Dr. Valles was invited to talk at the Department of Physics Colloquium, and will present on “Neural Operators for Physics-Informed AI in Ultrawide Bandgap (UWBG) Semiconductor Research.”
When: April 2nd, 2025
Where: RFM-3219
Time: 5 – 6 PM
Fire Tech: Frontline Innovation for Resilient and Effective Firefighter Technology –
Session 1: How Can Robotics, Drones, and AI Transform Fire Response?
March 26th 12 PM – 1 PM CST
Register: https://txstate.zoom.us/meeting/register/Tf_6H_-1RKSnDAna-cnMmg#/registration
Dr. Valles’s NSF-REU was renewed in collaboration with Texas A&M-San Antonio, “REU Site: Undergraduate Research Experiences in Artificial Intelligence, Data Analytics, and Mixed Reality for Smart and Connected Health“
Dr. Valles is on the “Smart Cities in the Era of 5G and Beyond – An Example” panel at the 2024 IEEE Future Networks World Forum (FNWF) in Dubai, UAE.
Hiroshi‘s “Fully Auto-Regressive Multi-Modal Large Language Model for Contextual Emotion Recognition” paper has been accepted to the 2024 IEEE 15th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON). It will be presented in October at the IBM T. J. Watson Research Center in New York.
Dr. Valles’s “Enhancing Early Diagnosis of Autism With Machine Learning Algorithms Using Postural Control Features” collaborative paper has been accepted to the 2024 IEEE 15th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON). It will be presented in October at the IBM T. J. Watson Research Center in New York.
Dr. Valles’s collaboration paper, “Traffic Safety Through Machine Learning: A Study of Crash Severity Factors,” has been accepted to the 2024 IEEE World AI IoT Congress (AIIoT).
Saad Rafiq and Erich Ellsworth‘s collaboration paper with HiPE Alums Adenrele Ishola, Oscar Resendiz, and Susmitha Haripriya Varanasi, “Design of Autonomous Rover for Firefighter Rescue: Integrating Deep Learning With ROS2,” has been accepted to the 2024 IEEE World AI IoT Congress (AIIoT).
Dr. Valles’s collaboration paper with Faria Farzana, “Enhancing Pedestrian Safety: Predicting Movements With Deep Learning Models,” has been accepted for the 2024 IEEE World AI IoT Congress (AIIoT).
Dr. Valles’s collaboration paper, “Ultrasonic Frequency Anomaly Localization With Machine and Deep Learning,” with Evan Smith, Antonio Grahm, and Joni McCawley, has been accepted to the 2024 IEEE World AI IoT Congress (AIIoT).
