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UT Dallas CS Professors and PhD Students Have Six Papers Accepted Into The Top Artificial Intelligence Conference

Next January, researchers from the UT Dallas CS Department will have a strong presence at the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19) with six accepted research papers. The purpose of the AAAI conference series is to promote research in artificial intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers in AI and its related disciplines. The AAAI Conference is particularly selective in accepting research papers and each paper submitted to the conference is rigorously peer-reviewed by multiple experts. Six papers submitted by Drs. Gopal Gupta, Haim Schweitzer, Sriraam Natarajan, Nicholas Ruozzi, Vincent Ng, Latifur Khan, Gautam Kunapuli, Crystal Maung, Professor Gordon Arnold and their respective research students were accepted into the Thirty-Third AAAI Conference on Artificial Intelligence.

The following is a list of papers authored by UT Dallas faculty members that were accepted by the AAAI Conference:

Paper Title Authors
Induction of Non­‐Monotonic Logic Programs to Explain Boosted Tree Models Using LIME
Farhad Shakerin (UT Dallas), Gopal Gupta (UT Dallas)
Multistream Classification with Relative Density Ratio Estimation
Bo Dong (UT Dallas), Swarup Chandra (UT Dallas), Yang Gao (UT Dallas), Latifur Khan (UT Dallas)
Heuristic Search Algorithm for Dimensionality Reduction Optimally Combining Feature Selection and Feature Extraction
Baokun He (UT Dallas), Swair Shah (UT Dallas), Crystal Maung (UT Dallas), Gordon Arnold (UT Dallas), Guihong Wan (UT Dallas), Haim Schweitzer (UT Dallas)
Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs
Mayukh Das (UT Dallas), Devendra Singh Dhami (UT Dallas), Gautam Kunapuli (UT Dallas), Kristian Kersting (TU Darmstadt), Sriraam Natarajan (UT Dallas)
Marginal Inference in Continuous Markov Random Fields using Mixtures
Yuanzhen Guo (UT Dallas), Hao Xiong (UT Dallas), Nicholas Ruozzi (UT Dallas)
Abstractive Summarization: A Survey of the State of the Art
Vincent Ng (UT Dallas), Hui Lin (UT Dallas)


The UT Dallas Computer Science Department has a large group of faculty members focused on research in Artificial Intelligence and all of its respective fields. Several of the faculty members conduct their research under the umbrella of the Institute for Human Language and Technology (HLTRI) which houses various institutes including the Center for Machine Learning and the Center for Applied AI and ML. Research into Artificial Intelligence includes natural language processing, machine learning, speech processing, computer vision, automatic question-answering, and automated reasoning.

The UT Dallas Computer Science Department is ranked 14th in AI and 6th in the combined areas of Artificial Intelligence and Natural Language Processing on Additionally, the CS Department ranks 8th in software engineering as well as in embedded and real-time systems. publishes its rankings of Computer Science Schools based on the number of publications by faculty that have appeared in the most selective conferences in each area of Computer Science. The rankings are designed to identify institutions and faculty actively engaged in research across a number of areas of computer science.


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.

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