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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