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Computer Science College of Engineering and Computer Science

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Department of Computer Science
EIEAB 3.239
Email: csci@utrgv.edu
Phone: 956-665-2320

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Machine Intelligence (MI@UTRGV)

Machine Intelligence Website: https://miutrgv.github.io/

 

What We Do


The MI research team is made up of dedicated undergraduate and graduate students helping to expand the boundaries of current technology. The MI lab is a great place for students to gain experience in collecting research and working as a team, we greatly encourage students to join!

Current Projects

  • Humanoid locomotion simulation using Reinforcement Learning (RL)
  • High Entropy Alloy property prediction using Deep NN and GAN
  • Structure-based Virtual Screening using RL
  • Honey bee monitoring system ( https://bee.utrgv.edu/ )
  • Concrete conductivity simulation
  • Pose estimation ( https://bee.utrgv.edu/poseEstimation.html )
  • VCORE emergency management tool ( https://vcore.utrgv.edu/ )
  • Rio Grande River salinity forecasting

 

MI@UTRGV Research Advisors 


Dr. Erik Enriquez
Assistant Professor of Practice 
erik.enriquez01@utrgv.edu

Areas of Research

  • Reinforcement Learning

 

 

 

Dr. Dong-Chul Kim
Associate Professor
dongchul.kim@utrgv.edu

Areas of Research

  • Bioinformatics
  • Data Mining
  • Computer Vision

 

 

Dr. Emmett Tomai
Professor 
Department Chair
emmett.tomai@utrgv.edu

Areas of Research

  • AI Game Development

 

 

 

Related Courses


CSCI 4350 Artificial Intelligence

Study of intelligent machines and machine learning. Includes problem-solving and heuristic search, natural language understanding, game playing, database, and expert systems. Artificial Intelligence projects will be implemented using an AI language such as LISP, Prolog, C++, or Ada.


 

CSCI 4352 Machine Learning

This course introduces machine learning, data mining, and statistical pattern recognition. Topics include supervised learning, unsupervised learning, reinforcement learning, and best practices in machine learning.

 

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