Tony Tran
Research / Teaching Assistant · NAIL Lab · University of Houston
122 ENGR4 (SAB2)
14000 University Blvd
Sugar Land, TX 77479
Tony Tran is a Machine Learning Engineer and Research / Teaching Assistant at the University of Houston. He earned his Bachelor’s degree in Computer Engineering Technology and is currently pursuing his Master’s degree in Engineering Data Science and AI (thesis track) under Dr. Bin Hu.
His research focuses on TinyML and hardware-aware neural architecture search for AI model deployment on resource-constrained devices through model compression techniques (pruning, quantization). He is especially interested in efficient edge vision (classification, detection, segmentation), model inference optimization, and robust neural networks.
He has a passion for technology, education, and the environment.
📍 Cullen College of Engineering · University of Houston
News
2026
| April 2026 | 🎉 I successfully defend my thesis, Efficient Iterative Neural Architecture Search for Object Detection on IoT Devices, advised by Professor Bin Hu in the Networked Autonomous Intelligent Learning (NAIL) Lab, with research focus on efficient TinyML and Embedded AI. [Slides] |
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| March 2026 | 🎉 Our paper ELASTIC: Efficient Once For All Iterative Search for Object Detection on Microcontrollers has been accepted by IEEE Transactions on Computers! [Paper] [arXiv] [Code] |
| March 2026 | 🎉 Our project Heterogeneous Multi-Robot Waste Detection with Conformal Runtime Monitoring has been selected for the NVIDIA Academic Grant Program! In support of our project, NVIDIA is donating 4× RTX PRO 6000 Blackwell Max-Q Workstation Edition and 2× Jetson AGX Orin Dev Kit to the University of Houston. We are grateful to NVIDIA for their generous support of academic research and innovation. |
| March 2026 | 📄 I present TrashDet: Iterative Neural Architecture Search for Efficient Waste Detection at the WASTEVISION: International Workshop on Smart Waste Monitoring at The IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2026, Tucson, USA. [Paper] [Slides] [Video] |
2025
| December 2025 | 🎉 Our paper TrashDet: Iterative Neural Architecture Search for Efficient Waste Detection has been accepted for presentation at the WASTEVISION: International Workshop on Smart Waste Monitoring at The IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2026. [Paper] |
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