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caiml22423498-WEB-

WHAT

WE DO

Applied AI And
Machine Learning

Bridge developments in AI and Machine Learning to real applications and services in collaboration with our industry partners.

Technology Development
And Deployment

Develop new on-demand technologies for machine learning and large-scale data analysis.

In-house Training

Train a new generation of industrial scientists to address the skills shortage in AI and machine learning areas and increase competitiveness in the high-value information technology sectors, with the development of dedicated education programs.

Intellectual
Property

Develop IP with and for our partners on demand.

Joint Research
And Development

Jointly research and develop tools, products, and services for our partners.

The Center for Applied Artificial Intelligence and Machine Learning (CAIML) is housed in the Department of Computer Science within the Erik Jonsson School of Engineering and Computer Science at the University of Texas at Dallas.

Our mission is to create a center of excellence skilled in applying leading-edge AI & ML technologies and solutions for our partners’ strategic products and services.

The objective of the Center for Applied AI and Machine Learning is to develop long-term, ongoing joint activities through research and development partnerships with companies and organizations in the Dallas Fort Worth Metroplex area and Texas. Our aim is to focus on applied R&D rather than on basic research with the intent of being integral rather than ancillary wherever possible.

Our core team consists of researchers whose expertise lie in artificial intelligence, machine learning, natural language processing, deep learning,   data mining,  big data, computational logic, explainable AI, automated commonsense reasoning,  probabilistic graphical models, health informatics/precision health, medical informatics, and biomedical applications. The research emphasis of the Center for AI & ML implies it is synergistic with the Human Language Technology Research Institute, the Center for Machine Learning, and the Cyber Security Research and Education Institute, and the Institute for Data Analytics.

Dr. Doug DeGroot

Director

  • Artificial Intelligence
  • Machine Learning
  • Data Science
  • Artificial Consciousness and Emotions
  • Computer Architecture
  • Natural Language Processing

Dr. Gopal Gupta

Co-Director

  • Explainable AI
  • Machine Learning
  • Computational Logic
  • Automated Common Sense Reasoning

Dr. Lakshman Tamil

  • Telemedicine,
  • Internet of Things (IoT)
  • Machine learning and artificial intelligence applications to Medicine and Healthcare

Dr. Feng Chen

  • Anomaly, Event, and Fraud Detection
  • Spatial-Temporal Data Analysis
  • Big Data Analytics
  • Graph Mining and Network Science
  • Machine Learning
  • Artificial Intelligence

Dr. Ovidiu Deascu

  • Computational Geometry
  • Algorithms and Optimization
  • Bio-Medical Computing
natarajan sriraam Spring 2018

Dr. Sriraam Natarajan

  • Artificial Intelligence
  • Machine Learning
  • Statistical Relational AI
  • Health Informatics/Precision Health

Dr. Rishabh Iyer

  • Artificial Intelligence
  • Machine Learning
  • Discrete Optimization (specifically submodular optimization) in Machine Learning
  • Convex and Non-Convex Optimization in Machine Learning
  • Deep Learning for Image Classification and Object Detection
  • Data Summarization (Video/Image/Text)
  • Active Learning, Data Subset Selection, Data partitioning, Model Compression/Pruning, etc.
  • Video Analytics
  • Online Learning, Contextual Bandits and Reinforcement Learning
  • Click Prediction, Web Search and Information Retrieval

Dr. Nicholas Rouzzi

  • Graphical Models
  • Machine Learning
  • Approximate Inference and Learning
  • Explainable AI

ANURAG NAGAR 2 - fall 2018

Dr. Anurag Nagar

  • Machine Learning
  • Bioinformatics
  • Financial Data Mining

vincent ng - cropped smaller

Dr. Vincent Ng

  • Natural Language Processing
  • Artificial Intelligence
  • Machine Learning

Dr. Vibhav Gogate

  • Artificial Intelligence
  • Machine Learning
  • Probabilistic Inference
  • Statistical Relational Learning

Dr. Haim Schweitzer

  • Artificial Intelligence
  • Machine Learning
  • Computer Vision

Dr. Jessica Ouyang

  • Natural Language Processing
  • Automatic Summarization
  • Text Generation

Dr. Latifur Khan

  • Machine Learning
  • Data Mining
  • Big Data
  • Data Analytics
  • Stream Data Mining

Dr. Sanda Harabagiu

  • Artificial Intelligence
  • Machine Learning
  • Natural Language Processing
  • Information Retrieval, Knowledge Processing
  • Medical Informatics

Dr. Dan Moldovan

  • Machine Learning
  • Artificial Intelligence
  • Natural Language Processing
  • Semantic Technologies

Dr. Anjum Chida

  • Machine Learning
  • Bioinformatics
  • Computational Biology

Dr. Klye Fox

  • Algorithms and Theory
  • Computational Geometry and Topology
  • Combinatorial Optimization and Graph Algorithms

caiml22423498-WEB-

Our mission is to create a center of excellence skilled in applying leading-edge AI & ML technologies and solutions for our partners’ strategic products and services. The objective of the Center for Applied AI and Machine Learning is to develop long-term, ongoing joint activities through research and development partnerships with companies and organizations in the Dallas Fort Worth Metroplex area and Texas.

WHAT WE DO

Applied
AI & Machine Learning

  • Bridge developments in AI & ML to real
    applications and services in
    collaboration with our industry partners.

In-House
Training

  • Train a new generation of industrial
    scientists to address the skills shortage
    in AI&ML areas and increase
    competitiveness in the high-value
    information technology sectors, with the
    development of dedicated education
    programs.

Intellectual
Property

  • Develop IP with and for our partners,
    on demand.

Technology Development
And Deployment

  • Develop on-demand new
    technologies for machine learning
    and large-scale data analysis

Joint Research and
Development

  • Jointly research and develop tools,
    products, and services for out
    partners.

Dr. Doug Degroot

Director

Data Science, Artificial Consciousness and Emotions, Computer Architecture, Natural Language Processing, AI, ML

Dr. Gopal Gupta

Co-Director

Explainable AI, ML, Computational Logic, Automated Common Sense Reasoning

Raj Pallapothu

Entrepreneur-in-Residence

Dr. Nicholas Rouzzi

Graphical Models, Machine Learning, Approximate Inference and Learning, Explainable AI

natarajan sriraam Spring 2018

Dr. Sriraam Natarajan

AI, ML, Statistical Relational AI Health Informatics/Precision Health

vincent ng - cropped smaller

Dr. Vincent Ng

Natural Language Processing,
AI, ML

Dr. Haim Schweitzer

AI, ML, Computer Vision

Dr. Vibhav Gogate

AI, ML, Probabilistic Inference, Statistical Relational Learning

Dr. Bill Semper

ML, Data Mining

Dr. Sanda Harabagiu

AI, ML, Natural Language Processing, Information Retrieval, Knowledge Processing, Medical Informatics

Dr. Dan Moldovan

ML, AI, Natural Language Processing, Semantic Technologies

Dr. Latifur Khan

ML, Data Mining, Big Data, Data Analytics, Stream Data Mining

Dr. Anjum Chida

ML, Bioinformatics, Computational Biology

ANURAG NAGAR 2 - fall 2018

Dr. Anurag Nagar

ML, Bioinformatics Financial Data Mining

UTD's CS Department is one of the largest in the nation with 80 faculty members and approximately 2900 students; I have been Department Head since August 2009.

I have worked on advanced computing research since 1986. My research has been focused on computational logic, declarative programming including AI and machine learning. My PhD students and I have developed many advanced techniques and systems for automated reasoning, automated software migration, machine learning, assistive technology, parallel computing, etc. Many of the systems my lab has developed have been made publicly available (or commercialized through startups). Visit my UT Dallas home page for more details. Also, have significant expertise with managing and advancing a large department (CS Department at UT Dallas is the 4th largest department in the US). Helped set up many innovative programs within the CS Department (CS Mentor Center, Honors Programs, K-12 Outreach, visit the CS Department news page for more details.