Welcome!
Welcome to my homepage! Here are some quick facts about me:
🧑🎓 I recently graduated from the University of Houston with a B.S. in Computer Science and Biomedical Engineering.
🧑💻 I am a full-time Engineer at Microsoft AI and Research Intern at the University of Washington.
📸 My research interests are in computer vision spanning 3D vision, robotics, scene representation, perception, and generative approaches.
🦾 I am very passionate about AI vision applications to robotics, accessibility, and health.
Overview
I am a Vietnamese-American born and raised in Houston, TX. I am currently at Microsoft AI working on the Copilot Ecosystem and Services for Office products.
I also am a research intern at the University of Washington in the Personal Robotics Lab advised by Siddhartha Srinivasa and Dieter Fox. I actively investigate robot learning from the perspective of digital twin technology for 3D articulated objects for policy learning in simulation and transferred to real-world robotic manipulation tasks.
I studied Computer Science and Biomedical Engineering focusing on Machine Learning and Neural Engineering throughout my bachelors at the University of Houston. During my bachelors, I spent three years working on a range of research topics (brain-machine interfaces, computer vision, and robotics). Notably, I spent over two years with Dr. Shishir Shah (University of Houston) developing pose-invariant methods for face recognition models (Bachelors Thesis, VISAPP 2025).
For work experience, I have spent my past three summers interning at Microsoft, Amazon Web Services, and Northrop Grumman where I focused on engineering machine learning systems and applying models for practical enterprise applications.
May you have any questions or interest in collaboration please reach out to me at ctung AT uh DOT edu.
News
February 2025 Published at the 20th International Conference on Computer Vision Theory and Applications (VISAPP) 2025 as first-author.
November 2024 My research in pose-invariant face recognition was accepted and presented at the Rice Gulf Coast Undergraduate Research Symposium (GCURS) 2024 as an oral presentation.
June 2024 I was granted the Provost Undergraduate Research Scholarship to conduct a funded-semester of research to work on resolution effects on face recognition.
May 2024 Began my SWE internship at Microsoft for the Office AI Team!
May 2024 I successfully defended my Senior Honor’s Thesis on “Optimizing Data Selection for Pose-Invariance in Facial Recognition Algorithms”.
March 2024 I started my research assistantship at the University of Washington conducting 3D computer vision and articulated object reconstruction.
March 2024 Presented at the University of Houston Undergraduate Research Day for Pose-invariance in Face Recognition.
November 2022 I started my research assistantship at the UH Quantitative Imaging Lab advised by Dr. Shishir Shah.
📝 Publications
Minimizing Number of Poses for Pose-invariant Face Recognition
Carter Ung, Pranav Mantini, Shishir Shah
- We introduce an empirical study that address data collection bottlenecks in practical face recognition systems. By studying the effect of model performance across varying pose sets, we infer the minimal number of poses to train and enroll in a face recognition system to achieve pose-invariant capability with less redundancy in data collection efforts.
Minimizing the Number of Poses for Pose-invariant Face Recognition
Carter Ung
- Defended as an undergraduate dissertation, we introduce an empirical study that address data collection bottlenecks in practical face recognition systems.