Advisory Board and Editors Algorithms & Analysis of Algorithms
Daniel Grosu
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.
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.
Jin-Kao Hao
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.
Nicholas J Higham
My research is largely concerned with the development and analysis of algorithms in numerical linear algebra. The second edition of my monograph on this topic was published by the Society for Industrial and Applied Mathematics (SIAM) in 2002. My other books include Functions of Matrices: Theory and Computation (SIAM, 2008) and The Princeton Companion to Applied Mathematics (2015), of which I am editor. I am a Fellow of the Royal Society, a SIAM Fellow, and a Member of Academia Europaea. I blog at https://nhigham.com
Sun-Yuan Hsieh
Sun-Yuan Hsieh received the PhD degree in computer science from National Taiwan University, Taipei, Taiwan, in June 1998. In February 2002, he joined the Department of Computer Science and Information Engineering, National Cheng Kung University, and now he is a distinguished professor. His current research interests include design and analysis of algorithms, fault-tolerant computing, bioinformatics, parallel and distributed computing, and algorithmic graph theory.
Falk Huettmann
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
Syed Anas Imtiaz
I am a researcher in wearable medical devices working on creating new technologies for the monitoring and diagnosis if neurological, neurodevelopmental and sleep disorders. My research focuses on developing new biomedical signal processing methods, algorithms and mixed-signal circuit design for wearable systems, low power digital circuits for medical applications and embedded systems design. I am a Research Fellow at Imperial College London where I am developing new technologies for long-term monitoring, management and diagnosis of COPD, sleep disorders, epilepsy, and autism. I am also the Head of Engineering at Acurable leading development and at-scale manufacturing of a wearable medical device and its accompanying smartphone applications for the diagnosis of respiratory disorders.
Lydia E Kavraki
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.
Laszlo T Koczy
Laszlo T. Koczy received the Ph.D. degree from the Technical University of Budapest (BME) in 1977, and the D.Sc. (a postdoctoral degree) from the Hungarian Academy of Science in 1998. He spent his career at BME until 2001, and from 2002 at Széchenyi István University (Győr, SZE), where he was Dean of Engineering, and had been from 2013 to 2022 President of the University Research and of the University Ph.D. Councils. In March 2022 he received the Professor Emeritus title from both universities.
His main research activities have been in the field of Computational Intelligence, especially in fuzzy systems, evolutionary and memetic algorithms, and neural networks, as well as applications in engineering, logistics, management, etc. He has published over 750 research articles with over 3000 fully independent and about 7800 Google Scholar citations. His h-index is 41.
Zhiyi Li
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).
Jingyu Liu
Associate Professor at the Mind Research Network; Adjunct Assistant Professor at the Department of Electrical and Computer Engineering, University of New Mexico. Our MRN lab focuses on developing and optimizing methods and software for quantitative analysis of structure and function in medical images with particular focus on the study of psychiatric illness. We work with many types of data, including functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), electroencephalography (EEG), structural imaging and genetic data.
Alessio Martino
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.