Ai Engineer

Đặng Ngọc Bảo Trâm

Ho Chi Minh City • ****.*************@*****.***.** • 070*******

Education

Ho Chi Minh City University of Technology - VNU BE, Honors Program

• Current GPA: 3.7/4.0 2022 – 2026 (Expected)

• Got A, A+ in core subjects: Operating Systems, Data Structures and Algorithms, Computer Networks, Software Engineering,..

• Got "Study Encouragement"Scholarship (which covered tuition fee) for 3 semesters so far. Ho Chi Minh City University of Technology - VNU MS, Data Science Specialty

• Current GPA: 7.6/10.0 2024 – 2027 (Expected)

• Relevant Coursework: Data Mining, Applied Data Science, Scientific Research Methodology Research

End-to-end Motion Planning for Autonomous Driving Vehicles July 2024 – Now

[Instructed self-project] [Demo Link]

• Toward a better Deep Neural Network Architecture which takes a monocular RGB image as input and produces control signals as output.

• Conducted experiments: Implement pretrained modules that transform front-camera RGB images into Optical flows, BEV segmentation images; alternate GRU architecture with Transformer

• Technologies: Pytorch, Pytorch Lightning, Wandb, Hydra, Gymnasium, Stable-Baselines3, Docker, Shell Scrip- ting

• Datasets: Carla Simulation, NAVSIM

AI-based Operating System January 2024 – May 2024

[Instructed self-project] [Github Link]

• Use Reinforcement Learning to improve scheduling policy of Linux’s CFS Scheduler. The experiments are run on a simulated environment.

• Technologies: Ray RLlib, Gymnasium

Projects

Movie Recommendation System Sep 2024 – October 2024

[Self-project – AI Engineer] [Github Link]

• An application that recommends movies for a specific user or users for a specific movie, using ALS collaborative filtering algorithm.

• A Jupyter notebook is attached for movie/user data visualization and comparing between processing data with/without Apache Spark, and storing/loading data between Postgres and MongoDB.

• Technologies: Apache Spark, Pandas, Seaborn, Postgres, MongoDB, Flask. Fine-tuning Diffusion Models for Text-to-image Generation November 2024

[Self-project – AI Engineer] [Github Link]

• A notebook that compare DDPM and Stable Diffusion in terms of inference time, train a pretrained Diffusion models with images from another domain, and fine-tune those models’ hyperparameters.

• Technologies: Pytorch, HuggingFace, Matplotlib

Meeting Application with ASL Detection Integration October 2024 – Now

[Leader of a 4-member group - Full-stack Developer] [Github Link]

• A web application that allows users to video-call each other, integrated with a sign-language detector to facilitate communication of speech-impaired people.

• Technologies: Keras, Mediapipe, Reactjs, Tailwind CSS Smart Home Controll Application January 2025 – Now

[Leader of a 4-member team – Backend Developer] [Github Link]

• An application that allows user to manage, control and receive logs from their house’s sensors like thermostat, humidity sensor, door, fan

• Technologies: Typescript, Express, Postgres

Experience

TickLab 2022 – Now

[Member – Research Team]

• Being guided by seniors in the field of AI/Computer Vision and mentor new-comers stepping into this domain.

• Participate in biweekly knowledge-sharing seminars on Computer Vision-related subjects (Link of notable presentations).

• Author articles covering interesting topics in Computer Vision and Reinforcement Learning: Edge Detection, Reinforcement Learning series - Part 1

• Notable project: Use Genetic Algorithm to solve "Reach The Flag"game. Certificates

Machine Learning Specialization Coursera

[Andrew Ng · DeepLearning.AI] [Certificate Link]

• An introduction of modern machine learning concepts, including supervised learning (linear regression, logistic regression, neural networks, decision trees), unsupervised learning (clustering, anomaly detection), recommen- der systems, and reinforcement learning.

Deep Learning Specialization Coursera

[Andrew Ng · DeepLearning.AI] [Certificate Link]

• An introduction to neural network architectures such as Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, Transformers, and improvement strategies such as Dropout, BatchNorm, and Xavier/He initialization.

Skills & Interests

Programming Languages: Python, C++, Javascript/Typescript, HTML, CSS, SQL AI frameworks/libaries: Pytorch, OpenCV, Keras, Gymnasium Software frameworks/libaries: Reactjs, Tailwindcss, Express Tools: Docker, Github, HuggingFace, Wandb, Jira, Confluence

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