I am
Name: Quan Tran
Profile: CS Student Specializing in Computer Vision
Email: qmt1@rice.edu
Phone: (281)-690-6463
Skills
About me
Hi, I'm Quan Tran, a Computer Science student at Rice University with a focus on backend systems, data infrastructure, and applied machine learning. Through internships at HP, VNG Cloud, and the Rice Computer Vision Lab, I've gained experience building robust software—from a Python-based automation framework integrated into Jenkins pipelines, to an online-learning anomaly detection system deployed on live cloud traffic, to full-stack tools for evaluating object-tracking models. My work spans scalable system design, data processing, and real-time performance optimization across both industry and academic settings.
Outside of internships, I've led and contributed to several technical projects that reflect my range and initiative. These include a real-time messaging app with a custom Go-based backend, a NoSQL database with RESTful APIs and concurrency support, and a gesture-tracking productivity tool powered by computer vision. I've also explored embedded systems and sensor fusion for exoskeleton control and managed cloud databases and caching layers for large-scale applications. I enjoy tackling complex technical challenges and turning ideas into efficient, well-structured solutions.
Resume
View my resumeSummary
Quan Tran
Computer science student with experience in backend systems, data infrastructure, and applied machine learning, seeking a Software Engineering role to build scalable, reliable, and impactful products.
- Houston, Texas
- (281)-690-6463
- qmt1@rice.edu
Education
B.S. in Computer Science
2022 - Present
Rice University, Houston, Texas
GPA: 3.8/4.0
Professional Experience
Computer Vision Research Intern - Rice University Computer Vision Lab
May 2025 - Present
Houston, Texas
- Built a full-stack annotation tool with JavaScript front end and Python backend (Flask, OpenCV) to evaluate rigid object tracking performance
- Enabled dynamic point and line selection, real-time track visualization, and seamless integration with models such as CoTracker3 and PIPs++
- Designed backend architecture for loading video data, managing tracker configuration, and multi-model support
- Benchmarked state-of-the-art trackers through both visual analysis and quantitative metrics to identify edge cases and performance bottlenecks
- Currently working on fine-tuning and training models for test-time optimization to improve rigid shape tracking on unseen data
Software Engineer Intern - HP/Poly
May 2024 - August 2024
Austin, Texas
- Developed an end-to-end Python framework using Zoom Rest API for automated testing, enabling Zoom Rooms configurations before and after testing to validate and certify software for Zoom
- Integrated the framework with the current Jenkins pipelines for minimal configurations when setting up and creating new test cases
- Collected and benchmarked Quality of Service data to evaluate live video performance in real-time test environments
- Refactored legacy codebase to double data retrieval speed and improve API efficiency
Software Engineer Intern - VNG Cloud
May 2023 - August 2023
Vietnam
- Built a scalable ML-based anomaly detection system to monitor cloud server traffic for millions of users, improving incident response time by 30%
- Evaluated time-series models (Holt-Winters, Prophet, ARIMA) and built an online-learning system that improved detection performance by 10% over baseline on seasonal traffic data
- Integrated a relational database to log and trigger user alerts on server traffic anomalies, with average delivery latency under 3 seconds
- Collaborated with cross-functional teams to deploy the alert system within the existing monitoring infrastructure
Projects
Contact
Please reach out if I am a good fit for your company
Location
United States of America
Call
+1 281 690 6463
qmt1@rice.edu