Advisory Board and Editors Computer Vision
Hossein Rahmani
Hossein Rahmani received his B.Sc. degree in computer software engineering from the Isfahan University of Technology, Isfahan, Iran, in 2004, an M.Sc. degree in software engineering from Shahid Beheshti University, Tehran, Iran, in 2010, and a Ph.D. degree from The University of Western Australia, in 2016.
He has published several papers in top conferences and journals such as CVPR, ICCV, ECCV, and the IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE. He is currently an Associate Professor (Lecturer) with the School of Computing and Communications, Lancaster University. Before that, he was a Research Fellow at the School of Computer Science and Software Engineering, The University of Western Australia. His research interests include computer vision, action recognition, 3D shape analysis, and machine learning.
Consolato Sergi
Dr. Consolato M. Sergi is Chief of Anatomical Pathology of the Children's Hospital of Eastern Ontario, University of Ottawa, Ontario, Canada and Emeritus Professor of Pathology and Pediatrics of the University of Alberta, Canada. Dr. Sergi was born in Rome (Italy), obtained his MD degree with honors at the University of Genoa, Italy, his Human Pathology degree at the University of Heidelberg, Germany, the title of the hon. Clinical Reader of the University of Bristol, UK, his Ph.D./Habilitation at the University of Innsbruck, Austria, his MSc Public Health in Austria, and his FRCPC degree at the Royal College in Ottawa. Dr. Sergi’s specialty areas of interest are congenital heart disease and metabolic diseases, obstructive cholangiopathies, carcinogenesis (bone/soft tissue/liver), gut microbiome, and mitochondrial DNA related cardiomyopathies.
Syed Hassan Shah
Syed Hassan Shah is a Wi-Fi connectivity subject matter expert with the Qualcomm Inc. product management team, where he is involved in Consumer and Compute Wireless products with a focus on Mi-Fi, CPE, and UWB technologies. In addition to that, Dr. Shah is also an adjunct faculty member at California State University, Fullerton Campus, where he teaches computer science courses to graduate classes. Over the past decade, Dr. Shah held multiple industrial & academic roles such as a Product Specialist for Distributed Antenna Systems (DAS), CBRS, Private LTE, Digital Electricity, and open RAN product lines. Dr. Shah was an Assistant Professor in the Department of Computer Science at Georgia Southern University, USA followed by a Post-Doctoral Fellowship at the University of Central Florida, Orlando, USA. Before moving to the United States, he completed his BS with honors in CS from Kohat University of Science & Technology (KUST), Pakistan, and his Ph.D. Degree (combined with Masters) from the School of Computer Science and Engineering (SCSE), Kyungpook National University (KNU), Republic of Korea (South Korea). During the summer of 2015, he was invited as a distinguished visiting researcher at Georgia Tech, Atlanta, USA to investigate MAC layer findings in IEEE 1609.4 protocol stacks. Overall, Dr. Shah has authored/co-authored over 250 peer-reviewed international publications including Journal articles, Conference Proceedings, Book Chapters, and 05 books. In 2016, his work on robust content retrieval in future vehicular networks won the Qualcomm Innovation Award at KNU, South Korea. Dr. Shah's research interests include Wireless and Ad hoc Networks, Cyber-Physical Systems, Smart Cities, Connected Vehicles, and Future Internet architectures.
Furthermore, Dr. Shah is a Senior IEEE and ACM member, served as a TPC Member or Reviewer in over 100 International Conferences and Workshops including IEEE Globecom, IEEE ICC, IEEE CCNC, IEEE ICNC, IEEE VTC, IEEE INFOCOM, ACM CoNEXT, ACM MobiHoc, ACM SAC, and many more. Furthermore, he has been reviewing papers for over 50 different International Journals including IEEE Magazines on Wireless Communications, Networks, Communications, IEEE Communications Letters, IEEE Sensors Letters, IEEE Transactions on Industrial Informatics, and Vehicular Technologies, Intelligent Transportation Systems, Big Data, and Mobile Computing. Moreover, Dr. Shah has been an editorial member of more than 60 Special Issues with top-ranked journals in Communication Society and served as an editorial board member of KSII Transactions on Internet & Information Systems, Wiley's Internet Technology Letters, Transactions on Emerging Telecommunications Technologies, IEEE Newsletters on Internet Initiative, Future Directions, and Software Defined Networks. Dr. Shah has been an appointee of the Board of Governors of the IEEE Vehicular Technology Society as liaison to IEEE Young Professionals society for the year 2018-2019. Since 2018, he is also an ACM Distinguished Speaker.
Osama Sohaib
Dr Osama Sohaib is a Lecturer at the Faculty of Engineering and Information Technology, University of Technology Sydney. His research interest areas include information systems modelling, e-Services, Human-Computer Interaction (HCI) and Applied Machine Learning.
Abdel Hamid Soliman
Dr Soliman has over 30 years of experience in the academic and industrial fields. He has a multidisciplinary academic/research experience in digital signal processing, telecommunications, data acquisition systems, WSN, IoT, Fibre Optics communication and image/video processing. He is working to harness and integrate different technologies towards implementing smart systems to contribute to smart cities and real-life applications. His research activities are not limited to the national level within the UK but are internationally extended to many partner Universities in various countries. His research has produced over 50 refereed papers.
In addition to his research activities, he is involved in several enterprise projects and consultancy activities for national and international companies. Since 2007 he has been leading and involved in several externally funded projects on national, European and international levels totalling more than £20M.
Dr Soliman’s work has been recognised through several awards such as: Lord Stafford award “Impact through Innovation”, for Designing and developing a smart monitoring and controlling system for diabetic people. The AWM ICT Excellence awards for “Best Knowledge Transfer project” category, for Designing and developing an electronic bladder diary, and UHNS “Clinical Innovation” award, for Designing and developing an online multimedia-based training system for surgeons.
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.
Ivor W Tsang
Ivor W Tsang is a Professor of Artificial Intelligence, at University of Technology Sydney (UTS). He is also the Research Director of the UTS Flagship Research Centre for Artificial Intelligence (CAI) with more than 30 faculty members and 180 PhD students. His research focuses on transfer learning, feature selection, crowd intelligence, big data analytics for data with extremely high dimensions in features, samples and labels. He has more than 180 research papers published in top-tier journal and conference papers. According to Google Scholar, he has more than 13,000 citations and his H-index is 54. In 2009, Prof Tsang was conferred the 2008 Natural Science Award (Class II) by Ministry of Education, China, which recognized his contributions to kernel methods. In 2013, Prof Tsang received his prestigious Australian Research Council Future Fellowship for his research regarding Machine Learning on Big Data. In addition, he had received the prestigious IEEE Transactions on Neural Networks Outstanding 2004 Paper Award in 2007, the 2014 IEEE Transactions on Multimedia Prize Paper Award, and a number of best paper awards and honors from reputable international conferences, including the Best Student Paper Award at CVPR 2010. He serves as an Associate Editor for the IEEE Transactions on Big Data, the IEEE Transactions on Emerging Topics in Computational Intelligence and Neurocomputing. He serves as an Area Chair/Senior PC for NeurIPS, AISTATS, AAAI and IJCAI.
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 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 including Frontiers in Immunology, Frontiers in Cell and Developmental Biology, Frontiers in Pharmacology, Biology, Frontiers in Genetics, and Genes.
Dr Wan is a 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, ISCB and ACM and an IEEE Senior Member.
Meng Wang
Dr. Meng Wang is a professor at the Hefei University of Technology, China. His current research interests include multimedia content analysis, search, mining, recommendation, and large-scale computing. He received the best paper awards successively from the 17th and 18th ACM International Conference on Multimedia. He is the recipient of ACM SIGMM Rising Star Award 2014.
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.