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<h2 class="featurette-name-heading">Joseph <span class="text-muted">JaJa</span></h2>
<p class="lead">University of Maryland</p>
<p>Joseph JaJa is Professor of Electrical and Computer Engineering, and the Institute for Advanced Computer Studies at the University of Maryland, College Park. . Dr. JaJa received his Ph.D. degree in Applied Mathematics from Harvard University and has since published extensively in a number of areas including parallel and distributed computing, theoretical computer science, circuits and systems, and data-intensive computing. His current research interests are in high performance computing, statistical machine learning, and scientific visualization. Dr. JaJa has served in a number of leadership positions at Maryland including Interim CIO and VP, Director of the Institute for Advanced Computer Studies, and Director of Cyberinfrastructure of the National Socio-environmental Synthesis Center. Dr. JaJa has received numerous awards including the IEEE Fellow Award in 1996, the 1997 R&D Award for the development software for tuning parallel programs, the ACM Fellow Award in 2000, and the Internet2 IDEA Award in 2006.</p>
<p>joseph "at" umiacs.umd.edu</p>
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<h2 class="featurette-name-heading">Wael <span class="text-muted">AbdAlmageed </span></h2>
<p class="lead">Information Sciences Institute, University of Southern California</p>
<p>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.</p>
<p>wamageed "at" isi.edu</p>
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<h2 class="featurette-name-heading">Barry Y. <span class="text-muted">Chen </span></h2>
<p class="lead">Lawrence Livermore National Laboratory</p>
<p>Dr. Barry Y. Chen is the Knowledge Systems and Informatics Group Leader at the Lawrence Livermore National Laboratory where he serves as principal investigator on several projects developing and applying scalable machine learning algorithms for clustering, classification, anomaly, and change detection</p>
<p>chen52 "at" llnl.gov</p>
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<h2 class="featurette-name-heading">Damian <span class="text-muted">Borth </span></h2>
<p class="lead">Deep Learning Competence Center, Deutsches Forschungszentrum für Künstliche Intelligenz (DFKI)</p>
<p>Dr. Damian Borth is the Director of the Deep Learning Competence Center at the German Research Center for Artificial Intelligence (DFKI) in Kaiserslautern, the Principle Investigator of the NVIDIA AI Lab at the DFKI, and founding co-director of Sociovestix Labs, a social enterprise in the area of financial data science. Damians research focuses on large-scale multimedia opinion mining applying machine learning and in particular deep learning to mine insights (trends, sentiment) from online media streams. His work has been awarded by NVIDIA at GTC Europe 2016, the Best Paper Award at ACM ICMR 2012, the McKinsey Business Technology Award 2011, and a Google Research Award in 2010. Damian currently serves as a member of the steering group at the VolkswagenStiftung, the review committee at the Baden-Wurttemberg Stiftung, the assessment committee for the Investment Innovation Benchmark (IIB) and several other steering and program committees of international conferences and workshops. He is also a founding member the Financial Data Science Association and scientific director of the Certified Financial Data Science Program at Deutsche Vereinigung fur Finanzanalyse und Asset Management (DVFA).</p>
<p>damian.borth "at" dfki.de</p>
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<h2 class="featurette-name-heading">Maya <span class="text-muted">Gokhale</span></h2>
<p class="lead">Lawrence Livermore National Laboratory</p>
<p>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.</p>
<p>gokhale2 "at" llnl.gov</p>
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<h2 class="featurette-name-heading">Seung-Hwan <span class="text-muted">Lim</span></h2>
<p class="lead">Oak Ridge National Laboratory</p>
<p>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.</p>
<p>lims1 "at" ornl.gov</p>
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<img class="featurette-image img-responsive" src="bio_images/Lim.png" alt="Seung-Hawn Lim">
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<h2 class="featurette-name-heading">Derek <span class="text-muted">Rose</span></h2>
<p class="lead">Oak Ridge National Laboratory</p>
<p>Dr. Derek Rose is a Research Staff Member 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.</p>
<p>rosedc "at" ornl.gov</p>
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<img class="featurette-image img-responsive" src="bio_images/Rose.jpg" alt="Derek Rose">
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<h2 class="featurette-name-heading">Chih-Chieh <span class="text-muted">Yang</span></h2>
<p class="lead">IBM Research</p>
<p>Chih-Chieh Yang is a postdoctoral research scientist in the Data Centric Systems group at IBM Research. He received both his B.S. and M.S. from National Tsing Hua University, and accumulated industry experiences working for the top Taiwanese IC design house, Mediatek, for several years before starting and eventually earning his Ph.D from University of Illinois at Urbana-Champaign. His past research experiences include designing software components that facilitate the development of distributed applications and high-level parallel programming abstractions. His current focus is on scaling distributed machine learning applications to both current state-of-the-art supercomputers and future extreme scale HPC systems.</p>
<p> chih.chieh.yang "at" ibm.com</p>
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<h2 class="featurette-name-heading">Gabriel <span class="text-muted">Perdue</span></h2>
<p class="lead">Fermi National Accelerator Laboratory</p>
<p>I work for the Fermi National Accelerator Laboratory as an particle physicist in the Scientific Computing Division. I am an Associate Scientist working on the MINERvA Experiment, high performance computing (espcially parallelization), and on the GENIE neutrino event generator.</p>
<p>perdue "at" fnal.gov</p>
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<h2 class="featurette-name-heading">Xipeng <span class="text-muted">Shen</span></h2>
<p class="lead">North Carolina State University</p>
<p>Prior to joining NC State, Shen was the Adina Allen Term Distinguished Associate Professor in the Computer Science Department at The College of William and Mary. He was a Visiting Researcher at M.I.T., Microsoft Research, and Intel Labs between 2012 and 2013, and an assistant professor at The College of William and Mary from 2006 to 2012. His research in data locality for exascale computing won the prestigious Early Career Research Award from the U.S. Department of Energy in 2011. His research in input-centric program dynamic optimizations won the CAREER Award from the US National Science Foundation in 2010. He is a receipt of Google Faculty Research Award. For the high impact of his research, he has been appointed an IBM Canada CAS Research Faculty Fellow since 2010. He is currently an ACM Distinguished Speaker, and a senior member of IEEE. Dr. Shen received his Ph.D. and M.S. in Computer Science from University of Rochester, his M.S. in Pattern Recognition and Intelligent Systems from Chinese Academy of Sciences, and his B.E. in Industrial Engineering from North China University of Technology.</p>
<p>xshen5 "at" ncsu.edu</p>
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<img class="featurette-image img-responsive" src="bio_images/xipeng_profile_2_b.png" alt="Xipeng Shen">
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<h2 class="featurette-name-heading">Kazu <span class="text-muted">Terao</span></h2>
<p class="lead">SLAC National Accelerator Laboratory</p>
<p>At SLAC I continue to participate in MicroBooNE Liquid Argon Time Projection Chamber (LArTPC) experiment (see more description below), but with a focus expanding toward future LArTPC experiments such as SBN program and DUNE. Together with continued tasks from my previous position at Columbia, I contribute to developing deep learning research group and facility at SLAC laboratory.</p>
<p>kterao "at" stanford.edu</p>
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<h2 class="featurette-name-heading">Steven <span class="text-muted">Young</span></h2>
<p class="lead">Oak Ridge National Laboratory</p>
<p>Dr. Steven Young is a research scientist 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.</p>
<p>youngsr "at" ornl.gov</p>
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<img class="featurette-image img-responsive" src="bio_images/Young.jpg" alt="Steven Young">
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<h2 class="featurette-name-heading">Brian <span class="text-muted">Van Essen</span></h2>
<p class="lead">Lawrence Livermore National Laboratory</p>
<p>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.</p>
<p>vanessen1 "at" llnl.gov</p>
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<img class="featurette-image img-responsive" src="bio_images/VanEssen.jpg" alt="Brian Van Essen">
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<h2 class="featurette-name-heading">Una-May <span class="text-muted">O'Reilly</span></h2>
<p class="lead">Massachusetts Institute of Technology</p>
<p>Una-May O'Reilly is founder and co-leader of the AnyScale Learning For All (ALFA) group at Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory. ALFA focuses on scalable machine learning, evolutionary algorithms, and frameworks for large scale knowledge mining, prediction and analytics. She received the EvoStar Award for Outstanding Achievements in Evolutionary Computation in Europe in 2013. She is a Junior Fellow (elected before age 40) of the International Society of Genetic and Evolutionary Computation, now ACM Sig-EVO. She now serves as Vice-Chair of ACM SigEVO. She is the area editor for Data Analytics and Knowledge Discovery for Genetic Programming and Evolvable Machines (Kluwer), and editor for Evolutionary Computation (MIT Press), and action editor for the Journal of Machine Learning Research.</p>
<p>unamay "at" csail.mit.edu</p>
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<img class="featurette-image img-responsive" src="bio_images/OReilly.jpeg" alt="Una-May O'Reilly">
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<h2 class="featurette-name-heading">Abdullah<span class="text-muted">Al-Dujaili</span></h2>
<p class="lead">Massachusetts Institute of Technology</p>
<p>I received the B.Eng. degree in electrical and electronics engineering from Universiti Teknologi PETRONAS, Malaysia, in 2012. I defended my Ph.D. thesis in March, 2017, under the supervision of Suresh Sundaram at the School of Computer Engineering, Nanyang Technological University, Singapore. From October, 2016 till November, 2017 , I was a Data Scientist (Operations Research) at Grab. Since November, 2017, I have been a Postdoc at the ALFA group, MIT CSAIL working with Una-May O'Reilly on principled AI approaches to adversarial dynamics and healthcare.</p>
<p>ash.aldujaili "at" gmail.com</p>
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<h2 class="featurette-name-heading">Trilce <span class="text-muted">Estrada</span></h2>
<p class="lead">University of New Mexico</p>
<p> Trilce Estrada is an assistant professor in the department of Computer Science at the University of New Mexico. Her research interests include self-managed distributed systems, Big Data analysis, crowd sourcing, and machine learning. Recently she got awarded the National Science Foundation's Early Career Award for the proposal entitled CAREER: Enabling Distributed and In-Situ Analysis for Multidimensional Structured Data
The goal of her research program is to solve computationally intensive and data intensive problems in science, health, and education, especially in scenarios where resources and trained professionals are scarce. I believe that a computer is only as good as the difference it can make in the world, and I strive to achieve this level of impact with her work. </p>
<p> trilce "at" unm.edu </p>
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<h2 class="featurette-name-heading">Nikoli <span class="text-muted">Dryden</span></h2>
<p class="lead">University of Illinois at Urbana-Champaign</p>
<p>I am a PhD student in computer science at the University of Illinois at Urbana-Champaign. My advisor is Professor Marc Snir. My research focuses on scaling deep neural network training on HPC resources (large clusters and supercomputers) by developing new algorithms and optimized implementations, and applying DNNs to scientific and simulation data sets.. I also work on tools and applications for exascale supercomputers.</p>
<p>dryden2 "at" illinois.edu</p>
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<h2 class="featurette-name-heading">Brian <span class="text-muted">Kingsbury</span></h2>
<p class="lead">IBM Watson Group</p>
<p>Dr. Brian Kingsbury is a principal research staff member in the IBM AI Foundations lab. He earned a BS in electrical engineering from Michigan State University and a PhD in computer science from the University of California, Berkeley. His research interests include deep learning, large-vocabulary speech transcription, and keyword search. Brian has contributed to IBM's entries in numerous competitive evaluations of speech technology, including Switchboard, SPINE, EARS, Spoken Term Detection, and GALE. He was co-PI and technical lead for LORELEI, an IBM-led consortium that participated in the IARPA Babel program. He has served on the Speech and Language Technical Committee of the IEEE Signal Processing Society; as an ICASSP speech area chair; as an associate editor for IEEE Transactions on Audio, Speech, and Language Processing; and as a program chair for the International Conference on Representation Learning.</p>
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<img class="featurette-image img-responsive" src="bio_images/kingsbury.jpeg" alt="Brian Kingsbury">
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<h2 class="featurette-name-heading">Guojing <span class="text-muted">Cong</span></h2>
<p class="lead">IBM Research</p>
<p>Guojing Cong is a Research Staff Member at the IBM TJ Watson research center in Yorktown Heights, New York. His current research interests include large-scale machine learning on HPC systems and graph analysis in the social media and security settings. In the past he has worked on parallel graph algorithms, large-scale combinatorial optimizations, finance risk analytics, and performance analysis and tuning for HPC systems. He received his PhD in Computer Engineering from the University of New Mexico. He is a senior member of IEEE.</p>
<p>gcong "at" us.ibm.com</p>
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<h2 class="featurette-name-heading">Derek <span class="text-muted">Murray</span></h2>
<p class="lead">Google Research</p>
<p>Derek Murray is a senior software engineer in the Google Brain team, currently building the TensorFlow system for large-scale machine learning. His principal research interest is distributed systems for parallel computation, with a particular emphasis on expressive programming constructs like streaming and iteration. Previously he was a researcher at Microsoft Research Silicon Valley, where he worked on the Naiad system for incremental, iterative, and interactive processing. He received his PhD in Computer Science from the University of Cambridge, his MSc in High Performance Computing from the University of Edinburgh, and his BSc from the University of Glasgow.</p>
<p>mrry "at" google.com</p>
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<h2 class="featurette-name-heading">Manjunath <span class="text-muted">Kudlur</span></h2>
<p class="lead">Google</p>
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<h2 class="featurette-name-heading">Reid <span class="text-muted">Porter</span></h2>
<p class="lead">Los Alamos National Laboratory</p>
<p>Reid Porter is a research scientist in the Computing, Computational and Statistical Sciences Division at Los Alamos National Laboratory. Reid obtained a doctorate in electrical engineering from the Queensland University of Technology, Australia, in 2002. Reid's thesis work focused on using reconfigurable computing to accelerate learning and inference in convolutional neural networks for satellite image analysis, and highlights his early interest at the intersection of machine learning, signal processing, and computer architecture. Reid's interest in these topics has continued to grow while working on a variety projects at Los Alamos. He has more recently contributed theory, algorithms and software for interactive machine learning systems to better support domain experts in specialized science and defense applications. From 2015 to 2018 Reid was a technical leader in Computer Vision at Kitware Inc. where he focused on moving object detection, tracking and activity detection in video and wide area motion imagery.</p>
<p>rporter "at" lanl.gov</p>
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<img class="featurette-image img-responsive" src="bio_images/Reid.jpg" alt="Reid Porter">
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