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UT Dallas CS Department Launches Research Center for Machine Learning

Machine Learning has gained significant popularity and has flourished in the past decade due to the development of scalable computing coupled with access to diverse data sources. Consequently, it has seemed only fitting that the UT Dallas Computer Science department would launch a research center for machine learning. The newly established Center for Machine Learning is housed in the Department of Computer Science within the Erik Jonsson School of Engineering and Computer Science. The mission of the Center for Machine learning is to foster cutting-edge research and development of machine-learning algorithms motivated by challenges from real work domains ranging from precision health to natural language understanding, from biology to social network analysis, and from vision to mobile health. The center’s core team consists of researchers whose expertise lie in relational models, probabilistic modeling, combinatorial optimization, active learning, logic-based learning, human-in-the-loop learning, reinforcement learning, supervised learning, and data mining.

The Center for Machine Learning was established in spring 2019 with members from academia, industry, and international research institutions. The founding members include UT Dallas Computer Science faculty members, Drs. Sriraam Natarajan (Director), Vibhav Gogate (Co-Director), Nicholas Ruozzi, and Gautam Kunapuli. They are accompanied by fellow UT Dallas CS Professors Drs. Sanda Harabaigu, Vincent Ng, Latifur Khan, Benjamin Raichel, Bhavani Thuraisingham, Murat Kantarcioglu, Haim Schweitzer, Dan Moldovan, Ovidiu Daescu, and Gopal Gupta. The center also collaborates with members of industry and academia, these include the Allen Institute of AI, Amazon, SRI International, Los Alamos National Lab, Nuance Communications, University of Texas Southwestern Medical Center, Duke University, Indian Institute of Technology, University of California Irvine, University of Illinois at Urbana-Champaign, University of Wisconsin, University of British Columbia, University of Pennsylvania, Technical University of Darmstadt, Oregon State University, University of Colorado, Washington State University, and the University of Memphis. The Center for Machine Learning is a UT Dallas Computer Science Department entity.

The research emphasis of the center implies it is synergistic with the UT Dallas Human Language Technology Research Institute (HLTRI) and the UT Dallas Cyber Security Research and Education Institute (CSI). Furthermore, the center works to promote outreach and educational activities in machine learning and AI, such as a summer school for students from other universities who are interested in this field. The center promotes education in machine learning at the undergraduate and graduate levels, through core faculty developing and teaching courses in three primary areas: (1) machine learning, (2) artificial intelligence, and (3) advanced machine learning topics including probabilistic graphical models and statistical relational AI.

The center is currently working on various machine learning-related research projects. One of the major thrusts of research being done on machine learning is Explainable AI (XAI) Project funded by the Defense Advanced Research Projects Agency (DARPA) for $1.8 Million, headed by Drs. Vibhav Gogate and Nicholas Ruozzi. This project aims to improve upon current state-of-the-art machine learning techniques (e.g., deep neural networks) that produce models that require a large number of learned parameters and a significant amount of hyper-parameter tuning. Below is a breakdown of current grants by each core member of the Center for Machine Learning:

  • Vibhav Gogate: $1,730,909 DARPA (Role: PI, Explainable AI grant with Prof. Nicholas Ruozzi); $550,000 NSF (Role: PI, CAREER), $360,348 NSF (Role: Co-PI, RI Small with Prof. Vincent Ng)
  • Nicholas Ruozzi: $1,730,909 DARPA (Role: PI, Explainable AI grant with Prof. Vibhav Gogate); $201,946 NSF (Role: PI, III)
  • Sriraam Natarajan: $680,000 NSF (Role: PI; SCH grant with Prof. Kris Hauser), $335,000 NIH (Role: Co-PI; R01 with PI Prof. David Page), $419,002 DARPA (Role: Co-PI, CwC grant with PI Prof. Dan Roth), $100,000 Gift (Role: PI, from Turvo Inc), $79800 Amazon (Role: PI, Faculty Award)

Below are brief biographies of the Center for Machine Learning core faculty members:

Dr. Sriraam Natarajan is an Associate Professor at the Department of Computer Science at the University of Texas Dallas and the inaugural director of the UT Dallas Center for Machine Learning. He is also the Director of Statistical Relational Learning (StARLinG) Lab at UT Dallas.

He was previously an Associate Professor and an Assistant Professor at Indiana University, Wake Forest School of Medicine, a postdoctoral research associate at the University of Wisconsin-Madison and had graduated with a Ph.D. from Oregon State University. His research interests lie in the field of Artificial Intelligence, with emphasis on Machine Learning, Statistical Relational Learning and AI, Reinforcement Learning, Graphical Models and Biomedical Applications. He has received the Young Investigator award from US Army Research Office, Amazon Faculty Research Award, XEROX Faculty Award and the IU Trustees Teaching Award from Indiana University. He is an editorial board member of MLJ, JAIR and DAMI journals and is the electronics publishing editor of JAIR.


Dr. Vibhav Gogate is an Associate Professor in the Computer Science Department at the University of Texas at Dallas and the co-director of the UT Dallas Center for Machine Learning. He received his Ph.D. from the University of California, Irvine, in 2009 and then did a two-year post-doc at the University of Washington. His research interests are in artificial intelligence, machine learning, and data mining. His ongoing focus is on probabilistic graphical models and their first-order logic-based extensions such as Markov logic and probabilistic programming.

In 2017, Dr. Gogate earned a National Science Foundation Faculty Early Career Development (CAREER) Award for his work to improve a type of computer algorithm used in artificial intelligence and machine learning. Dr. Gogate was awarded co-winner of both the 2010 and 2012 UAI Inference Competitions.


Dr. Nicholas Ruozzi is an Assistant Professor in the Department of Computer Science at the University of Texas at Dallas.  He was previously a postdoctoral researcher and Adjunct Professor at Columbia University and a postdoctoral researcher at Ecole Polytechnique Federale de Lausanne (EPFL) in Lausanne, Switzerland. He obtained his Ph.D. at Yale University.  His research interests include statistical machine learning, probabilistic graphical models, approximate inference and learning, and optimization.  His work has been funded by the National Science Foundation (NSF) and the Defense Advanced Research Projects Agency (DARPA).


Dr. Gautam Kunapuli is a Research Associate Professor with the Department of Computer Science at The University of Texas at Dallas. He is the currently the co-supervisor of the Statistical Relational Learning (StARLinG) Lab at UT Dallas along with Dr. Sriraam Natarajan. Dr. Kunapuli received his Ph.D. in Mathematics from Rensselaer Polytechnic Institute (RPI), Troy, NY, in 2008 under the supervision of Kristin P. Bennett and Jong-Shi Pang. From 2013–2017, Dr. Kunapuli was Senior Research and Development Scientist at UtopiaCompression Corporation. From 2008–13, he was a Postdoctoral Research Associate at the University of Wisconsin-Madison under the supervision of Jude W. Shavlik and C. David Page Jr. He has over ten years of experience in machine learning and optimization in both industry and academia, with focus on knowledge-based and advice-taking learning algorithms, scalable learning algorithms for Statistical Relational Learning, Learning with Autonomous Agents and Domain Adaptation.


The UT Dallas Computer Science program is one of the largest Computer Science departments in the United States with over 2,800 bachelors-degree students, more than 1,000 master’s students, 190 Ph.D. students,  52 tenure-track faculty members, and 41 full-time senior lecturers, as of Fall 2018. With The University of Texas at Dallas’ unique history of starting as a graduate institution first, the CS Department is built on a legacy of valuing innovative research and providing advanced training for software engineers and computer scientists.