Advisory Board and Editors Computer Vision
Easter S Suviseshamuthu
Dr. Suviseshamuthu is an Associate Research Scientist at the Human Performance and Engineering Research Lab, Kessler Foundation, West Orange, NJ, U.S.A., since Dec. 2015.
He received the B.E. degree in Electronics and Communication Engineering from the Government College of Engineering, Tirunelveli, India (1988), the M.E. degree in Applied Electronics from Bharathiar University, Coimbatore, India (2001), and the Ph.D. in Multispectral Satellite Image Analysis from the Laboratoire des Sciences de l’Information et des Systèmes, Université de la Méditerranée, Marseille, France (2007). He was Post-Doctoral Fellow at the Bioimaging and Biostructure Institute, Italian National Research Council, Naples, Italy, (2008 to 2010), the Department of Mathematical Engineering, Université catholique de Louvain, Louvain-la-Neuve, Belgium, (2010 to 2014), and the GIPSA-Lab, Université Joseph Fourier, Grenoble, France (2014 to 2015).
His research focus encompasses statistical signal processing, blind source separation, medical imaging, optimization on matrix manifolds, machine learning, biomedical signal analysis, and bio-inspired computing. He serves as Associate Editor of IEEE Access.
Sándor Szénási
Sándor Szénási has earned his MSc degree in 2004 from Faculty of Informatics of Eötvös Loránd University, Budapest. He has received his PhD in 2013 from Doctoral School of Applied Informatics (GSAI) of Óbuda University, Budapest.
Currently, he is an associate professor in the Institute of Applied Informatics of John von Neumann Faculty of Informatics, Óbuda University, Budapest. He is the leader of the local CUDA Teaching Center.
His research areas are (data) parallel algorithms, GPU programming and medical image processing. He engages both in theoretical fundamentals and in algorithmic issues with respect to realization of practical requirements and given constraints.
He is the member of the John von Neumann Computer Society and IEEE, and also a reviewer of several conferences and journals.
Yi-Hsuan Tsai
Yi-Hsuan Tsai is the Director of AI at Phiar, leading the AI team to conduct cutting-edge research for real-world AR navigation. He was a senior researcher at NEC Laboratories America, working on fundamental computer vision/deep learning research. He received his PhD at University of California, Merced, honored with the Graduate Dean's Dissertation Fellowship. Prior to that, he received his MS at University of Michigan, Ann Arbor and BS at National Chiao Tung University, Taiwan. He is the recipient of the Best Student Paper Honorable Mention award for ACCV'18. He has various research interests in computer vision and machine learning, with a focus on scene understanding, video analysis, fairness of AI, and representation learning.
Shibiao Wan
Dr. Shibiao Wan is currently an Assistant Professor in the Department of Genetics, Cell Biology and Anatomy, and the Co-Director for the Bioinformatics and Systems Biology (BISB) PhD Program at University of Nebraska Medical Center (UNMC). He is also an Assistant Professor (courtesy) in the Department of Biostatistics at UNMC.
With more than 15 years of experience in machine learning, bioinformatics, and computational biology, Dr. Wan has published >50 articles in top-tiered journals such as Genome Research, Nature Communications, Science Advances, Circulation Research, Briefings in Bioinformatics, and Bioinformatics. Dr. Wan is the Editor-in-Chief for Current Proteomics, and an Associate Editor/Academic Editor/Editorial Board Member for a series of prestigious journals such as Briefings in Functional Genomics, Heliyon, BMC Bioinformatics, International Journal of Microbiology, PeerJ Computer Science, BioMed Research International, and Computational and Mathematical Methods, and a guest associate editor for multiple high-impact journals.
He is a Scientific Program Committee (SPC) member for American Medical Informatics Association (AMIA) Annual Symposium and a Technical Program Committee (TPC) member for >20 machine learning related international conferences including IEEE ICTAI. Dr. Wan is also a reviewer for >70 prestigious journals including Nature Biotechnology, Nature Methods, Nature Communications, Nature Computational Science, Science Advances, Nucleic Acids Research, Advanced Science, Cancer Research, Genome Biology, and Genome Medicine. Dr. Wan has received a number of accolades including the Springer Nature Editor of Distinction Award in 2025 by Springer Nature, the New Investigator Award in 2024 by UNMC, the FIRST Award in 2023 by Nebraska EPSCoR, the Outstanding Young Alumni Award in 2022 by HK PolyU as well as the Global Peer Review Awards (top 1%) in “Cross-Field” and “Biology and Biochemistry” in 2019 by Clarivate. Dr. Wan is a member of AACR, AMIA, ISCB and ACM and an IEEE Senior Member.
Lexing Xie
Lexing Xie is Professor in the Research School of Computer Science at the Australian National University. She leads the ANU Computational Media lab (http://cm.cecs.anu.edu.au/). Her current research interests are in machine learning on graphs and time series, especially on understanding individual and aggregate behaviour in online social networks, at the intersection of media, language and behaviour. She was research staff member at IBM T J Watson Research Center 2005-2010. She is Associate editor for ACM TOIS, ACM TiiS and PeerJ CS.
Jiachen Yang
Prof. Dr. Jiachen Yang is an Associate Editor for “Journal of Ambient Intelligence and Humanized Computing”, “Alexandria Engineering Journal”, “IEEE Access”, “IET Image Processing”, “Sensors”, etc. Currently, he is a Professor at the School of Electronical and Information Engineering, Tianjin University. From 2014 to 2015, he was a visiting scholar with the Department of Computer Science, School of Science, Loughborough University, U.K. In 2019, He was a visiting scholar with Embry-Riddle Aeronautical University. His recent research interests include image processing, artificial intelligence, and information security. He has published more than 150 technical articles in highly ranked journals, such as IEEE Transactions on Neural Network and Learning System, IEEE Transactions on Cybernetics, IEEE Transactions on Industrial Informatics, IEEE Transactions on Image Processing, IEEE Transactions on Multimedia, etc. His Google Scholar H-index is 28.
Yu-Dong Zhang
From 2010 to 2012, Dr. Yudong (Eugene) Zhang worked at Columbia University as a postdoc. From 2012 to 2013, he worked as an assistant research scientist at Columbia University and New York State Psychiatric Institute. From 2013 to 2017, he is a full professor and doctoral advisor at School of Computer Science and Technology at Nanjing Normal University. He also serves as the academic leader of the“Jiangsu key laboratory of 3D printing equipment and manufacturing”. At present, he is a Professor in Knowledge Discovery and Machine Learning, in Department of Informatics, University of Leicester, United Kingdom. His research interests focus on computer-aided medical diagnosis and biomedical image processing.
Huiyu Zhou
Prof. Huiyu (Joe) Zhou received a Bachelor of Engineering degree in Radio Technology from Huazhong University of Science and Technology of China and a Master of Science degree in Biomedical Engineering from University of Dundee of United Kingdom, respectively. He was awarded a Doctor of Philosophy degree in Computer Vision from Heriot-Watt University, Edinburgh, United Kingdom.
Prof. Zhou currently heads the Applied Algorithms and AI (AAAI) Theme and leads the Biomedical Image Processing Lab at University of Leicester. He was the Director of MSc Programme (2018-19), and currently is the Coordinator of MSc Distance Learning and a Member of Research Committee at School of Informatics. Prior to this appointment, he worked as a Lecturer (2012-17) at the School of Electronics, Electrical Engineering and Computer Science, Queen's University Belfast.
Prof. Zhou has published widely in the field. He was the recipient of "CVIU 2012 Most Cited Paper Award", "MIUA 2020 Best Paper Award", "ICPRAM 2016 Best Paper Award in the Area of Applications" and was shortlisted for "ICPRAM 2017 Best Student Paper Award" and "MBEC 2006 Nightingale Prize".