Dr. Manoranjan Majji

Image analysis and software tools to provide an automated means of infrastructure damage assessment from natural disasters.


Dr. Ali Mostafavi

This is a finished project – view it here!
AI for Urban Flood Risk Prediction: This study employs AI methods for analyzing multi-model data (social media, remote sensing, crowdsourced data) to predict flood risk in urban area.

Dr. Ali Mostafavi

Social Sensing of Community Response to Disasters: This study will examine social media and crowdsourced data in building NLP, Network Embedding, and Network modeling to assess community response to disaster impacts.

Dr. Ali Mostafavi

AI for Urban Mobility Prediction to Support Crisis Response: The objective of the project is to create novel machine learning models to predict disruptions in urban road systems and mobility during crises


Dr. Raymundo Arroyave

Microstructure Zoo: use a massive amount of microstructural images to train a deep learning model to be able to classify new microstructure images. This requires microstructure images to be classified prior to model training. The important features in images will be extracted and used as the classifier.

Dr. Raymundo Arroyave

3D Printing: This project consists of using a large database of extracted literature data to better understand the print parameters and their effect on the quality of the printed part. With so many print parameters, feature extraction will be very important in the analysis.

Dr. Kelvin Xie

Data mining and deep learning of electron microscopy images.


Dr. McAdams

Speculative Technology NLP Analysis: Predict future technological innovations from science fiction novels and text.


Dr. Garth Crosby

The capstone team is developing a portable medical diagnostic device. The device will utilize AI/machine learning to analyze patients’ physiological data. The user will be able to interact with the device through a dedicated app both to input patients’ data and receive the results of the processed data.



Dr. Timothy Logan

Process data from the Houston Lightning Mapping Array to predict storm severity and flooding potential in order to alert the public. Machine learning and data mining skills are strongly needed. Students who wish to enhance website design skills are also needed.


Dr. Kurt Zhang

Develop a deep learning generative model for single cell sequencing data. The revolution of single cell high throughput technology has generated a massive amount of genomic data for understanding molecular mechanisms at single cell resolution. However, the bioinformatics tools for single cell sequencing data analysis are under-developed, and the traditional machine learning methods for bulk sequencing data don’t work well for single cell data. Help develop a software package that integrates advanced statistical method and deep learning modeling.



Prof. David Lowe

The Libraries maintain a repository containing open access articles representing TAMU research. Using AI-related text mining akin to sentiment analysis, we would like to add a metadata facet for this collection that describes the research activity as either basic or applied research. We feel confident that, checking for the presence of two discrete sets of verbal phrases, we can classify the research type by expressions like “understand the phenomenon of” for basic and “apply this method” for applied research.

tidal Proposed Projects

Advisor TBD

Autodrive Challenge (SAE Autonomous Vehicle): The automotive industry is being transformed by self driving vehicles. Be on the leading edge of this technology, working alongside the SAE team to program and train a self-driving vehicle for an autonomous vehicle competition.

Advisor TBD

Microfluidics Analysis Automation: Lab-on-chip offers high-throughput data with an experimental bottleneck at the analysis phase. Using deep learning and image processing, automate this analysis for lipid-lipid interactions.

Advisor TBD

Brain-Computer Interface Optimization: BCI, Nanotechnology, and Artificial Intelligence are rapidly changing the sensing and control capabilities of various devices. Develop Bayesian Belief Networks to process signals to and from the brain for sensing and controls.