Our panel on “The Future of Smart Ecosystem Empowered by IoT Collaborative Technologies” was accepted and will be presented at the IEEE GLOBECOM 2022.
Category: Engineering
Panel Accepted to FNWF22!
Our panel on “Agriculture in the Age of Advanced Technology” was accepted and will be presented at the IEEE Future Networks World Forum 2022.
IN THE NEWSROOM
NSF STTR for real-time mineral data collection and identification module, which will incorporate machine learning and a unique sensor package to analyze the walls of mineral exploration and geotechnical boreholes. Newsroom: Texas State University:
Engineering Smart Firefighting with Dell-NVIDIA!
Awarded $24,976.00 from Dell-NVIDIA for the Human Detection Using IR, and Scream DL Classifiers and Prototype Development of Autonomous Vehicle Units for Smart Firefighting project for this summer/fall.
NSF-STTR FUNDING AWARD!
Awarded $256,000 from the NSF-STTR Program for Phase I: Real-Time Mineral Data Collection and Identification Module with Stratajam, LLC as the TXST Co-PI!
Health Scholar Showcase Poster Accepted!
Discussing resilient health research topics at #HSS22. Join me and Texas State University’s Translational Health Research Center on April 8th to learn more about our research: “Human Expression Recognition Deep Learning Models to Help Children with ASD Identify Emotions.”
In the Newsroom
NSF grant establishes REU site for undergrad research into smart, connected communities, health. Newsroom: Texas State University:
IEEE Article Accepted!
Co-authored journal article “Manufacturing Operator Ergonomics: A Conceptual Digital Twin Approach to Detect Biomechanical Fatigue” was accepted to IEEE Access.
NSF-REU FUNDING AWARD!
Awarded $344,029 from the NSF-REU Program for the Undergraduate Research Experiences in Machine Learning, Analytics, and Augmented Reality for Smart and Connected Health.
REP Funding Award!
Collaboration with Dr. Maria Resendiz (PI – Dept. of Communication Disorders) was awarded $10,984 from the Research Enhancement Program at Texas State University for the development of the Emotion Validation Dataset.
