The team presented at the TXST Innovation Lab at SXSW 2022 for the Multimodal Emotion Recognition Solution for Children with ASD -Nurturing Neurodiversity APP
Author: Damian Valles
In the Newsroom
NSF grant establishes REU site for undergrad research into smart, connected communities, health. Newsroom: Texas State University:
Data Science Pathway Funded!
Happy to be part of the Faculty cohort from TXST in collaboration with Sam Houston State University in the development of a Data Analytics Certificate funded by the Texas Higher Education Coordinating Board
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.
Invited Talk!
Invited to present TXST’s project on Industry 4.0 Digital Twin to the Industry 4.0 – Strategies for Success! Virtual Seminar at CETYS University System in collaboration with American College of Thessaloniki. Coming in Feb. 2022!
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.
BEST PAPER AWARD
Best Paper Award at The 12th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (IEEE – UEMCON’21), Author: Md. Syadus Sefat, Co-Authors: Dr. Md. Shahjahan, Mahbubur Rahman, & Dr. Valles, New York, NY, USA, 2021.
Journal Article Accepted!
Dr. Valles’ co-authored collaborative journal article titled “Supervised Machine Learning in Inter-Level, Ultra-Low Frequency Power Line Communications” was accepted to the International Journal On Advances in Telecommunications, 2021, vol. 14, no. 1&2.
Journal Article Published!
Our collaborative journal article titled “An Initial Machine Learning-Based Victim’s Scream Detection Analysis for Burning Site” is now published on Appl. Sci. 2021, Volume 11, Issue 18, 8425.
