Advisory Board and Editors Computer Vision
Krishna Dev Oruganty
I can best describe myself as a simulation biologist. I am interested in simulating life processes at multiple scales. From the atomic scale to understand protein function to cellular or systems scale to understand physiological processes. My main tool is the computer which I use to analyze, understand and predict biology. Secondary tools are in vitro biochemistry and biophysics experiments that I use to validate my predictions.
Marco Piangerelli
Dr. Marco Piangerelli had his M.Sc. in Bioengineering from the University of Bologna and got his Ph.D. in Computer Science from the University of Camerino, where he is currently a Research Associate. His research interests are mainly on Unsupervised techniques for Machine Learning and Data Science in Manufacturing and Bio Science, Self-Adaptive Systems, and Topological Data Analysis. He is the author of many publications and was a PC member for many conferences and Workshops (AAAI-MAKE 2022-23-24 Spring Symposium, SACAIR 2023, DESRIST 2023, ATDA2019). He co-organized the 9th International Workshop on Engineering Energy Efficient InternetWorked Smart seNsors (E3WSN ) hosted by the 37th International Conference on Advanced Information Networking and Applications (AINA) at the Federal University of Juiz de Fora, Brazil. He has experience in Technological transfer projects and actively collaborates with international companies (INGKA, Schnell S.p.A., Sigma S.p.A., and Nuova Simonelli S.P.A.) and Italian ones (Syeew S.r.l). In 2024, he will be a Visiting Researcher at Addis Ababa University (Ethiopia) to work on topics related to his research fields.
Tomaso A Poggio
Tomaso A. Poggio, is the Eugene McDermott Professor at MIT and one of the most cited computational scientists. The citation for the 2009 Okawa prize mentions his “…pioneering research ranging from the biophysical and behavioral studies of the visual system to the computational analysis of vision and learning in humans and machines.” His recent work is on a theory of hierarchical architectures for unsupervised learning of invariant representations.
Kai Qin
Kai Qin received the Ph.D. degree from the Nanyang Technological University (Singapore) in 2007. After that, he worked at the University of Waterloo (Canada) and then INRIA (France) from 2007 to 2012. He joined the RMIT University (Australia) in 2012, first as a Vice-Chancellor’s research fellow and then promoted to a lecturer. His major research interests include evolutionary computation, machine learning, computer vision, GPU computing and service computing. He is an IEEE senior member.
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.
Syed Sajid Ullah
Dr. Syed Sajid Ullah is a Research Fellow in the Department of Information and Communication Technology, University of Agder.
He currently works as a researcher in the NIST project of Quantum Cryptography and has published more then 90 papers in quality journals.
Ananya Sen Gupta
Ananya Sen Gupta received her PhD from the University of Illinois in 2006, spent a significant part of her research career (2008-2012) at the Woods Hole Oceanographic Institution, and is currently an Assistant Professor in Electrical and Computer Engineering.
She leads and directs multiple research grants focused computational innovations for shallow water acoustic communications, sonar target classification, and more generally, dynamic environmental sensing. Her algorithms have also been applied towards petroleum forensics, air pollution studies, tracking whistler-mode chorus emissions in the Van Allen radiation Belts, escaping local ion populations against solar wind in the Martian ionosphere, as well for separation of reaction wheel signature from magnetometer measurements in the e-POP spacecraft.
Her research for her Iowa EPSCoR project was featured in the ISGC 2015-2016 STIMULI EPsCOR report distributed to Congress. She has also received a collegiate-level teaching excellence award in 2015, three mentor awards from the Iowa Space Grant Consortium in 2016, 2017 and 2019, and a career mentor award from University of Iowa. Dr. Sen Gupta has served as a guest editor for the IEEE Journal of Oceanic Engineering and currently serves as an Associate Editor for IEEE Access, co-chair of the Technical Committee for Data Analytics, Integration and Modeling for IEEE Ocean Engineering Society, and a committee member for the Oceans chapter of IEEE Planet Positive 2030 effort.
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.
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.