I am an Associate Professor at Linnaeus University, where my research and teaching center on AI-enabled systems for healthcare and smart environments. My work leverages the power of IoT, machine learning, and deep learning to create practical solutions, from contactless heart monitoring to smart home technologies that support assisted living. I am passionate about using technology to improve well-being and create more intelligent, responsive environments.
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.
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.
Distinguished Professor of Computer Science, Université d'Angers (France); Senior Fellow of the French "Institut Universitaire de France", Working on computational methods for large scale and complex combinatorial optimization problems.
Falk grew up in Germany, got a M.Sc. in Forestry from Universities, Goettingen, Freiburg and Munich with a thesis at NISK/Norway on digital image processing of trees affected by acid rain. He then worked at the EU with a Robert Schuman Scholarship of the European Parliament in Luxemburg, and with a NGO in Bruxelles. In 2001 he got a PhD from the ACWERN at the University of New Brunswick (UNB) in Eastern Canada on pelagic seabirds, Geographic Information Systems (GIS) and data. His postdoc was with the Center of Wildlife Ecology at Simon Fraser University in Vancouver about Marbled Murrelets. He then got a Killam Scholarship with the University of Calgary working on Grizzly Bear habitat future models in the Rocky Mountains.
In 2002 he became a Professor of Wildlife Ecology in his EWHALE lab with the University of Alaska-Fairbanks. Falk works with his students world-wide on landscapes, oceans and the atmosphere focusing on the conservation of biodiversity and habitats. He has over 350 publications, including 9 books and many Open Access datasets and metadata on over 2000 species
Lydia Kavraki received her B.A. in Computer Science from the University of Crete in Greece and her Ph.D. in Computer Science from Stanford University. Her research contributions are in physical algorithms and their applications in robotics as well as in computational structural biology and biomedciine. Kavraki is the recipient of the ACM Grace Murray Hopper Award; a Fellow of ACM, IEEE, AAAS, AAAI, and AIMBE; and a member of the Institute of Medicine of the National Academies.
Dr. Zhiyi Li received his Ph.D. degree in Electrical Engineering from Illinois Institute of Technology in 2017. He received an M.E. degree in Electrical Engineering from Zhejiang University (Hangzhou, China) in 2014 and a B.E. degree in Electrical Engineering from Xi’an Jiaotong University (Xi’an, China) in 2011. From August 2017 to May 2019, he was a senior research associate at Robert W. Galvin Center for Electricity Innovation at Illinois Institute of Technology. Since June 2019, he has been with the College of Electrical Engineering, Zhejiang University(Hangzhou, China) as a research professor. His research interests lie in the application of state-of-the-art optimization and control techniques in smart grid design, operation and management with a focus on cyber-physical security. He has already authored/co-authored over 60 refereed journal articles in these areas. He is an associate editor of 4 other international journals (IEEE Access, Journal of Modern Power Systems and Clean Energy, Journal of Electrical Engineering and Technology, and IET Journal of Engineering) and a reviewer of over 30 international journals (including IEEE Transactions on Power Systems, IEEE Transactions on Smart Grid, IEEE Transactions on Sustainable Energy, and IEEE Transactions on Power Delivery).
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.
Kurt Mehlhorn is Director at the Max Planck Institute for Informatics.
Dr. Maria Navarro-Caceres is an Associate Professor and Computer Scientist at the University of Salamanca.
She is interested in ML and DL proposals, and also in the application of computing technologies to artistic and musical perspectives.
I received the BEng (Hons) in Electrical and Computer Systems Engineering and the Ph.D. in Fault Diagnosis and Control Systems from Monash University in 2006 and 2009, respectively. I am currently a Reader in Mechatronics Engineering and Control at the School of Engineering, Ulster University, UK, and I am attached to the Engineering Research Institute.
My research interests include fault diagnosis, mathematical modelling, digital twin, and data analytics for anomaly detection and classification.
In 2014–2015, I was a postdoctoral researcher at the Division of Vehicular Systems, Linköping University, Sweden, where I worked with Volvo Car Corporation (VCC) on advanced fault diagnosis schemes in vehicular engines using model-based and data-driven methods. For this research, I was instrumental in developing a Digital Twin/Simulation Testbed on the MATLAB/Simulink platform for realistic simulation and testing of residuals generation and fault diagnosis methods. This research work was published in the IEEE Control Systems Magazine and the Digital Twin/Simulation Testbed can be downloaded via the main hosting site or its mirror at Linköping University.
Throughout my career, I have secured more than £6.5 million in research grants from various funders such as the Engineering and Physical Sciences Research Council (EPSRC), UK Research and Innovation (UKRI), Global Challenges Research Fund (GCRF), and the Northern Ireland Department for the Economy in the UK; the Fundamental Research Grant Scheme (FRGS), Exploratory Research Grant Scheme (ERGS), and EScienceFund from the Ministry of Higher Education in Malaysia; and industries such as Volvo Car Corporation in Gothenburg, Sweden.
Overall, I have successfully supervised no less than 2 postdoctorals, 8 PhD, and 3 Master’s by Research candidates.
I am also currently attached to the Digital Catapult as an awardee of the EPSRC Innovation Launchpad Network+ (ILN+) Researcher in Residence Scheme. This research project aims to develop an energy mapping Digital Twin technology that contributes towards net zero in wind turbine energy. This technology encompasses the entire energy lifecycle, from mining through storage to utilisation in Northern Ireland (NI). This project also involves collaboration with the Offshore Renewable Energy Catapult.
Other highlights include being a co-investigator in SAFEWATER, a £5 million project funded by UKRI-GCRF, where I led the development and the optimisation of embedded algorithms to control low-cost water disinfection technologies used in the rural areas in South America.
In addition, during the COVID-19 pandemic, I led the Modelling and Forecast Task Force at Ulster where we worked with the Southern Health and Social Care Trust to provide analysis to the Government Specialist Modelling Response Expert Group (SMREG) in Northern Ireland. The main purpose of the project was to validate and inform the SMREG as well as help governing bodies in Northern Ireland to better plan for intervention measures and ultimately flatten the curve. I was also a member of the COVID-19 Task Force set up by the IEEE Region 8 community. In addition, I led a team of researchers and data scientists from Ulster and Queen’s University Belfast to work with the Incident Controller for the State Health Incident Control Centre and Deputy Chief Health Officer of the Department of Health in Western Australia to model the outbreak of COVID-19 on commercial cargo vessels.
I am a Senior Member of the IEEE and I am currently the Vice-Chair of the IEEE Control Systems Society (CSS), UK and Ireland Chapter.
I am the Moderator for the IEEE TechRxiv, the Associate Editor for IEEE Access, Editor for PeerJ Computer Science, and Section Editor for Sage Science Progress.
I am also an Adjunct Senior Research Fellow with Monash University Malaysia where I served as a Lecturer from 2009, and subsequently as Senior Lecturer till 2017.
Inventor of innovations that make today's network protocols scalable, robust, and self-organizing. In particular, link state routing, spanning tree, and TRILL. Also, innovations in security including distributed algorithms resilient against malicious participants, assured expiration of data from storage, and PKI trust models.
Awards
- National Inventors Hall of Fame induction (2016)
- Internet Hall of Fame induction (2014)
- SIGCOMM Award (2010)
- USENIX Lifetime Achievement Award (2006)
- Recipient of the first Anita Borg Institute Women of Vision Award for Innovation in 2005
- Silicon Valley Intellectual Property Law Association Inventor of the year (2003)
- Honorary Doctorate, Royal Institute of Technology (June 28, 2000)
- Twice named as one of the 20 most influential people in the industry by Data Communications magazine: in the 20th anniversary issue (1992) and the 25th anniversary issue (1997). Perlman is the only person to be named in both issues.
- Fellow of the Association for Computing Machinery, class of 2016