Advisory Board and Editors Computer Vision
Zhaojie Ju
Zhaojie Ju (M'08-SM'16) received a BSc degree in automatic control and a MSc degree in intelligent robotics from the Huazhong University of Science and Technology, China. He received a Ph.D. degree in intelligent robotics from the University of Portsmouth, U.K. He held research appointments at University College London, London, U.K., before he started his independent academic position at the University of Portsmouth, in 2012. He has authored or co-authored over 200 publications in journals, book chapters, and conference proceedings, and received five Best Paper Awards, one book award, and one Best AE Award in ICRA2018. His research interests include machine intelligence, pattern recognition and their applications on human motion analysis, multi-fingered robotic hand control, human–robot interaction and collaboration, and robot skill learning.
Goo Jun
I am currently an assistant professor at the University of Texas Health Science Center at Houston. I work on statistical genetics, computational biology, bioinformatics, and sequence data analysis. With backgrounds in machine learning and data mining, my research is focused on development of computational and statistical methods for analysis of massive data to understand genetics and biology of complex traits. I have been working on the analysis of large-scale next-generation sequencing data, for which I developed statistical models and software pipelines for detecting sample contamination, variant discovery, machine-learning based variant filtering, and genotyping of structural variations. I also work on genetics of diabetes, obesity, and related traits and study of metabolomic and microbiome compositions related to genetics of common and complex traits.
Yann LeCun
Director of Facebook AI Research (2013-) and Silver Professor at New York University (2003-), affiliated with: Courant Institute, Center for Data Science, Center for Neural Science, and ECE Dept. Founding director of the NYU Center for Data Science (2012-2014); Fellow,NEC Research Institute (2002-2003); Head, Image Processing Research AT&T Labs (1996-2002); Research Scientist Bell Laboratories (1988-1996).
Pengcheng Liu
Pengcheng Liu is a member of IEEE, IEEE Robotics and Automation Society (RAS), IEEE Control Systems Society (CSS) and International Federation of Automatic Control (IFAC). He is also a member of the IEEE Technical Committee on Bio Robotics, Soft Robotics, Robot Learning, and Safety, Security and Rescue Robotics. Dr Liu is an Associate Editor of IEEE Access, PeerJ Computer Science, and he received the Global Peer Review Awards from Web of Science in 2019, and the Outstanding Contribution Awards from Elsevier in 2017. He has published over 70 papers on flagship journals and conferences. He was nominated as a regular Funding/Grants reviewer for EPSRC, NIHR and NSFC and he has been leading and involving in several research projects and grants, including EPSRC, Newton Fund, Innovate UK, Horizon 2020, Erasmus Mundus, FP7-PEOPLE, NSFC, etc. He serves as reviewers for over 30 flagship journals and conferences in robotics, AI and control. His research interests include robotics, machine learning, automatic control and optimization.
Laurent Najman
In 1998, he joined OCÉ Print Logic Technologies, as senior scientist. He worked there on various problem of image analysis dedicated to scanning and printing. In 2002, he joined the Informatics Department of ESIEE, Paris, where he is professor and a member of the Laboratoire d’Informatique Gaspard Monge, Université Paris-Est Marne-la-Vallée. His current research interest is discrete mathematical morphology and discrete optimization.
Binh P. Nguyen
Senior Lecturer in Data Science at the School of Mathematics and Statistics in Victoria University of Wellington (New Zealand). Former Scientist at the Institute of High Performance Computing, A*STAR (Singapore). Former Research Fellow at Duke-NUS Medical School and National University of Singapore (Singapore).
Feiping Nie
Feiping Nie's research interests are machine learning and its application. He has published more than 100 papers in the following journals and conferences: TPAMI, IJCV, TIP, TNNLS/TNN, TKDE, TKDD, TVCG, TCSVT, TMM, TSMCB/TC, Machine Learning, Pattern Recognition, Medical Image Analysis, Bioinformatics, ICML, NIPS, KDD, IJCAI, AAAI, ICCV, CVPR, SIGIR, ACM MM, ICDE, ECML/PKDD, ICDM, MICCAI, IPMI, RECOMB. According to Google scholar, his papers have been cited more than 2000 times.
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.