Research

Research Topics

  • High-Performance Computing (HPC)
  • Machine/Deep/Reinforced Learning
  • Embedded Edge-Systems
  • Virtual/Augmented Reality (XR)
  • Robotics

Director – HiPE Research Group:

PI Faculty Mentor of NSF-REU Site:

PI Faculty Member, TXST CADS Research Center:

Co-PD USDA AnimalCareBot Project:

 

Peer-Review Journals Articles

  1. Ishola A. A., Valles D. Enhancing Safety and Efficiency in Firefighting Operations via Deep Learning and Temperature Forecasting Modeling in Autonomous Units. Sensors. 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 Images. Animals. 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 Sites. Appl. Sci. 2021, 11, 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), Cross-cultural 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 Learning. Appl. 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-Review Conference Papers

  1. G. Jackson and D. Valles, “Dataset Enlargement With Generative Adversarial Neural Networks,” 2024 IEEE World AI IoT Congress (AIIoT). [Presenting in May]
  2. S. Hossain and D. Valles, “Traffic Safety Through Machine Learning: A Study of Crash Severity Factors,” 2024 IEEE World AI IoT Congress (AIIoT). [Presenting in May]
  3. S. A. Rafiq, E. S. Ellsworth, D. Valles, et al., “Design of Autonomous Rover for Firefighter Rescue: Integrating Deep Learning With ROS2,” 2024 IEEE World AI IoT Congress (AIIoT). [Presenting in May]
  4. F. Farzana and D. Valles, “Enhancing Pedestrian Safety: Predicting Movements With Deep Learning Models,” 2024 IEEE World AI IoT Congress (AIIoT). [Presenting in May]
  5. E. Smith, A. T. Grahm, J. E. McCawley, and D. Valles, “Ultrasonic Frequency Anomaly Localization With Machine and Deep Learning,” 2024 IEEE World AI IoT Congress (AIIoT). [Presenting in May]
  6. D. Shrestha and D. Valles, “Evolving Autonomous Navigation: A NEAT Approach for Firefighting Rover Operations in Dynamic Environments,” 24th Annual IEEE International Conference on Electro Information Technology (EIT2024). [Presenting in May]
  7. 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]
  8. E. Smith, R. Koldenhoven, D. Valles, 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.
  9. 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.
  10. 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.
  11. D. Valles 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.
  12. 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].
  13. 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.
  14. 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.
  15. 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.
  16. 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.
  17. 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.
  18. 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].
  19. 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.
  20. 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].
  21. 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.
  22. 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.
  23. 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.
  24. 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.
  25. 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.
  26. 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.
  27. 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.
  28. 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.
  29. 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.
  30. 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.
  31. 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.
  32. 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.
  33. 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.
  34. 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.
  35. 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, Nevada, USA, 2020, pp. 0300-0305, doi:10.1109/CCWC47524.2020.9031222
  36. S. B. Islam, 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, Nevada, USA, 2020, pp. 0537-0542, doi:10.1109/CCWC47524.2020.9031190
  37. S. Islam, 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, Nevada, USA, 2020, pp. 0511-0516, doi:10.1109/CCWC47524.2020.9031223
  38. D. Johnson, 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, Nevada, USA, 2020, pp. 0517-0523, doi:10.1109/CCWC47524.2020.9031282
  39. F. Jaradat, 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, Nevada, USA, 2020, pp. 0280-0286, doi:10.1109/CCWC47524.2020.9031275
  40. P. Sharma, 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, Nevada, USA, 2020, pp. 0311-0316, doi:10.1109/CCWC47524.2020.9031186
  41. 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, New York, USA, 2019, pp. 0476-0482. doi: 10.1109/UEMCON47517.2019.8993051.
  42. A. A. Bashit, D. Valles, “MFCC based Houston Toad call Detection using LSTM,”  2019 IEEE International Symposium on Measurement and Control in Robotics (IEEE-ISMCR). Houston, Texas, USA, 2019, pp. D3-3-1-D3-3-6. doi:10.1109/ISMCR47492.2019.8955667.
  43. D. A. Johnson, D. Valles, “A Linear Approach to Network Performance Modeling and a Consolidation of Linear Performance Models of the LEAP Cluster,” 2019 World Congress in Computer Science, Computer Engineering, & Applied Computing – 17th International Conference on Scientific Computing (CSCE-CSC’19), Las Vegas, Nevada, 2019, pp. 132-135, ISBN:1-60132-494-4.
  44. B. DasGupta, D. Valles, S. McClellan, “Estimating TCP RTT with LSTM Neural Networks,” 2019 World Congress in Computer Science, Computer Engineering, & Applied Computing – 21st International Conference on Artificial Intelligence (CSCE-ICAI’19), Las Vegas, Nevada, 2019, pp. 192-198, ISBN:1-60132-501-0.
  45. A. A. Bashit, D. Valles, “A Solar Powered Raspberry Pi-based Cellular Modem Integrated Real-time Houston Toad Calls Detection System Design using Neural Network Trained Model,” 5th Annual Conference on Computational Science & Computational Intelligence – Symposium on Internet of Things & Internet of Everything (CSCI-ISOT’18), Las Vegas, Nevada, 2018, pp. 1024-102, doi:10.1109/CSCI46756.2018.001987
  46. A. Pinales, D. Valles, “AESV Integration of IMU and Implementation of Interleaved Data Acquisition and Transmission Method,” 5th Annual Conference on Computational Science & Computational Intelligence – Symposium on Smart Cities and Smart Mobility (CSCI-ISSC’18), Las Vegas, Nevada, 2018, pp. 541-544, doi:10.1109/CSCI46756.2018.00110
  47. F. Jaradat, D. Valles, “A Human Detection Approach for Burning Building Sites Using Deep Learning Techniques,” 5th Annual Conference on Computational Science & Computational Intelligence – Symposium on Computational Intelligence (CSCI-ISCI’18), Las Vegas, Nevada, 2018, pp 1434-1435, doi:10.1109/CSCI46756.2018.00277
  48. B. DasGupta, D. Valles, S. McClellan, “A Comparison of MLA Techniques for Classification of Network Bandwidth Loss,” 5th Annual Conference on Computational Science & Computational Intelligence – Symposium on Mobile Computing, Wireless Networks, & Security (CSCI-ISMC’18), Las Vegas, Nevada, 2018, pp. 771-775, doi:10.1109/CSCI46756.2018.00155
  49. M. I. Haque, D. Valles, “Facial Expression Recognition from Different Angles Using DCNN for Autistic Children to Recognize Emotional Patterns,” 5th Annual Conference on Computational Science & Computational Intelligence – Symposium on Signal & Image Processing, Computer Vision & Pattern Recognition (CSCI-ISPC’18), Las Vegas, Nevada, 2018, pp. 446-449, doi:10.1109/CSCI46756.2018.00090
  50. D. Johnson, D. Valles, “An Initial Scale-Factor Linear Polynomial Regression Model Approach for Hardware Performance on an HPC Compute-Node,” 9th IEEE Annual Information Technology, Electronics & Mobile Communication Conference (IEMCON’18), Vancouver, Canada, 2018, pp. 661-666, doi:10.1109/IEMCON.2018.8614937
  51.  B. DasGupta, D. Valles, S. McClellan “A K-Means Algorithm Approach for Classifying Wireless Signal Loss Using RTT and Bandwidth,” 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].
  52.  A. Pinales, D. Valles, “Autonomous Embedded System Vehicle Design on Environmental, Mapping and Human Detection Data Acquisition for Firefighting Situations,“ 9th IEEE Annual Information Technology, Electronics & Mobile Communication Conference (IEMCON’18), Vancouver, Canada, 2018, pp. 194-198, doi:10.1109/IEMCON.2018.8615022.
  53.  M. I. Haque, D. Valles, “A Facial Expression Recognition Approach using DCNN for Autistic Children to Identify Emotions,” 9th IEEE Annual Information Technology, Electronics & Mobile Communication Conference (IEMCON’18), Vancouver, Canada, 2018, pp. 546-551, doi:10.1109/IEMCON.2018.8614802
  54. A. A. Bashit, D. Valles, “A Mel-Filterbank and MFCC-based Neural Network Approach to Train the Houston Toad Call Detection System Design,” 9th IEEE Annual Information Technology, Electronics & Mobile Communication Conference (IEMCON’18), Vancouver, Canada, 2018, pp. 438-443, doi: 10.1109/IEMCON.2018.8615076.
  55. F. Jaradat, D. Valles, “An Exponential Smoothing Embedded System Approach to Dangerous Temperature Detection for Firefighter Safety,” 16th Int’l Conf on Embedded Systems, Cyber-physical Systems, and Applications (ESCS’18), Las Vegas, Nevada, 2018, pp. 41-44, ISBN: 1-60132-475-8.
  56. 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,” 16th Int’l Conf on Embedded Systems, Cyber-physical Systems, and Applications (ESCS’18), Las Vegas, Nevada, 2018, pp. 33-36, ISBN: 1-60132-475-8.
  57. N. Azami, D. Valles, “An Electrical Vehicle Charging Station Monitoring Embedded Design,” 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.
  58. M. I. U. Haque, D. Valles, “Design of a Sensor-Based Adaptive Smart Home System using ARM Cortex-M3,” 16th Int’l Conf on Embedded Systems, Cyber-physical Systems, and Applications (ESCS’18), Las Vegas, Nevada, 2018, pp. 22-25, ISBN: 1-60132-475-8.
  59. M.U. Jewel, B. DasGupta, D. Valles, “Gas and Air Quality Detection, Monitoring, and Alerting Using Embedded System for Nanofabrication Facility,” 16th Int’l Conf on Embedded Systems, Cyber-physical Systems, and Applications (ESCS’18), Las Vegas, Nevada, 2018, pp. 45-48, ISBN: 1-60132-475-8.
  60. B. DasGupta, D. Valles, “IP Packet Loss and RTT Calculation Simulation Using Low-Cost Embedded Real-Time Systems,” 16th Int’l Conf on Embedded Systems, Cyber-physical Systems, and Applications (ESCS’18), Las Vegas, Nevada, 2018, pp. 54-57, ISBN: 1-60132-475-8.
  61. Freedman, R. J., Valles, D., “A Communication Benchmark Tailored to Intel Broadwell Nodes and Tuned to the DEAC Cluster,” 8th IEEE Annual Computing and Communication Workshop and Conference (CCWC’18), UNLV, Las Vegas, Nevada, pp.502-508, doi:10.1109/CCWC.2018.8301671, [Best Paper Award].
  62. 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
  63. Freedman, R. J., Valles, D., “A Modeling Approach to Hardware Analysis of the Heterogeneous DEAC Cluster,” International Symposium on Parallel and Distributed Computing and Computational Science (CSCI-ISPD’17), Las Vegas, Nevada, 2016, pp.1408-1409, doi:10.1109/CSCI.2016.0272.
  64. Valles, D., Apple, M.E., Dick, J., Andrews, C., Gutierrez-Giron, A., and Pauli, H., “Modeling Plant Functional Traits and Elevation in the Cairngorm Mountains of Scotland,” International Conference on Modeling, Simulation and Visualization Methods (MSV’15), Las Vegas, Nevada, 2015.
  65. Valles D., “A Numerical Modeling MATLAB Approach to Memory Behavior on a Multi-core Architecture on a Beowulf Cluster Single-Node,” International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA’13), Las Vegas, Nevada, 2013.
  66. Valles D., Williams D., Nava P., “Scheduling Modifications for Improvement Performance on a Beowulf Cluster Single-Node,” International Conference on Computer Applications in Industry and Engineering (CAINE’12), New Orleans, Louisiana, 2012.
  67. Valles D., Williams D., Nava P., “Load Balancing Approach Based on Limitations and Bottlenecks of Multi-core Architectures on a Beowulf Cluster Compute-Node,” International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA’12), Las Vegas, Nevada, 2012.

  68. Valles D., Williams D., Nava P., “Performance and Timing Measurements in a Multi-core Beowulf Cluster Compute-Node,” International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA’09), Las Vegas, Nevada, 2009.

Posters

  1. A. Lopez, D. Valles, and M. Drewery, “Monitoring Cattle Behavior and Health Using Artificial Intelligence and Thermography,” The 2024 TXST STEM Conference, Texas State University, San Marcos, TX, 2024.
  2. G. Jackson, and D. Valles, “Dataset Enlargement with Generative Adversarial Neural Network,” The 2024 TXST STEM Conference, Texas State University, San Marcos, TX, 2024.
  3. D. Hall, and D. Valles, “Emotion Recognition and Communication Assistance: A Machine Learning App for Children with Autism,” The 2024 TXST STEM Conference, Texas State University, San Marcos, TX, 2024.
  4. T. Liu, I. Wallace, H. Cressman, D. Valles, et al., “Enhancing Early Diagnosis of Autism Spectrum Disorder with Machine Learning Algorithms Using Postural Control Features” 2024 International Society of Research and Advocacy for Development Coordination Disorder and the International Motor Development Research Consortium (DCD15-IMDRC6), Ghent, Belgium, 2024.
  5. D. Valles, “Autonomous Innovation: Revolutionizing Urban Firefighting with Data and Artificial Intelligence,” The 2024 Health Scholar Showcase, Texas State University, San Marcos, TX, 2024.
  6. Hernandez, A. L., Resendiz, M. D., Valles, D., et. al (2023, Oct). Is there gender bias in emotion identification? 2023 SACNAS National Diversity in STEM (NDiSTEM) Conference, Portland, OR, USA, 2023 [To be presented in October].
  7. Liu, T., Mohammed, H., & Valles, D. (2023, May). Virtual reality effectiveness on motor assessment in children with autism. In JOURNAL OF SPORT & EXERCISE PSYCHOLOGY (Vol. 45, pp. S19-S19). 1607 N MARKET ST, PO BOX 5076, CHAMPAIGN, IL 61820-2200 USA: HUMAN KINETICS PUBL INC.
  8. J. McCawley, G. Taverna, and D. Valles, “Emotion Recognition using Audio Input for Voice and Environmental Sounds,” The 2nd Annual Texas State University Data Analytics Showcase, San Marcos, TX, 2023.
  9. S. Rafiq, E. Ellsworth, and D. Valles, “Smart City Firefighting Autonomous Data Collection,” The 2nd Annual Texas State University Data Analytics Showcase, San Marcos, TX, 2023.
  10. G. Jackson, D. Hall, and D. Valles, “Face Emotion Recognition DL Development and App Adaptability,” The 2nd Annual Texas State University Data Analytics Showcase, San Marcos, TX, 2023.
  11. A. L. Hernandez, S. Valenzuela, A. E. Quiñonez Camacho, L. A. Umali, R. Newcomb, D. Valles, M. Resendiz, “Inclusion of Diverse Participants in Development of Emotion Portrayal Database,” The 2023 TXST STEM Conference, Texas State University, San Marcos, TX, 2023.
  12. D. Valles, M. Resendiz, “A Facial Expression Recognition Application Using Machine Learning for Children with ASD to Help Identify Emotions,” The 2022 Health Scholar Showcase, Texas State University, San Marcos, TX, 2022.
  13. T. Stapleton, R. Fuentes, S. R. Jeter, R. Rolfe, D. Knudson, D. Valles, and F. Mendez, “Development of an Artificial Intelligence System to Prevent Overexertion Injuries at the Workplace,” American Statistical Association Conference on Statistical Practice 2022, New Orleans, LA, 2021. [1st Place Excellence in the Student Poster Competition]
  14. Stewart, A., Resendiz, M., Valles, D., Haque, I., and Matin, R. (2020, November). 11638: Emotions and Emoticons: Facial Expression Recognition App for Individuals with Autism Spectrum Disorder (ASD). Proposal accepted at the Annual Convention of the American Speech-Language-Hearing Association, San Diego, CA.
  15. Uma K. K. Pillai, D. Valles, “Vehicle Colors and Types Detection for Amber and Silver Alert Emergencies Using Machine Learning,” Women in Science and Engineering (WiSE) Annual Conference, Texas State University, San Marcos, TX, 2020.
  16. D. Liu, Z. Dong, D. Valles, “Exploring the Contagion Effect of Social Media on Mass Shootings,” Women in Science and Engineering (WiSE) Annual Conference, Texas State University, San Marcos, TX, 2020.
  17. D. Valles, M. Resendiz, M.I.U. Haque, “A Facial Expression Recognition Application Using Machine Learning for Children with ASD to Help Identify Emotions,” The 2019 Health Scholar Showcase, Texas State University, San Marcos, TX, 2019.
  18. M. Apple, D. Valles, “The RAPT Model Predicts Resilience and Vulnerability of Boreal Plant Species to Climate Change in the Cairngorm Mountains of Scotland,” The 2018 AGU Fall Meeting, Washington, D.C., 2018.
  19. F. Jaradat, D. Valles, “A Human Detection Approach for Burning Building Sites Using Deep Learning Techniques,” 5th Annual Conference on Computational Science & Computational Intelligence – Symposium on Computational Intelligence (CSCI-ISCI’18), Las Vegas, NV, 2018.
  20. David A.S. Johnson, D. Valles, “Modeling of High-Performance Computing Servers using Analysis of Benchmarks,” 2018 SACNAS – The National Diversity in STEM Conference, San Antonio, TX, 2018.
  21. A.  Pinales, D. Valles, “Autonomous Embedded System Design on Environmental, Mapping and Human Detection Data Acquisition for Firefighting Situations,” 2018 SACNAS – The National Diversity in STEM Conference, San Antonio, TX, 2018
  22. David A.S. Johnson, D. Valles, “Performance Modeling High-End Servers Using Benchmark Analysis,” TECHCON 2018, Austin, TX, 2018.
  23. David A.S. Johnson, D. Valles, “Modelling of High-Performance Computing Servers using Analysis of Benchmarks,” 2018 Women in Science and Engineering (WiSE) Annual Conference, Texas State University, San Marcos, TX, 2018.