systems, and data visualization. He leverages data-driven approaches to model the behavior of (groups of) individuals and their interactions in space and time, aiming at understanding the interplay between online and offline social behavior. He is passionate about understanding the dynamics of complex phenomena in modern cities and building interactive web interfaces to explore urban spaces and access human knowledge through geography.