National University of Singapore
Dr. Yan Shuicheng is currently a Dean's Chair Associate Professor in the Department of Electrical and Computer Engineering at National University of Singapore, and the founding lead of the Learning and Vision Research Group. Dr. Yan's research areas include computer vision, multimedia and machine learning. He is an associate editor of Journal of Computer Vision and Image Understanding, IEEE Transactions on Knowledge and Data Engineering (TKDE), IEEE Transactions on Circuits and Systems for Video Technology (IEEE TCSVT) and ACM Transactions on Intelligent Systems and Technology (ACM TIST), and has been serving as the guest editor of the special issues for TMM and CVIU.
eleyans "at" nus.edu.sg
University of Southern California
Dr. Wael AbdAlmageed is a senior computer scientist with the University of Southern California’s Viterbi School of Engineering Information Sciences Institute (USC/ISI). His research focus is applying large-scale machine learning techniques to computer vision and image processing problems. His research interests also include implementing machine learning and computer vision algorithms on modern high performance computing platforms. Prior to joining ISI, Dr. AbdAlmageed was a research scientist with the University of Maryland at College Park, where he lead several research efforts for various NSF, DARPA and IARPA programs. He obtained his Ph.D. with Distinction from the University of New Mexico in 2003 where he was also awarded the Outstanding Graduate Student award. He has two patents and over 50 publications in top computer vision and high performance computing conferences and journals.
wamageed "at" isi.edu
Lawrence Livermore National Laboratory
Dr. Brian Van Essen has been a Computer Scientist at Lawrence Livermore National Laboratory (LLNL) since 2010. His research interests include operating systems and architectures for data-intensive HPC, deep learning, and embedded systems. Brian earned his Ph.D. in Computer Science and Engineering (CSE) from the University of Washington in Seattle in 2010. He also holds a M.S. in CSE from UW, plus a M.S. and a B.S. in Electrical and Computer Engineering (ECE) from Carnegie Mellon University. Prior to his graduate studies, Brian co-founded two startups in the area of reconfigurable computing.
vanessen1 "at" llnl.gov
Lawrence Livermore National Laboratory
Dr. Maya Gokhale has been a Computer Scientist at the Lawrence Livermore National Laboratory (LLNL) since 2007. Her career spans research conducted in academia, industry, and National Labs, most recently Los Alamos National Laboratory. Maya received a Ph.D. in Computer Science from University of Pennsylvania in 1983. Her current research interests include data intensive architectures and reconfigurable computing. She is co-author of more than one hundred technical publications. Maya is a member of Phi Beta Kappa, a Distinguished Member of Technical Staff at LLNL, and a Fellow of the IEEE.
gokhale2 "at" llnl.gov
Oak Ridge National Laboratory
Dr. Thomas P. Karnowski is a Research Staff Member in the Imaging, Signals and Machine Learning Group at ORNL. He earned a Ph.D. in Electrical and Computer Engineering from U. Tennessee-Knoxville. His research interests are in image and signal processing, machine and computer vision, and machine learning as well as their implementations on a variety of platforms. His work has focused on applications in manufacturing, homeland security, and medicine. His the author or co-author of over 100 publications in these areas.
karnowskitp "at" ornl.gov
Oak Ridge National Laboratory
Dr. Seung-Hwan Lim has been a Research Staff Member at the Oak Ridge National Laboratory (ORNL). His career spans research and development conducted in industry and national laboratory. He earned a PhD in Computer Science and Engineering from the Pennsylvania State University. His current research focuses on data intensive system architectures for machine learning, graph processing, and statistical inference algorithms. He earned a BS in Computer Engineering from Seoul National University. Prior to graduate studies, he worked for Samsung’s smartphone business as a software engineer, in charge of device drivers of communication network layers.
lims1 "at" ornl.gov
Lawrence Livermore National Laboratory
Dr. Karl Ni obtained his BS from UC Berkeley and Doctorate from the University of California, San Diego in 2008. Subsequently, he joined the MIT Lincoln Laboratory research staff from 2008 until 2013. There, he served as algorithms co-lead and program manager on various signal & image processing, text analytics, and computer vision problems. He has also volunteered as the secretary of the IEEE Boston Chapter, lecturing for various classes. In 2013, he left MIT/LL to join Lawrence Livermore National Laboratory (LLNL) and is currently a staff scientist. His research focus is large scale data analytics.
ni4 "at" llnl.gov
Lawrence Livermore National Laboratory
Dr. Roger Pearce is a computer scientist in the Center for Applied Scientific Computing (CASC) at Lawrence Livermore National Laboratory. His research interests include parallel and external memory graph algorithms, deep learning, and data-intensive computing. Roger received a Ph.D. in Computer Science form Texas A&M University in 2013, and also holds a B.S. in Computer Engineering from Texas A&M University. Roger joined LLNL in 2008 as a Lawrence Scholar, and joined CASC in 2013.
pearce7 "at" llnl.gov
Oak Ridge National Laboratory
Dr. Laura Pullum is a senior research scientist in the Computational Data Analytics Group at Oak Ridge National Laboratory (ORNL). Her career includes research conducted in academia, industry (small and large businesses, and non-profit) and a national laboratory, currently Oak Ridge National Laboratory. Laura received a Doctorate of Science in Systems Engineering and Operations Research. Her current research includes evaluation, verification and validation of predictive analytics and machine learning systems, and the use and validation of machine learning algorithms for the examination of disease dynamics. Dr. Pullum has authored hundreds of publications including books, book chapters, and peer-reviewed papers; serves on technical advisory boards; and is a senior member of the IEEE Computer Society.
pullumll “at” ornl.gov
Oak Ridge National Laboratory
Dr. Derek Rose is a postdoctoral research associate working at Oak Ridge National Laboratory in the Imaging, Signals, and Machine Learning Group. His current active research areas include segmentation and classification of subcellular structures in fluorescence microscopy and vehicle detection and tracking using correlation filters and deep learning. Further research interests include neural networks, visual attention mechanisms, natural image statistics, bag-of-visual words models, sparse coding, and neuromorphic computing and biologically inspired architectures.
rosedc1 "at" ornl.gov
Oak Ridge National Laboratory
Dr. Steven Young is a postdoctoral research associate at Oak Ridge National Laboratory working in the Computational Data Analytics Group. He earned a Ph.D. in Computer Engineering from The University of Tennessee where he studied machine learning in the Machine Intelligence Lab. He also holds a B.S. in Electrical Engineering from The University of Tennessee. His current research involves applying machine learning to large scale datasets with a focus on deep learning methods.
youngsr "at" ornl.gov
