Publications

Peer-Reviewed Journals

  1. Ishola A. A., Valles D. Enhancing Safety and Efficiency in Firefighting Operations via Deep Learning and Temperature Forecasting Modeling in Autonomous UnitsSensors. 2023; 23(10):4628. https://doi.org/10.3390/s23104628
  2. Islam S. B., Valles D., Hibbitts T. J., Ryberg W. A., Walkup D. K., Forstner M. R. J. Animal Species Recognition with Deep Convolutional Neural Networks from Ecological Camera Trap ImagesAnimals. 2023; 13(9):1526. doi: 10.3390/ani13091526
  3. A. Sharotry, J. A. Jimenez, F. A. Méndez Mediavilla, D. Wierschem, R. M. Koldenhoven and D. Valles, “Manufacturing Operator Ergonomics: A Conceptual Digital Twin Approach to Detect Biomechanical Fatigue,” in IEEE Access, vol. 10, pp. 12774-12791, 2022, doi: 10.1109/ACCESS.2022.3145984.
  4. K. Thapa, S. McClellan, D. Valles. Supervised Machine Learning in Inter-Level, Ultra-Low Frequency Power Line Communications, International Journal On Advances in Telecommunications, ISSN: 1942-2601 vol. 14, no. 1 & 2, 2021, pp. 51:69, http://www.iariajournals.org/telecommunications/.
  5. Saeed, F.S.; Bashit, A.A.; Viswanathan, V.; Valles, D. An Initial Machine Learning-Based Victim’s Scream Detection Analysis for Burning SitesAppl. Sci. 202111, 8425. https://doi.org/10.3390/app11188425.
  6. Brake, N. A., & Sehin, O., & Partain, J. W., & Valles, D., & Marquez, A., & Jimenez, J. A., & Saltsman, G., & Davis, R. (2020, June), Crosscultural Engineering Skill Development at an International Engineering Summer Boot Camp, 2020 ASEE Virtual Annual Conference Content Access, doi: 10.18260/1-2–34357.
  7. McClellan, S., Valles, D., Koutitas, G. (2019). Dynamic Voltage Optimization Based on In-Band Sensors and Machine LearningAppl. Sci. 2019, 9(14), 2902; doi: 10.3390/app9142902.
  8. Valles, D., & McClellan, S. (2019). Using Machine Learning to Optimize Linux Networking. Linux Journal, May 2019 (Issue 298), pp. 128-138.

 


Case Studies

  1. E. Ellsworth, S. Rafiq, and D. Valles, “Saving lives while reducing first responder risks – with AI,” Dell Technologies/NVIDIA/Texas State University, September 2023. [Online]. Available: https://www.workstationguides.com/briefs/texasstateuniversity/
  2. D. Valles, “Democratizing access to data science boosts university’s research,” Dell Technologies/NVIDIA/Texas State University, September 2021. [Online]. Available: https://www.delltechnologies.com/asset/en-us/products/workstations/customer-stories-case-studies/texas-state-university-dell-dsw-case-study.pdf.

 


Peer-Reviewed Papers

2024

  1. N. C. Tran, I. X. Liang, T. Liu, and D. Valles, Impact of Virtual Reality on Motor Skill Performance in Children with Autism Spectrum Disorder, 2024 ASEE Annual Conference & Exposition. [Presenting in June]
  2. E. Smith, R. Koldenhoven, et al., “Development of an Augmented Reality Handwashing Tool for Children With Autism Spectrum Disorder,” 2024 IEEE 14th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, USA, 2024, pp. 0249-0256, doi: 10.1109/CCWC60891.2024.10427963.
  3. N. Pawar, S. Gujar, H. Dhonde, and D. Valles, “Early Prediction of Characteristic Compressive Strength of Concrete Based on Mix Proportions Using Modified Dimensional Analysis,” 2024 IEEE 14th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, USA, 2024, pp. 0043-0052, doi: 10.1109/CCWC60891.2024.10427830.

2023

  1. C. J. Woodman, A. Ridlon, C. J. Evelyn, A. Martinez and D. Valles, “Integrating machine learning and infrared smart cameras into critically endangered bird production,” 2023 IEEE 14th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), New York, NY, USA, 2023, pp. 0523-0527, doi: 10.1109/UEMCON59035.2023.10316121.
  2. D. Valles, G. Jackson, et al., “Data Collection and Real-Time Facial Emotion Recognition in iOS Apps With CNN-Based Models,” 2023 IEEE World AI IoT Congress (AIIoT), Seattle, WA, USA, 2023, pp. 0669-0677, doi: 10.1109/AIIoT58121.2023.10174520.
  3. M. Nooruddin, and D. Valles, “An Advanced IoT Framework for Long Range Connectivity and Secure Data Transmission Leveraging LoRa and ASCON Encryption,” 2023 IEEE World AI IoT Congress (AIIoT), Seattle, WA, USA, 2023, pp. 0583-0589, doi: 10.1109/AIIoT58121.2023.10174401. [Best Paper Award].
  4. S. Somvanshi, E. Zhu, K. Ikehata, D. Valles, and T. Jin, “Wind Speed Forecasting for Designing Sustainable Wastewater Treatment Plants,” 2023 13th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, USA, 2023, pp. 0844-0850, doi: 10.1109/CCWC57344.2023.10099313.
  5. S. Saha and D. Valles, “Forecast Analysis of Visibility for Airport Operations With Deep Learning Techniques,” 2023 13th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, USA, 2023, pp. 553-558, doi: 10.1109/CCWC57344.2023.10099100.
  6. D. Grimes and D. Valles, “Performance Analysis of TensorFlow2 Object Detection API Models for Engineering Site Surveillance Applications,” 2023 13th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, USA, 2023, pp. 0547-0552, doi: 10.1109/CCWC57344.2023.10099270.
  7. E. Alonso, D. Alonso, and D. Valles, “Classification Challenges and Analysis of Traffic Patterns for Highly Congested Areas in Central Texas,” 2023 13th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, USA, 2023, pp. 0382-0388, doi: 10.1109/CCWC57344.2023.10099316.

2022

  1. S. N. B. Tushar, S. Sarker, W. Stapleton, and D. Valles, “Peanut maturity classification by features extracted from selected hyperspectral components,” 2022 IEEE Global Humanitarian Technology Conference (GHTC 2022), Santa Clara, CA, USA, 2022, pp. 176-183, doi: 10.1109/GHTC55712.2022.9911049.
  2. M. Rahman, A. Haque, D. Pujara, J. Mayorga, H. Kang, and D. Valles, “Automation of Luminescence Quantitation for High-Throughput Plant Phenotyping Using Image Processing and U-Net Segmentation,” The 26th International Conference on Image Processing, Computer Vision, & Pattern Recognition (IPCV’22), [In Press].
  3. A. Ishola, and D. Valles, “Using Machine Learning and Regression Analysis to Classify and Predict Danger Levels in Burning Sites,” 2022 IEEE World AI IoT Congress (AIIoT), 2022, pp. 453-459, doi: 10.1109/AIIoT54504.2022.9817232.

2021

  1. M. S. Sefat, M. Shahjahan, M. Rahman, and D. Valles, “Ensemble Training with Classifiers Selection Mechanism,” 2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), 2021, pp. 0131-0136, doi: 10.1109/UEMCON53757.2021.9666676, [Best Paper Award].
  2. T. G. Paveglio and D. Valles, “Second Sight: MobileNet v1 Integration in Dynamic and Time Critical Scenarios,” 2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON), 2021, pp. 0378-0384, doi: 10.1109/IEMCON53756.2021.9623152.
  3. H. Alam and D. Valles, “Debris Object Detection Caused by Vehicle Accidents Using UAV and Deep Learning Techniques,” 2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON), 2021, pp. 1034-1039, doi: 10.1109/IEMCON53756.2021.9623110.
  4. D. Valles and R. Matin, “An Audio Processing With Ensemble Learning Approach for Speech-Emotion Recognition for Children With ASD,” 2021 IEEE World AI IoT Congress (AIIoT), 2021, pp. 0055-0061, doi: 10.1109/AIIoT52608.2021.9454174.
  5. U. K. K. Pillai and D. Valles, “An Initial Deep CNN Design Approach for Identification of Vehicle Color and Type for Amber and Silver Alerts,” 2021 IEEE 11th Annual Computing and Communication Workshop and Conference (CCWC), NV, USA, 2021, pp. 0903-0908, doi: 10.1109/CCWC51732.2021.9375917.

2020

  1. M. Hernandez, D. Valles, et al., “An Initial Julia Simulation Approach to Material Handling Operations from Motion Captured Data,” 2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON), Vancouver, BC, 2020, pp. 0718-0722, doi: 10.1109/IEMCON51383.2020.9284829.
  2. S. Islam, D. Valles and M. R. J. Forstner, “Performance Analysis and Evaluation of LSTM and GRU Architectures for Houston toad and Crawfish frog Call Detection,” 2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), New York City, NY, 2020, pp. 0106-0111, doi: 10.1109/UEMCON51285.2020.9298170.
  3. P. Sharma and D. Valles, “Backbone Neural Network Design of Single Shot Detector from RGB-D Images for Object Detection,” 2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), New York City, NY, 2020, pp. 0112-0117, doi: 10.1109/UEMCON51285.2020.9298175.
  4. T. Caroll, G. Hernandez, G. Koutitas, D. Wierschem, F. Mendez, D. Valles, S. Aslan, R. Koldenhoven, and J. Jimenez, “Comparison of Inverse Kinematics Algorithms for Digital Twin Industry 4.0 Applications,” 2020  IEEE International Conference on Systems, Man, and Cybernetics (IEEE-SMC 2020), Toronto, ON, 2020, pp. 3319-3326, doi: 10.1109/SMC42975.2020.9283253.
  5. U. K. K. Pillai and D. Valles, “Vehicle Type and Color Classification and Detection for Amber and Silver Alert Emergencies Using Machine Learning,” 2020 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS), Vancouver, BC, Canada, 2020, pp. 1-5, doi: 10.1109/IEMTRONICS51293.2020.9216368.
  6. A. Sharotry, J. Jimenez, D. Wierschem, F. Mendez, G. Koutitas, D. Valles, S. Aslan, R.M. Koldenhoven, “A Digital Twin Framework for Real-Time Analysis and Feedback of Repetitive Work in the Manual Material Handling Industry,” 2020 Winter Simulation Conference (WSC), Orlando, FL, USA, 2020, pp. 2637-2648, doi: 10.1109/WSC48552.2020.9384043.
  7. S. B. Islam, D. Valles, and M. R. J. Forstner, “Herpetofauna Species Classification from Images with Deep Neural Network,” 2020 Intermountain Engineering, Technology and Computing (IETC), Orem, UT, USA, 2020, pp. 1-6, doi: 10.1109/IETC47856.2020.9249141.
  8. S. Islam, D. Valles and M. R. J. Forstner, “A Houston Toad Call Detection Initial Approach Using Gated Recurrent Units for Conservational Efforts,” 2020 Intermountain Engineering, Technology and Computing (IETC), Orem, UT, USA, 2020, pp. 1-6, doi: 10.1109/IETC47856.2020.9249158.
  9. R. Matin and D. Valles, “A Speech Emotion Recognition Solution-based on Support Vector Machine for Children with Autism Spectrum Disorder to Help Identify Human Emotions,” 2020 Intermountain Engineering, Technology and Computing (IETC), Orem, UT, USA, 2020, pp. 1-6, doi: 10.1109/IETC47856.2020.9249147.
  10. A. Sharotry, J. Jimenez, D. Wierschem, F. Mendez, G. Koutitas, D. Valles, S. Aslan, R.M. Koldenhoven, “A Digital Twin Framework of a Material Handling Operator in Industry 4.0 Environments,” International Conference on Information Systems, Logistics & Supply Chain (ILS) 2020.
  11. G. Hernandez, D. Valles, D. Wierschem, R.M. Koldenhoven, G. Koutitas, F. Mendez,  S. Aslan, J. Jimenez, “Machine Learning Techniques for Motion Analysis of Fatigue from Manual Material Handling Operations Using 3D Motion Capture Data,” 2020 10th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, USA, 2020, pp. 0300-0305, doi:10.1109/CCWC47524.2020.9031222
  12. S. B. Islam and D. Valles, “Identification of Wild Species in Texas from Camera-trap Images using Deep Neural Network for Conservation Monitoring,” 2020 10th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, USA, 2020, pp. 0537-0542, doi:10.1109/CCWC47524.2020.9031190
  13. S. Islam and D. Valles, “Houston Toad and Other Chorusing Amphibian Species Call Detection Using Deep Learning Architectures,” 2020 10th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, USA, 2020, pp. 0511-0516, doi:10.1109/CCWC47524.2020.9031223
  14. D. Johnson and D. Valles, “A Non-Linear GPU Performance Modeling Approach and Consolidated Linear Hardware Model Performance Evaluation of the LEAP Cluster,” 2020 10th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, USA, 2020, pp. 0517-0523, doi:10.1109/CCWC47524.2020.9031282
  15. F. B. Jaradat and D. Valles, “A Victims Detection Approach for Burning Building Sites Using Convolutional Neural Networks,” 2020 10th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, USA, 2020, pp. 0280-0286, doi:10.1109/CCWC47524.2020.9031275
  16. P. Sharma and D. Valles, “Deep Convolutional Neural Network Design Approach for 3D Object Detection for Robotic Grasping,” 2020 10th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, USA, 2020, pp. 0311-0316, doi:10.1109/CCWC47524.2020.9031186

2019

  1. M. I. Ul Haque and D. Valles, “Facial Expression Recognition Using DCNN and Development of an iOS App for Children with ASD to Enhance Communication Abilities,” 2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), New York City, NY, USA, 2019, pp. 0476-0482. doi: 10.1109/UEMCON47517.2019.8993051.
  2. A. A. Bashit, D. Valles, “MFCC based Houston Toad call Detection using LSTM,” 2019 IEEE International Symposium on Measurement and Control in Robotics (ISMCR), Houston, TX, USA, 2019, pp. D3-3-1-D3-3-6. doi: 10.1109/ISMCR47492.2019.8955667.
  3. D. A. Johnson, D. Valles, “A Linear Approach to Network Performance Modeling and a Consolidation of Linear Performance Models of the LEAP Cluster,” The 2019 World Congress in Computer Science, Computer Engineering, & Applied Computing –The 17th International Conference on Scientific Computing (CSCE-CSC’19), Las Vegas, NV, 2019, pp. 132-135, ISBN: 1-60132-494-4.
  4. B. DasGupta, D. Valles, S. McClellan, “Estimating TCP RTT with LSTM Neural Networks,” The 2019 World Congress in Computer Science, Computer Engineering, & Applied Computing – The 21st International Conference on Artificial Intelligence (CSCE-ICAI’19), Las Vegas, NV, 2019, pp. 192-198, ISBN: 1-60132-501-0.

2018

  1. A. A. Bashit, D. Valles, “Solar Powered Raspberry Pi-based Cellular Modem Integrated Real-time Houston Toad Calls Detection System Design using Neural Network Trained Model,” The 5th Annual Conference on Computational Science & Computational Intelligence – Symposium on Internet of Things & Internet of Everything (CSCI-ISOT’18), Las Vegas, NV, 2018, pp. 1024-1027, doi:10.1109/CSCI46756.2018.00198.
  2. A. Pinales, D. Valles, “AESV Integration of IMU and Implementation of Interleaved Data Acquisition and Transmission Method,” The 5th Annual Conference on Computational Science & Computational Intelligence – Symposium on Smart Cities and Smart Mobility (CSCI-ISSC’18), Las Vegas, NV, 2018, pp. 541-544, doi:10.1109/CSCI46756.2018.00110.
  3. F. Jaradat, D. Valles, “A Human Detection Approach for Burning Building Sites Using Deep Learning Techniques,” The 5th Annual Conference on Computational Science & Computational Intelligence – Symposium on Computational Intelligence (CSCI-ISCI’18), Las Vegas, NV, 2018, pp 1434-1435, doi:10.1109/CSCI46756.2018.00277.
  4. B. DasGupta, D. Valles, S. McClellan, “A Comparison of MLA Techniques for Classification of Network Bandwidth Loss,” The 5th Annual Conference on Computational Science & Computational Intelligence – Symposium on Mobile Computing, Wireless Networks, & Security (CSCI-ISMC’18), Las Vegas, NV, 2018, pp. 771-775, doi: 10.1109/CSCI46756.2018.00155.
  5. M. I. Haque, D. Valles, “Facial Expression Recognition from Different Angles Using DCNN for Autistic Children to Recognize Emotional Patterns,” The 5th Annual Conference on Computational Science & Computational Intelligence – Symposium on Signal & Image Processing, Computer Vision & Pattern Recognition (CSCI-ISPC’18), Las Vegas, NV, 2018, pp. 446-449, doi:10.1109/CSCI46756.2018.00090.
  6. D. Johnson, D. Valles, “An Initial Scale-Factor Linear Polynomial Regression Model Approach for Hardware Performance on an HPC Compute-Node,” The 9th IEEE Annual Information Technology, Electronics & Mobile Communication Conference (IEMCON’18), Vancouver, Canada, 2018, pp. 661-666, doi:10.1109/IEMCON.2018.8614937.
  7. B. DasGupta, D. Valles, S. McClellan “A K-Means Algorithm Approach for Classifying Wireless Signal Loss Using RTT and Bandwidth,” The 9th IEEE Annual Information Technology, Electronics & Mobile Communication Conference (IEMCON’18), Vancouver, Canada, 2018,  pp. 160-165, doi:10.1109/IEMCON.2018.8615015. [Best Paper Award].
  8. A. Pinales, D. Valles, “Autonomous Embedded System Vehicle Design on Environmental, Mapping and Human Detection Data Acquisition for Firefighting Situations,” The 9th IEEE Annual Information Technology, Electronics & Mobile Communication Conference (IEMCON’18), Vancouver, Canada, 2018, pp. 194-198, doi:10.1109/IEMCON.2018.8615022.
  9. M. I. Haque, D. Valles, “A Facial Expression Recognition Approach using DCNN for Autistic Children to Identify Emotions,” The 9th IEEE Annual Information Technology, Electronics & Mobile Communication Conference (IEMCON’18), Vancouver, Canada, 2018, pp. 546-551, doi:10.1109/IEMCON.2018.8614802.
  10. A. A. Bashit, D. Valles, “A Mel-Filterbank and MFCC-based Neural Network Approach to Train the Houston Toad Call Detection System Design,” The 9th IEEE Annual Information Technology, Electronics & Mobile Communication Conference (IEMCON’18), Vancouver, Canada, 2018, pp. 438-443, doi:10.1109/IEMCON.2018.8615076.
  11. F. Jaradat, D. Valles, “An Exponential Smoothing Embedded System Approach to Dangerous Temperature Detection for Firefighter Safety,” The 16th Int’l Conf on Embedded Systems, Cyber-physical Systems, and Applications (ESCS’18), Las Vegas, NV, 2018, pp. 41-44, ISBN: 1-60132-475-8.
  12. A. A. Bashit, D. Valles, “An Embedded Approach for Controlling Automatic Water Pump and Monitoring Real-Time Remote Data on Desktop, Android, and Web-based Application,” The 16th Int’l Conf on Embedded Systems, Cyber-physical Systems, and Applications (ESCS’18), Las Vegas, NV, 2018, pp. 33-36. ISBN: 1-60132-475-8.
  13. N. Azami, D. Valles, “An Electrical Vehicle Charging Station Monitoring Embedded Design,” The 16th Int’l Conf on Embedded Systems, Cyber-physical Systems, and Applications (ESCS’18), Las Vegas, NV, 2018, pp. 58-61, ISBN: 1-60132-475-8.
  14. M. I. U. Haque, D. Valles, “Design of a Sensor-Based Adaptive Smart Home System using ARM Cortex-M3,” The 16th Int’l Conf on Embedded Systems, Cyber-physical Systems, and Applications (ESCS’18), Las Vegas, NV, 2018, pp. 22-25, ISBN: 1-60132-475-8.
  15. M.U. Jewel, B. DasGupta, D. Valles, “Gas and Air Quality Detection, Monitoring, and Alerting Using Embedded System for Nanofabrication Facility,” The 16th Int’l Conf on Embedded Systems, Cyber-physical Systems, and Applications (ESCS’18), Las Vegas, NV, 2018, pp. 45-48, ISBN: 1-60132-475-8.
  16. B. DasGupta, D. Valles, “IP Packet Loss and RTT Calculation Simulation Using Low-Cost Embedded Real-Time Systems,” The 16th Int’l Conf on Embedded Systems, Cyber-physical Systems, and Applications (ESCS’18), Las Vegas, NV, 2018, pp. 54-57, ISBN: 1-60132-475-8.
  17. Freedman, R. J., Valles, D., “A Communication Benchmark Tailored to Intel Broadwell Nodes and Tuned to the DEAC Cluster,The 8th IEEE Annual Computing and Communication Workshop and Conference (CCWC’18), Las Vegas, NV, 2018, pp.502-508, doi:10.1109/CCWC.2018.8301671. [Best Paper Award].

2017

  1. Valles D., Apple, M.E., Andrews, C., “Visual Simulations Correlate Plant Functional Trait Distribution with Elevation and Temperature in the Cairngorm Mountains of Scotland,International Symposium on Computation Biology (CSCI-ISCB’17), Las Vegas, Nevada, 2017, pp.1252-1258, doi:10.1109/CSCI.2017.220.

 

 

 

 

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