About Us

Machine Intelligence

The Machine Intelligence research team is led by UTRGV Associate Professor Dr. Dong-Chul Kim with collaboration of multiple faculty from various departments within UTRGV, including CS chair Dr. Emmet Tomai and CE co-chair Dr. Jungseok Ho. The MI research team is made up of dedicated undergaraduate 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!

Topics

  • Machine Learning
  • Bioinfomatics
  • Robotics
  • Cyber Security

Join Our Team

Why do research?

By joining our research team you will gain valuable insight on new technologies and have the opportunity to work alongside students and faculty from other departments. You will also be helping promote the image of the university and encourage more sponsors to invest in research here at UTRGV.

Weekly Meetings every Friday @3pm in EIEAB 2.210

EIEAB Research Lab

Research Lab

Our research lab is equiped high performing computers, printers, white boards & markers that are made available to research members throughout university hours.

Security

Our research lab doors can be accessed by research members only. Once you join one of our research teams you will be granted entry access to use our equipment.

Location

We are located on the second floor of the Interdisciplinary Engineering & Academic Building (EIEAB) in room 2.210.

Hours

  • Monday - Friday
  • 8:00am - 7:00pm

Current Work

Our research projects in machine intelligence range from coding baseline algorithms to constructing and programming drones.

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.
  • Concrete conductivity simulation.
  • Pose estimation.

Location

University of Texas - Rio Grande Valley, Edinburg TX 78539

College of Engineering and Computer Science