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.
Björn W Schuller
Björn W. Schuller received his diploma in 1999, his doctoral degree in 2006, and his habilitation and was entitled Adjunct Teaching Professor in the subject area of Signal Processing and Machine Intelligence in 2012 all in electrical engineering and information technology from TUM in Munich/Germany. He is Full Professor and Chair of Complex and Intelligent Systems at the University of Passau/Germany and a Senior Lecturer (Associate Professor) in Machine Learning at Imperial College London/UK.
Eftim Zdravevski
Head of the Institute for Intelligent Systems and an Associate Professor at the Faculty of Computer Science and Engineering of the Saints Cyril and Methodius University in Skopje, Macedonia.
His research interests are in FinTech, Big Data, ML, cloud computing, time series analysis, etc.
Founder and CEO of MAGIX.AI - a company specialized in applied AI for predictive maintenance, FinTech, AdTech, and E-commerce. Participated in and led many national and international research projects related to ML in various domains.
Published over 150 papers in peer-reviewed international conferences and top-ranked journals, of which over 100 are indexed in Web of Science.
Aurora Saibene
Aurora Saibene is a Post Doctoral Research Fellow in Computer Science at the University of Milano-Bicocca, whose research activities are mainly focused on brain-computer interfacing, human-machine interaction, multimedia signal processing, and neuroinformatics.
She took her Bachelor's, Master's Degree, and PhD in Computer Science at the University of Milano-Bicocca in 2015, 2018, and 2022, respectively.
Her PhD thesis in Computer Science focused on the design of a Flexible Pipeline for Electroencephalographic Signal Processing and Management, wanting to provide a set of suggestions and technical procedures to pre-process, normalize, manage features, and classify a particularly tricky signal like the electroencephalographic one in different contexts. She has especially focused on the field of motor movement and imagery as well as on emotion recognition and she is now facing the challenge of employing wearable technologies with a multimodal approach to provide efficient and reliable brain-computer interfacing and human-centric systems in different fields of application.
Stefan Güttel
Stefan Güttel is Professor of Applied Mathematics at the University of Manchester. His work focuses on computational mathematics, including numerical algorithms for large-scale linear algebra problems arising with differential equations and in data science. He has been awarded the 2021 SIAM James H. Wilkinson Prize in Numerical Analysis and Scientific Computing, the 2023 Taussky–Todd Prize of the International Linear Algebra Society, and holds a Royal Society Industry Fellowship.
Marta Giovanetti
My research focuses on investigating the patterns of gene flow in pathogen populations, focusing in phylogenetics and phylogeography as tools to recreate and understand the determinants of viral outbreaks and how this information can be translated into public policy recommendations. More specifically, my research focuses on recent arboviral outbreaks in Latin America (Zika, Chikungunya, Dengue and Yellow fever viruses and more recently SARS-CoV-2 in Brazil, Italy and South Africa), combining genetic, spatial and ecological information. I am interested in the epidemiology and ecology of viruses in natural populations. My research involves developing and applying techniques to integrate virus genetic data with traditional clinical and demographic data.
Takayuki Kanda
Takayuki Kanda is a Group Leader at ATR Intelligent Robotics and Communication Laboratories, Kyoto, Japan. He is one of the starting members of Communication Robots project at ATR. He has developed a communication robot, Robovie, and applied it in daily situations, such as peer-tutor at elementary school and a museum exhibit guide. His research interests include human-robot interaction, interactive humanoid robots, and field trials.
Trang Do
Dr. Trang Do earned her PhD degree from the National University of Singapore in 2013. She is a proactive and motivated educator and data scientist, showcasing a track record of effectively managing expansive and intricate projects alongside engagements with stakeholders and government agencies. Her expertise spans data and computer science, coupled with a foundation in economics and bioinformatics, driving an ongoing pursuit of professional development. Her research interests encompass a wide scope within data science, intelligent systems, and interdisciplinary computing. Presently, her primary focus centers on machine learning, deep learning, explainable AI, data analysis, and visualization, particularly within the realms of health informatics, drug discovery, bioinformatics, tourism, and intelligent systems.
Marco Dorigo
Research director for the Belgian F.R.S.-FNRS and co-director of IRIDIA, the AI lab of the Université Libre de Bruxelles. Editor-in-Chief, Swarm Intelligence, Springer. Recipient of: Italian Prize for Artificial Intelligence (1996), Marie Curie Excellence Award (2003), Dr. A. De Leeuw-Damry-Bourlart award in applied sciences (2005), Cajastur International Prize for Soft Computing (2007), ERC Advanced Grant (2010), and IEEE Frank Rosenblatt Award (2015). Elected Fellow of IEEE, AAAI, and ECCAI.
Ian Taylor
Ian Taylor is a Reader Cardiff University. He has a strong track record specialising in the workflow and data distribution areas, with application in audio, astrophysics and healthcare. Ian wrote a 2nd edition professional distributed computing book (sold 2000+) and was lead editor for “Workflows for eScience”. Ian has guest edited for the Journal of Grid Computing and co-chaired the OGF Workflow Management Research Group. He has published 110 papers.
Michela Quadrini
Current research is focused on Artificial Intelligence, Bioinformatics, Formal methods and Languages for the modelling, analysis and verification of Distributed Systems.
Amit Sheth
Educator, Researcher, and Entrepreneur. Founding Director - AI Institute, NCR Professor, and Professor of Comuter SC & Engg, University of South Carolina. Earlier, LexisNexis Ohio Eminent Scholar. Executive Director, Ohio Center of Excellence in Knowledge-enabled Computing (Kno.e.sis) at Wright State University. Elected Fellow IEEE, AAAS, AAAI, ACM, and AAIA. Working towards a vision of Computing for Human Experience. His recent work has focused on knowledge-infused learning and neuro-symbolic AI, semantic-cognitive-perceptual computing, and semantics-empowered Physical-Cyber-Social computing. He coined the terms: Smart Data, Semantic Sensor Web, Semantic Perception, Citizen Sensing, etc. He has (co-)founded four companies, including the first Semantic Search company in 1999 that pioneered technology similar to what is found today in Google Semantic Search and Knowledge Graph, ezDI, which developed knowledge-infused clinical NLP/NLU, and Cognovi Labs at the intersection of emotion and AI. He is particularly proud of the success of his >45 Ph.D. advisees and postdocs.
Kristina Lerman
Kristina Lerman is a Project Leader at the Information Sciences Institute and holds a joint appointment as a Research Associate Professor in the USC Viterbi School of Engineering's Computer Science Department. Her research focuses on applying network-based and machine learning methods to problems in social data analysis and social computing.