Bio:  Prof. Rama Chellappa is a Distinguished University Professor, a Minta Martin Professor of Engineering and Chair of the ECE department at the University of Maryland. His current research interests span many areas in image processing, computer vision, machine learning and pattern recognition. Prof. Chellappa is a recipient of an NSF Presidential Young Investigator Award and four IBM Faculty Development Awards. He received the K.S. Fu Prize from the International Association of Pattern Recognition (IAPR). He is a recipient of the Society, Technical Achievement and Meritorious Service Awards from the IEEE Signal Processing Society. He also received the Technical Achievement and Meritorious Service Awards from the IEEE Computer Society. Recently, he received the inaugural Leadership Award from the IEEE Biometrics Council. At UMD, he received college and university level recognitions for research, teaching, innovation and mentoring of undergraduate students. In 2010, he was recognized as an Outstanding ECE by Purdue University. He received the Distinguished Alumni Award from the Indian Institute of Science in 2016. Prof. Chellappa served as the Editor-in-Chief of PAMI. He is a Golden Core Member of the IEEE Computer Society, served as a Distinguished Lecturer of the IEEE Signal Processing Society and as the President of IEEE Biometrics Council. He is a Fellow of IEEE, IAPR, OSA, AAAS, ACM and AAAI and holds six patents.

Bio:  Ming-Ming Cheng is a professor at Nankai University. He received his Ph.D. degree from Tsinghua University in 2012. Then he worked as a research fellow for 2 years, working with Prof. Philip Torr in Oxford. Dr. Cheng’s research primarily focuses on algorithmic issues in image understanding and processing, including salient object detection, semantic segmentation, low-level vision techniques, image manipulation, etc. He has published over 30 papers in leading journals and conferences, such as IEEE TPAMI, ACM TOG, ACM SIGGRAPH, IEEE CVPR, and IEEE ICCV. He has designed a series of popular methods and novel systems, indicated by 9000+ paper citations (2000+ citations to his first author paper on salient object detection).

Bio:  Gang Hua is a Principal Researcher/Research Manager in Microsoft Cloud & AI Division, managing the Machine Perception and Cognition Group in the Core Computer Vision Technology Center. He was an Associate Professor of Computer Science in Stevens Institute of Technology between 2011 and 2015, while holding an Academic Advisor position at IBM T. J. Watson Research Center. Before that, he was a Research Staff Member at IBM Research T. J. Watson Center from 2010 to 2011, a Senior Researcher at Nokia Research Center, Hollywood from 2009 to 2010, and a Scientist at Microsoft Live Labs Research from 2006 to 2009. He received the Ph.D. degree in Electrical and Computer Engineering from Northwestern University in 2006, and a M.S. in pattern recognition and intelligence system from Xi'an Jiaotong University (XJTU) in 2002. He was selected to the Special Class for the Gifted Young of XJTU in 1994 and received a B.S. in Electrical Engineering in 1999. He is the recipient of the 2015 IAPR Young Biometrics Investigator Award. He is an IAPR Fellow, an ACM Distinguished Scientist, and a Senior Member of the IEEE. He has published over 140 peer reviewed papers in top journals and conferences. To date, he holds 19 US patents and has 15 more patents pending.

Bio:  Jiaya Jia is an IEEE fellow. He is now the Distinguished Scientist and Director of X-Lab, Tencent, where X-Lab is the core research facility in Tencent focusing on cutting-edge computer vision and sound technologies. Jiaya Jia takes the professorship also at Department of Computer Science and Engineering, The Chinese University of Hong Kong (CUHK). Jiaya Jia published 100+ papers in top conferences and journals where most of them are with new practical techniques for computational imaging, and gave 30+ keynote talks in academia and industry. His papers received 13,000+ citations in total. His team also released 20+ open-source systems and freeware. PhDs and masters from this group made significant contributions, and become leaders, such as CEO of startups and professors, in a variety of fields. He is in the editorial boards of IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) and International Journal of Computer Vision (IJCV). He served as area chairs for ICCV and CVPR for several times. He was on (technical paper) program committees of major conferences in graphics and computational imaging, including ICCP, SIGGRAPH, and SIGGRAPH Asia, and co-chaired the Workshop on Interactive Computer Vision, in conjunction with ICCV 2007.

Bio:  Hong Jiang received the B.Sc. degree in Computer Engineering from Huazhong University of Science and Technology, Wuhan, China; the M.A.Sc. degree in Computer Engineering from the University of Toronto, Toronto, Canada; and the PhD degree in Computer Science from the Texas A&M University, College Station, Texas, USA. He is currently Chair and Wendell H. Nedderman Endowed Professor of Computer Science and Engineering Department at the University of Texas at Arlington. Prior to joining UTA, he served as a Program Director at National Science Foundation (2013.1-2015.8) and he was at University of Nebraska-Lincoln since 1991, where he was Willa Cather Professor of Computer Science and Engineering. His present research interests include computer architecture, computer storage systems and parallel I/O, high-performance computing, big data computing, cloud computing, performance evaluation. He has graduated 16 Ph.D. students and supervised about 20 post-doc fellows who now work in either major IT companies or academia. He has over 250 publications in major journals and international Conferences in these areas. Dr. Jiang is a Fellow of IEEE, and Member of ACM.

Bio:  Mark Johnson is a Professor of Language Science in the Dept of Computing at Macquarie University, and the Chief Scientific Officer of Voicebox Technologies Australia, an R&D lab on the Macquarie University campus. Mark has worked on a wide range of topics in computational linguistics, but his main area of research is natural language understanding, especially syntactic parsing and semantic analysis, and their applications to text and speech processing. He is a past president of Association for Computational Linguistics (ACL) and currently is an Editor in Chief for the Transactions of the ACL (TACL).

Bio:  Hongdong Li is currently a Reader/Associate Professor (Tenured Professor equivalent) of ANU (Australian National University). He is a Chief Investigator and AA2 Sub-Program Leader for the Australia ARC Centre of Excellence for Robotic Vision. He taught undergradaute course of "computer vision" and "robotics" at ANU sicne 2005. His research interests include 3D Computer Vision, Camera Calibration, Robot navigation, autonomous driving, as well as applications of optimization in vision. During 2009-2010 he was a senior researcher with NICTA (Canberra Labs) working on the “Australia Bionic Eyes” project. He was a visiting professor with Carnegie Mellon University in 2017. He served as the Area Chair for CVPR, ICCV, ECCV, BMVC and 3DV in the past; Associate Editor for IEEE Transactions on PAMI (T-PAMI); Program Co-Chair for ACCV (Asian Conference on Computer Vision) 2018. Jointly with co-workers and PhD students he won a number of prestigious awards in computer vision research including the IEEE CVPR Best Paper Award and ICCV Marr Prize-Honourable Mention.

Bio:  Patrick Naylor is a member of academic staff in the Department of Electrical and Electronic Engineering at Imperial College London. He received the BEng degree in Electronic and Electrical Engineering from the University of Sheffield, UK, and the Ph.D. degree from Imperial College London, UK. His research interests are in the areas of speech, audio and acoustic signal processing. He has worked in particular on adaptive signal processing for dereverberation, blind multichannel system identification and equalization, acoustic echo control, speech quality estimation and classification, single and multi-channel speech enhancement and speech production modelling with a particular focus on the analysis of the voice source signal. In addition to his academic research, he enjoys several fruitful links with industry in the UK, USA and in Europe. He is the past-Chair of the IEEE Signal Processing Society Technical Committee on Audio and Acoustic Signal Processing, director and president-elect of the European Association for Signal Processing (EURASIP) and Senior Area Editor of IEEE Transactions on Audio Speech and Language Processing.

Bio:  Dinggang Shen is Jeffrey Houpt Distinguished Investigator, and a Professor of Radiology, Biomedical Research Imaging Center (BRIC), Computer Science, and Biomedical Engineering in the University of North Carolina at Chapel Hill (UNC-CH). He is currently directing the Center for Image Analysis and Informatics, the Image Display, Enhancement, and Analysis (IDEA) Lab in the Department of Radiology, and also the medical image analysis core in the BRIC. He was a tenure-track assistant professor in the University of Pennsylvanian (UPenn), and a faculty member in the Johns Hopkins University. Dr. Shen's research interests include medical image analysis, computer vision, and pattern recognition. He has published more than 800 papers in the international journals and conference proceedings. He serves as an editorial board member for eight international journals. He has also served in the Board of Directors, The Medical Image Computing and Computer Assisted Intervention (MICCAI) Society, in 2012-2015. He will be General Chair for MICCAI 2019. He is Fellow of IEEE, Fellow of The American Institute for Medical and Biological Engineering (AIMBE), and Fellow of The International Association for Pattern Recognition (IAPR).

Bio:  Dr. Jian Sun is Chief Scientist of Megvii Technology (Face++). He received a B.S., a M.S. and a Ph.D., in Electronical Engineering at Xian Jiaotong University in 1997, 2000 and 2003. Following his dissertation, he joined Visual Computing Group in Microsoft Research Asia. He led the computer vision research as Lead Researcher, Senior Researcher, Principal Researcher in 2008, 2010, and 2013. He relocated to Microsoft Research US in 2015, and was promoted as Partner Research Manager. He has transferred many computer vision technologies in Microsoft products including Windows, Office, Bing, Xbox, and Azuer. In the summer of 2016, he joined Megvii Technology and established Megvii Research, a R&D department for fundamental and applied research. His primary research interests are deep learning based image understanding, face recognition, and computational photography. He has published 100+ scientific papers on tier-one conferences or journals (CVPR, ICCV, ECCV, SIGGRAPH, and PAMI). His Google Scholar citation number is 48,000+, H-index is 72, up to 06/2018. He is the recipient of Best Paper Awards of CVPR 2010 and CVPR 2016. In 2015, his team won five 1st places on ImageNet Challenge and COCO Visual Recognition Challenge, by invented “Residual Networks” and “Faster R-CNN” algorithms, which have been prevalently used in both academy and industry, including DeepMind’s AlphaGo Zero in 2017. His team at Megvii Research won three 1st places on COCO & Places Visual Recognition Challenge in 2017. Jian was named one of the world's top 35 young innovators (TR35) by MIT Technology Review in 2010. He severed as area chair of ICCV 2011, Siggraph 2011, and CVPR 2012/2015/2016/2017/2019. He is also the recipient of National Natural Science Award of China (second class) in 2016. He holds 40 International or US patents.

Bio:  Ivan Sutherland received his Ph.D. degree from MIT in 1963, with a well- known thesis called “Sketchpad” for which he has been called the “father of computer graphics.” His career has included government service, private industry, venture capital and professorships at Harvard, the University of Utah, and Caltech. With his research partner and wife, Marly Roncken, he joined Portland State University in 2009 to found the Asynchronous Research Center (ARC). The ARC will soon graduate its 4th PhD student. Ivan holds more than 70 US patents, and is author of numerous publications and lectures. Ivan’s 1999 book, Logical Effort, describes mathematics for designing fast transistor circuits. Sutherland holds the 1988 ACM Turing Award, the 2012 Kyoto Prize, and the 1998 IEEE John von Neumann Medal. He is a Fellow of the ACM and a Member of both the US National Academy of Engineering and the US National Academy of Sciences. Now 80 years of age, Ivan devotes full time to research, lectures, and writing.

Bio:  Rene Vidal is a Professor of Biomedical Engineering and the Innaugural Director of the Mathematical Institute for Data Science at The Johns Hopkins University. His research focuses on the development of theory and algorithms for the analysis of complex high-dimensional datasets such as images, videos, time-series and biomedical data. His current major research focus is understanding the mathematical foundations of deep learning and its applications in computer vision and biomedical data science. He has pioneered the development of methods for dimensionality reduction and clustering, such as Generalized Principal Component Analysis and Sparse Subspace Clustering, and their applications to face recognition, object recognition, motion segmentation and action recognition. He has also created new technologies for a variety of biomedical applications, including detection, classification and tracking of blood cells in holographic images, classification of embryonic cardio-myocytes in optical images, and assessment of surgical skill in surgical videos. Dr. Vidal is recipient of numerous awards for his work, including the Jean D'Alembert Faculty Fellowship (2017), IAPR Fellowship (2016), IEEE Fellowship (2014), J.K. Aggarwal Prize (2012), ONR Young Investigator Award (2009), Sloan Fellowship (2009), NSF CAREER Award (2004), as well as best paper awards for his work in machine learning, computer vision, medical imaging, and controls.

Bio:  Prof. Liang Wang received both the BEng and MEng degrees from Anhui University, in 1997 and 2000, respectively, and the PhD degree from the Institute of Automation, Chinese Academy of Sciences (CASIA), in 2004. From 2004 to 2010, he was a research assistant at Imperial College London, United Kingdom, and Monash University, Australia, a research fellow with the University of Melbourne, Australia, and a lecturer with the University of Bath, United Kingdom, respectively. Currently, he is a full professor of the Hundred Talents Program at the National Lab of Pattern Recognition, CASIA. His major research interests include machine learning, pattern recognition, and computer vision. He has widely published in highly ranked international journals such as the IEEE TPAMI and the IEEE TIP, and leading international conferences such as CVPR, ICCV, and ICDM. He is a senior member of the IEEE and a fellow of the IAPR.

Bio:  Wei Wang is the Leonard Kleinrock Chair Professor of Computer Science at University of California, Los Angeles and the director of the Scalable Analytics Institute (ScAi). She is a co-director of the NIH BD2K Centers-Coordination Center. She received her PhD degree in Computer Science from the University of California, Los Angeles in 1999. She was a professor in Computer Science at the University of North Carolina at Chapel Hill from 2002 to 2012, and was a research staff member at the IBM T. J. Watson Research Center between 1999 and 2002. Dr. Wang's research interests include big data analytics, data mining, bioinformatics and computational biology, and databases. She has filed seven patents, and has published one monograph and more than one hundred seventy research papers in international journals and major peer-reviewed conference proceedings and multiple best paper awards. Dr. Wang received the IBM Invention Achievement Awards in 2000 and 2001. She was the recipient of an NSF Faculty Early Career Development (CAREER) Award in 2005. She was named a Microsoft Research New Faculty Fellow in 2005. She was honored with the 2007 Phillip and Ruth Hettleman Prize for Artistic and Scholarly Achievement at UNC. She was recognized with an IEEE ICDM Outstanding Service Award in 2012, an Okawa Foundation Research Award in 2013, and an ACM SIGKDD Service Award in 2016. Dr. Wang has been an associate editor of the IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Big Data, IEEE/ACM Transactions on Computational Biology and Bioinformatics, ACM Transactions on Knowledge Discovery in Data, Journal of Computational Biology, Journal of Knowledge and Information Systems, Data Mining and Knowledge Discovery, and International Journal of Knowledge Discovery in Bioinformatics. She serves on the organization and program committees of international conferences including ACM SIGMOD, ACM SIGKDD, ACM BCB, VLDB, ICDE, EDBT, ACM CIKM, IEEE ICDM, SIAM DM, SSDBM, RECOMB, BIBM. She was elected to the Board of Directors of the ACM Special Interest Group on Bioinformatics, Computational Biology, and Biomedical Informatics (SIGBio) in 2015.

Bio:  Yongtian Wang received his B.Sc. degree in precision instrumentation from Tianjin University, China, in 1982, and his Ph.D. degree in optics from the University of Reading, England, in 1986. He is currently a professor of optics and applied computer science in Beijing Institute of Technology (BIT), the founding director of Beijing Engineering Research Center of Mixed Reality and Advanced Display. His research interests include optical design and CAD, 3D display, image processing, virtual reality (VR) and augmented reality (AR) technologies and applications. Dr. Wang is a Fellow of SPIE, OSA and IET, and a member of the board of directors of the Chinese Society for Optical Engineering (CSOE), the China Computer Federation (CCF), and the China Society of Image and Graphics (CSIG). He is a member of the expert group on information technology for the Chinese Ministry of Science and Technology, and the leader of the working group on VR and AR standards of the National Information Technology Standardization Committee.

Bio:  Dr. Xiao Jing, professorate senior engineer, Chief Scientist at Ping An Group, Dean of Ping An Technology Research Institute. He obtained his Ph.D degree in computer science from Carnegie Mellon University(CMU), USA. His current research interests include Big Data, Artificial Intelligence, and Robotics.

Bio:  Dong Xu is Chair in Computer Engineering at the School of Electrical and Information Engineering, The University of Sydney, Australia. He received the B.Eng. and PhD degrees from University of Science and Technology of China, in 2001 and 2005, respectively. While pursuing the PhD degree, he worked at Microsoft Research Asia and The Chinese University of Hong Kong for more than two years. He also worked as a postdoctoral research scientist at Columbia University from 2006 to 2007 and a faculty member at Nanyang Technological University from 2007 to 2015. His current research interests include computer vision, multimedia and machine learning. He has published more than 100 papers in IEEE Transactions and top tier conferences. His co-authored work (with his former PhD student Lixin Duan) received the Best Student Paper Award in IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) in 2010. His co-authored work (with his former PhD student Lin Chen) won the IEEE Transactions on Multimedia Prize Paper Award in 2014. He was awarded the IEEE Computational Intelligence Society Outstanding Early Career Award in 2017. He is/was on the editorial boards of T-PAMI, T-TIP, T-NNLS, T-MM and T-CSVT. He also served as a guest editor of seven special issues in T-NNLS, T-CYB, T-CSVT, IJCV, ACM TOMM, CVIU and IEEE Multimedia. Moreover, he served as a steering committee member of ICME (2016-2017), a program co-chair of ICME 2014, as well as an area chair of CVPR 2012, ECCV 2016 and ICCV 2017. He is a Fellow of the IEEE and the IAPR.

Bio:  Xiangyang XUE received the B.S., M.S., and Ph.D. degrees from the Xidian University, Xi’an, China, in 1989, 1992, and 1995, respectively, all in information and communication engineering. He is currently a Professor with the School of Computer Science, Fudan University. His research interests include computer vision, video analysis and deep learning, and he has co-authored about 200 technical papers, as well as more than 20 granted patents. He serves as an Associate Editor for IEEE Transaction on Cognitive and Developmental Systems, Journal of Computer Research and Development and Journal of Frontiers of Computer Science & Technology.

Bio:  Dr. Yan Shuicheng, Vice President of 360, Director of 360 AI Institute, China 1000Plan Expert, IEEE Fellow, IAPR Fellow and ACM Outstanding Scientist. Dr. Yan's research areas include machine learning, computer vision and multimedia. He has authored/co-authored more than 500 technical papers over a wide range of research topics, with Google Scholar citation over 30,000 times and H-index 75. He is ISI Highly-cited Researcher of 2014, 2015 and 2016. The team he is leading won the championships in both Pascal VOC and ImageNet. His team received 10 times winner or honorable-mention prizes in PASCAL VOC and ILSVRC competitions, along with more than 10 times best (student) paper prizes. In ACM MM, the core conference of multimedia area, he won the grand slam with the Best Paper Award, the Best Student Paper Award, and the Best Demo Award.

Bio:  Ming-Hsuan Yang is a professor of Electrical Engineering and Computer Science at University of California, Merced, and a researcher at Google Cloud. He received the PhD degree in Computer Science from the University of Illinois at Urbana-Champaign in 2000. He serves as an area chair for several conferences including IEEE Conference on Computer Vision and Pattern Recognition, IEEE International Conference on Computer Vision, European Conference on Computer Vision, Asian Conference on Computer, and AAAI National Conference on Artificial Intelligence. He serves as a program co-chair for IEEE International Conference on Computer Vision in 2019 as well as Asian Conference on Computer Vision in 2014, and general co-chair for Asian Conference on Computer Vision in 2016. He serves as an associate editor of the IEEE Transactions on Pattern Analysis and Machine Intelligence (2007 to 2011), International Journal of Computer Vision, Computer Vision and Image Understanding, Image and Vision Computing, and Journal of Artificial Intelligence Research. Yang received the Google faculty award in 2009, and the Distinguished Early Career Research award from the UC Merced senate in 2011, the Faculty Early Career Development (CAREER) award from the National Science Foundation in 2012, and the Distinguished Research Award from UC Merced Senate in 2015.

Bio:  Xiaokang YANG received the B. S. degree from Xiamen University, Xiamen, China, in 1994, the M. S. degree from Chinese Academy of Sciences, Shanghai, China, in 1997, and the Ph.D. degree from Shanghai Jiao Tong University, Shanghai, China, in 2000. He is currently Professor in School of Electronic Information and Electrical Engineering, and the Deputy Executive Dean of Artificial Intelligence Institute, Shanghai Jiao Tong University, China. From September 2000 to March 2002, he worked as a Research Fellow in Centre for Signal Processing, Nanyang Technological University, Singapore. From April 2002 to October 2004, he was a Research Scientist in the Institute for Infocomm Research (I2R), Singapore. From August 2007 to July 2008, he visited the Institute for Computer Science, University of Freiburg, Germany, as an Alexander von Humboldt Research Fellow. He has published over 200 refereed papers, and has filed 60 patents. His current research interests include pattern recognition and machine learning, visual signal processing and communication. He is Associate Editor of IEEE Transactions on Multimedia and Senior Associate Editor of IEEE Signal Processing Letters. He was Series Editor of Springer CCIS, and a member of Editorial Board of Digital Signal Processing. He is a member of APSIPA, a senior member of IEEE, a member of VSPC Technical Committee of IEEE Circuits and Systems Society, a member of MMSP Technical Committee of IEEE Signal Processing Society, Chair of Multimedia Big Data Interest Group of MMTC Technical Committee of IEEE Communication Society.

Bio:  Alan Yuille is a Bloomberg Distinguished Professor of Cognitive Science and Computer Science, Johns Hopkins University. He is a mathematician and computer scientist studying the biology of vision. His research has been focused on the development of computational models for vision, development of mathematical models to explain cognition, artificial intelligence and neural networks in which he is now a world reference. He is developing mathematical models of vision and cognition that allow us to build computers that, when given images or videos, can reconstruct the 3D structure of a scene. These models also serve as computational models of biological vision which can be tested by behavioral, invasive, and non-invasive techniques. He has published more than 300 publications including three books (one co-edited). Dr. Yuille is a recipient of many awards including the Bloomberg Distinguished Professorship in 2016; Helmholtz Test of Time Award in 2013; Marr Prize, ICCV 2013. His work reaches across the computer vision, vision science, and neuroscience communities at Johns Hopkins, particularly in the schools of Arts and Sciences and Engineering.

Bio:  Co-director of Columbia’s Computer Graphics Group, Changxi Zheng is currently an Associate Professor in the Department of Computer Science at Columbia University, working on audiovisual processing, computer graphics, acoustic and optical engineering, and scientific computing. He received his Ph.D. from Cornell University with the Best Dissertation Award and his B.S. from Shanghai Jiaotong University. He currently serves as an associated editor of ACM Transactions on Graphics. He was a Conference Chair for SCA in 2017, has won several Best Paper awards, a NSF CAREER Award, and was named one of Forbes’ “30 under 30” in science and healthcare in 2013.

Bio:  Dr. Rui Zheng received her bachelor and master degree from Department of Engineering Physics in Tsinghua University, Beijing, China, in 2000 and 2002 respectively. She received her PhD degree in Physics and Biomedical engineering from University of Alberta, Alberta, Canada in 2011. Between May, 2012 and April 2013, she was a postdoctoral fellow in Laboratory of Mechanics and Acoustics–CNRS, Marseille, France. In 2013-2017, she worked as research associate in Department of surgery, University of Alberta and Glenrose Rehabilitation Hospital, Alberta Health Services, Alberta, Canada. In March of 2018, she joined in the School of Information Science and Technology in ShanghaiTech University as a tenure track assistant professor, PI.

Bio:  Dr. Jie Zhou received the BS and MS degrees both from the Department of Mathematics, Nankai University, Tianjin, China, in 1990 and 1992, respectively, and the PhD degree from the Institute of Pattern Recognition and Artificial Intelligence, Huazhong University of Science and Technology (HUST), Wuhan, China, in 1995. From then to 1997, he served as a postdoctoral fellow in the Department of Automation, Tsinghua University, Beijing, China. Since 2003, he has been a full professor in the Department of Automation, Tsinghua University. From 2015 to now, he is the Chair of Department of Automation, Tsinghua University. His research interests include pattern recognition, computer vision, and image processing. In recent years, he has authored more than 300 papers in peer-reviewed journals and conferences. Among them, more than 50 papers have been published in top journals and conferences (IEEE T-PAMI, T-IP, CVPR and ICCV. He received the National Outstanding Youth Foundation of China Award in 2012. He is a fellow of IAPR and Associate Editor of IEEE T-PAMI.