Computer Vision Machine Learning

Dang Vu Tuan Kiet

• ******************@*****.*** • 093******* • https://github.com/Kiet0712

Education

Ho Chi Minh University of Technology (HCMUT) Computer Science

• GPA: 8.74/10.0.

• Third-year student of the Honor program of the Faculty of Computer Science and Engineering. Experience

AI TechLab

AI Researcher 2024-now

• Research Activities:

– First author of MonoDSSMs (published at ACCV2024), an efficient pipeline for monocular 3D object detection task, which is appropriate for real-world applications.

– The first author of MonoQ (under review at NeurIPS2025), a novel model for the monocular 3D object detection task, achieves SOTA performance on the KITTI dataset.

– Currently working on improving the performance of monocular 3D detection using the GRPO technique from DeepSeek.

• Familiar with modern AI models, especially in computer vision and 3D perception tasks.

• Possesses a strong understanding of contemporary deep learning architectures. Project

Genetic Algorithm for Game Solving Github Repository 9/2023 - 11/2023

• Design genetic algorithm for solving Reach The Flag, an online puzzle game.

• Design and collect data to create a game environment to visualize and solve the game.

• The result algorithm can solve several levels of the game but not all due to the limit of the genetic algorithm Brain Tumor Segmentation Github Repository 1/2024 - 5/2024

• Research and improve the performance of brain tumor segmentation on the BraTS dataset for a college-level research project.

• The design model achieves impressive performance on BraTS and multiple medical segmentation datasets (Le- sion, Polyp ).

Adaptive Round Robin Github Repository 4/2024 – 5/2024

• Enhance the Round Robin scheduler algorithm based on user requirements using the transformer architecture.

• Early results show it can achieve 88.8% accuracy while still being fast with 3,000 FPS. SmartHome Github Repository 2/2025 – 4/2025

• Design a system for a smart home with multiple AI features: Facial Recognition, Voice Command Classification, Anomaly Detection.

Skills & Certifications

Technical: Familiar with C++, Python programming, Docker, and modern AI frameworks (Pytorch, Triton). Language: Proficient in technical English, with experience writing and presenting research papers. Certifications: Machine Learning Specialization and Deep Learning Specialization on Coursera.

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