Leadership Team

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Xiaolin Andy Li (Center Director)

Dr. Xiaolin Andy Li is a Professor and University Term Professor of Electrical and Computer Engineering at the University of Florida where he teaches cloud computing, big data ecosystems, cognitive IoT, and advanced deep learning. He is the director of Large-scale Intelligent Systems Laboratory (Li Lab). He led the design and deployment of one of the first software-defined campus research networks and campus clouds GatorCloud. He received the NSF CAREER Award, the Internet2 Innovative Application Award, NSF I-Corps Top Team Award,  Top Team Award (DeepBipolar) in the CAGI Challenge, and Best Paper Awards (IEEE ICMLA 2016, IEEE SECON 2016, ACM CAC 2013, and IEEE UbiSafe 2007).
Research Interests: Cloud Computing, Intelligent Platforms, Deep Learning, Precision Medicine, IoT/CPS, Security & Privacy
Homepagehttp://www.andyli.ece.ufl.edu 

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Jose Principe (Deputy Director)

Dr. Jose C. Principe is a Distinguished Professor of Electrical and Computer Engineering at the University of Florida where he teaches advanced signal processing, machine learning and artificial neural networks (ANNs) modeling. He is the Beckis Professor and the Founder and Director of the University of Florida Computational NeuroEngineering Laboratory (CNEL) www.cnel.ufl.edu . His primary area of interest is extracting information from time varying signals with adaptive neural models, with applications to brain machine interfaces. He is a Fellow of IEEE, AIMBE, and IAMBE. He received IEEE Neural Network Pioneer Award in 2011.
Research Interests: Adaptive Systems Theory, Machine Learning, Information Theoretic Learning
Homepagehttp://www.cnel.ufl.edu/people/people.php?name=principe

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Ruslan Salakhutdinov (Center Co-Director)

Dr. Ruslan Slakhutdinov is an Associate Professor in Department of Machine Learning at Carnegie Mellon University. His primary interests lie in deep learning, machine learning, and large-scale optimization. His main research goal is to understand the computational and statistical principles required for discovering structure in large amounts of data. He is an action editor of the Journal of Machine Learning Research and served on the senior programme committee of several learning conferences including NIPS and ICML. He is an Alfred P. Sloan Research Fellow, Microsoft Research Faculty Fellow, Canada Research Chair in Statistical Machine Learning, a recipient of the Early Researcher Award, Connaught New Researcher Award, Google Faculty Award, Nvidia’s Pioneers of AI award, and is a Senior Fellow of the Canadian Institute for Advanced Research.
Research Interests: Deep Learning, Machine Learning, Large-scale Optimization
Homepagehttp://www.cs.cmu.edu/~rsalakhu/

Jian Ma (Site Co-Director)

Dr. Jian Ma is an Associate Professor of Computational Biology in the School of Computer Science at Carnegie Mellon University. He also has affiliated appointment with the Machine Learning Department at CMU. His research is focused on developing new algorithms to understand the human genome organization and function and its implications in human diseases. He also works on high-dimensional machine learning methods to analyze heterogeneous biomedical data. He received an NSF CAREER award and was named “Tomorrow’s PIs” by Genome Technology. He serves as an Associate Editor for PLOS Computational Biology. His lab has been consistently supported by the NSF and the NIH.
Research Interests: Computational Biology, Machine Learning
Homepagehttp://www.cs.cmu.edu/~jianma/

Ameet Talwalkar (Site Co-Director)

Dr. Ameet Talwalkar is an assistant professor in the Machine Learning Department at Carnegie Mellon University, and also co-founder and Chief Scientist at Determined AI. His primary interests are in the field of statistical machine learning, including problems at the intersection of systems and learning, and applications in computational genomics. His current work is motivated by the goal of democratizing machine learning, with a focus on topics related to the scalability, automation, and interpretability of learning algorithms and systems.He led the initial development of the MLlib project in Apache Spark, is a co-author of the graduate-level textbook ‘Foundations of Machine Learning’ (2012, MIT Press), and created an award-winning edX MOOC about distributed machine learning.
Research Interests: Statistical Machine Learning, Systems and Learning, and Computational Genomics
Homepagehttps://www.cs.cmu.edu/~atalwalk/index.html

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Zhu Li (Center Co-Director)

Dr. Zhu Li is an Associate Professor with the Dept of Computer Science & Electrical Engineering, University of Missouri,Kansas City, and director of the Multimedia Computing & Communication (MC^2) Lab. His research interests include audio-visual analytics and machine learning with its application in large scale video repositories annotation, mining and recommendation, video object identification and event recognition, as well as video adaptation, source-channel coding and distributed optimization issues of the wireless video networks.
Research Interests: Audio-Visual Analytics, Machine Learning, Object Recognition, Deep Learning
Homepagehttp://l.web.umkc.edu/lizhu/

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Yugyung Lee (Site Co-Director)

Dr. Yugyung Lee is a Professor in the department of Computer Science and Electrical Engineering at University of Missouri – Kansas City. Her research interests include Big Data Analytics, Computational Intelligence, Semantic Web, Deep Learning, Medical Informatics. She is the author of over one hundred articles in top tier journals and conferences and also received significant funding from federal agencies includingthe National Institute of Health (NIH) and the National Science Foundation (NSF).
Research Interests: Big Data Analytics, Computational Intelligence, Deep Learning, Medical Informatics
Homepagehttp://sce2.umkc.edu/csee/leeyu/

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Dejing Dou (Center Co-Director)

Dr. Dejing Dou is a Professor in the Computer and Information Science Department at the University of Oregon and leads the Advanced Integration and Mining (AIM) Lab. His research areas include ontologies, data mining, data integration, information extraction, and health informatics. His DEXA’15 paper received the best paper award. His KDD’07 paper was nominated for the best research paper award. He is on the Editorial Boards of Journal on Data Semantics and Journal of Intelligent Information Systems. Dejing Dou has received over $4.5 million PI research grants from the NSF and the NIH.
Research Interests: Artificial Intelligence, Data Mining, Health Informatics
Homepagehttps://www.cs.uoregon.edu/~dou

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Allen Malony (Site Co-Director)

Dr. Allen D. Malony is a Professor in the Department of Computer and Information Science at the University of Oregon. He was awarded NSF National Young Investigator award in 1994, a Fulbright Research Scholarship in 1999,  the prestigious Alexander von Humboldt Research Award in 2002. He led the TAU Performance System, a leading open source parallel performance tool suite widely used around the world.
Research Interests: Performance Analysis, PDC/HPC, Scientific Software Environments
Homepagehttps://www.cs.uoregon.edu/People/Faculty/Allen_Malony.php