Research

We are a team of UTRGV faculty and students working in Theoretical Computer Science. Our primary interest is in the field of algorithmic self-assembly. Algorithmic self-assembly is a relatively new research area that has great potential for applications in a wide range of fields, from nanotechnology to biomedical technology.

Our team has expertise in many areas, and thus our research is not limited to this field, but it is our focus. Beyond the theoretical results, we host several software projects for research and education listed on the software page. All software is open-source and hosted on GitHub.

We are always looking for new collaborators and students, so please email us if you are interested. We also host the weekly Xtreme Algorithms, so come find out what we’re working on and join us!

Faculty:

• Dr. Robert Schweller
• Dr. Timothy Wylie
• Dr. Bin Fu

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Our research focuses on designing algorithms and development models and software to extract information from a variety of molecular biology data including genomic, transcriptomic, proteomic, and phospho-proteomic (i.e. omics data).

Faculty

• Dr. Marzieh Ayati

MI research focuses on Humanoid Locomotion using reinforcement learning (RL), High Entropy Alloy Prediction using deep neural networks and generative adversarial networks, Structure-Based Virtual Screening using RL, and much more.

Faculty:

• Dr. Dong-Chul Kim
• Dr. Erik Enriquez
• Dr. Emmett Tomai

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MARS research focuses on Intelligence Swarm Robotics. More specifically, Scalable Foraging Swarm Robotics. Jajor tasks include algorithm design, modeling, simulation, training, optimization, data visualization, and analysis.

Faculty:

• Dr. Qi Lu

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TDM research focuses on data mining and knowledge discovery. Our research team aims to push the boundaries of current data mining and knowledge discovery technology in mining time series data such as sensor signals and video.

Faculty

• Dr. Yifeng Gao