Markus Endler obtained his Dr. rer. nat. in Computer Science from the Technical University of Berlin (1992), and the Professor Livre-docente title (Habilitation) from the University of São Paulo (2001). From 1989 to 1993 he worked as a researcher at the GMD Research Institute Karlsruhe (Germany), and from 1994 to 2000 as an Assistant Professor at the Institute of Mathematics and Statistics of the University of São Paulo (USP). In 2001 he joined the Department of Informatics of the Pontifícia Universidade Católica in Rio de Janeiro (PUC-Rio), where he is currently Associate Professor. His main research interests include Mobile and Pervasive Computing, IoT Middleware Architectures. Distributed Algorithms for Cooperation and Consensus, Online Data Analytics, and Data Stream Processing. As of 2020, he has supervised 13 PhD thesis and 30+ M.Sc. dissertations.
Massimiliano Fasi is a Lecturer in Software Engineering at the School of Computer Science of the University of Leeds. He obtained a PhD from the University of Manchester in 2019, and has held positions in the UK (University of Manchester and Durham University) and in Sweden (Örebro University).
His research interests include scientific computing, computer arithmetic, and numerical analysis, with particular focus on numerical linear algebra.
I am a computer scientist with a predilection for building software systems (and, more recently, for deploying services) that solve problems in the sciences. I am a Distinguished Fellow at Argonne National Laboratory and a Professor at the University of Chicago. I am affiliated, in particular, with the Department of Computer Science, Data Science and Learning Division, and Institute for Molecular Engineering.
Luiz Gadelha works in the German Human Genome-Phenome Archive (GHGA) at the German Cancer Research Center (DKFZ) in Germany and the National Laboratory for Scientific Computing (LNCC) in Brazil. He received his D.Sc. degree in Computer and Systems Engineering from the Federal University of Rio de Janeiro, Brazil. He has been involved in the research and development of parallel and distributed scientific workflow management systems and scientific databases. He has participated in research projects in the bioinformatics and biodiversity application areas. His main research interests are scientific data management, computational reproducibility, and high performance computing.
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.
Daniel Grosu is an Associate Professor in the Department of Computer Science at Wayne State University. His research focuses on cloud and edge computing, parallel and distributed algorithms, approximation algorithms, and topics at the intersection between computer science, game theory and economics.
Marieke Huisman is a professor in Software Reliability, leading the Formal Methods and Tools group at the Univ. of Twente, Netherlands. She obtained her PhD in 2001 from the Univ. of Nijmegen, in the area of semantics and verification of sequential Java programs. She worked 8 years at INRIA Sophia Antipolis, France on verification of concurrent programs. In 2008 she joined the UT. She leads the development of the VerCors program verifier for concurrent software. For this work, she has received the support of several personal grants, such as an ERC Starting Grant, and a Vici grant from the Dutch Science Organisation. She has been chairing Versen, the Dutch association of software researchers, and works hard to improve the overall visibility of software research.
Dan's interest is in the development and use of advanced cyberinfrastructure to solve challenging problems at multiple scales. His technical research interests are in applications, algorithms, fault tolerance, and programming in parallel and distributed computing, including HPC, Grid, Cloud, etc. He is also interested in policy issues, including citation and credit mechanisms and practices associated with software and data, organization and community practices for collaboration, and career paths for computing researchers.
In 1991 Marco Lapegna received his PhD in Applied Mathematics and Computer Science at the University of Naples Federico II (Italy), and since 2001 is a professor of Computer Science at the Department of Mathematics and Applications of the same university.
His main research interests concern methods, algorithms, and software for parallel and distributed computing environments applied to computational mathematics and machine learning, taking into account the influence of the technological evolution on them (cluster computing, multicore computing, grid computing, cloud, and edge computing). He has an active academic life with several institutional coordination duties.
Miriam Leeser is Professor of Electrical and Computer Engineering at Northeastern University. She has been doing research in hardware accelerators, including FPGAs and GPUs, for decades, and has done ground breaking research in floating point implementations, unsupervised learning, medical imaging and privacy preserving data processing. She received her BS degree in Electrical Engineering from Cornell University, and Diploma and Ph.D. Degrees in Computer Science from Cambridge University in England. She has been a faculty member at Northeastern since 1996, where she is head of the Reconfigurable Computing Laboratory and a member of the Computer Engineering group. She is a senior member of ACM, IEEE and SWE. Throughout her career she has been funded by both government agencies and companies, including DARPA, NSF, Google, MathWorks and Microsoft. She is the recipient of an NSF Young Investigator Award and the prestigious Fulbright Scholar Award.
My research group website is: https://rcl.sites.northeastern.edu/
Pengcheng Liu is a member of IEEE, IEEE Robotics and Automation Society (RAS), IEEE Control Systems Society (CSS) and International Federation of Automatic Control (IFAC). He is also a member of the IEEE Technical Committee on Bio Robotics, Soft Robotics, Robot Learning, and Safety, Security and Rescue Robotics. Dr Liu is an Associate Editor of IEEE Access, PeerJ Computer Science, and he received the Global Peer Review Awards from Web of Science in 2019, and the Outstanding Contribution Awards from Elsevier in 2017. He has published over 70 papers on flagship journals and conferences. He was nominated as a regular Funding/Grants reviewer for EPSRC, NIHR and NSFC and he has been leading and involving in several research projects and grants, including EPSRC, Newton Fund, Innovate UK, Horizon 2020, Erasmus Mundus, FP7-PEOPLE, NSFC, etc. He serves as reviewers for over 30 flagship journals and conferences in robotics, AI and control. His research interests include robotics, machine learning, automatic control and optimization.
Alessio Martino graduated summa cum laude in Communications Engineering at University of Rome "La Sapienza", Italy, 2016. From 2016 to 2019, he served as PhD Research Fellow in Information and Communications Technologies at the same University (Department of Information Engineering, Electronics and Telecommunications), with a final dissertation on pattern recognition techniques in non-metric domains. During his PhD, he also served as scientific collaborator with Consortium for Research in Automation and Telecommunication, Rome, Italy.
After obtaining the PhD, he was granted a 1-year Post Doctoral Research Fellowship at University of Rome "La Sapienza" and a 1-year Post Doctoral Research Fellowship at the Italian National Research Council (Institute of Cognitive Sciences and Technologies). Since February 2022, he is Assistant Professor of Computer Science at LUISS University.
His research interests include machine learning, computational intelligence and knowledge discovery. Currently he's focusing on large-scale machine learning, advanced pattern recognition systems, big data analysis, parallel and distributed computing, granular computing and complex systems modelling, in applications including bioinformatics and computational biology, natural language processing and energy distribution networks.
He serves as Editor for several journals and regularly serves as Technical Program Committee member for several international conferences. Alessio Martino is also a member of the IEEE.