AI Internship Candidate with ML & NLP Focus

Ngo Phuong Nam Email: **********@*****.***

https://www.linkedin.com/in/ngonam1601/ Mobile: 086******* Summary

Proactive and data-driven Computer Science student with a strong foundation in machine learning and model optimization. Looking for an AI/ML Engineer internship to develop and integrate intelligent systems into real-world products.

Education

University of Information Technology (UIT), VNUHCM Ho Chi Minh, Vietnam Bachelor of Computer Science; Current GPA: 8.61 Sep 2023 – 2027 (Expected)

• Achievements: Excellent Student — Recognized for academic excellence

• Relevant Coursework: Natural Language Processing (9.8), Computational Thinking (9.0), Data Mining (9.1) Technical Skills

Programming Language: Python, SQL, JavaScript

AI / Machine Learning: TensorFlow, PyTorch, Scikit-learn, XGBoost, CNN, NLP, Computer Vision Data Processing & Visualization: Matplotlib, Seaborn MLOps & Deployment: Flask, FastAPI, Docker

Tools: Git, Jupyter Notebook, VS Code, Microsoft Office Projects

Protein Functional Annotation System Group Project, 4 members 09/2025 - 12/2025 GitHub

• Engineered TF-IDF and ESM embeddings to transform protein sequences into numerical feature vectors.

• Benchmarked tree-based models (RF, XGBoost and LightGBM), with XGBoost achieving 99.93% test accuracy.

• Applied NLP-inspired techniques (TF-IDF, sequence tokenization) to extract features from amino acid sequences.

• Authored and presented the final report, translating technical results into clear insights. Garbage Classification System Group Project, 3 members 09/2025 - 12/2025 GitHub

• Developed an image classification system for 6 waste categories using SVM.

• Engineered hybrid features (HOG, LBP, Histogram), improving F1-score to 0.67.

• Leveraged pretrained models (CLIP, EfficientNet, ResNet), achieving up to 98.8% accuracy.

• Optimized SVM with GridSearchCV, boosting performance by 3–5%. Traffic Law QA Chatbot Personal Project 03/2025 - 04/2025 GitHub

• Developed a Vietnamese RAG-based chatbot for traffic law consultation.

• Generated embeddings using multilingual-e5-large for semantic retrieval.

• Implemented vector similarity search to retrieve relevant regulations.

• Built an interactive interface for real-time question answering. CodeSIM: Multi-Agent Code Generation NLP Research, 2 members 02/2026 – 06/2026 GitHub

• Reproduced and evaluated the CodeSIM multi-agent code generation framework from NAACL Findings 2025

• Benchmarked GPT-4o-mini across HumanEval, MBPP, and LBPP datasets, achieving up to 96.3% pass@1 on HumanEval and 69.8% on LBPP.

• Conducted systematic error analysis covering algorithmic reasoning failures, planning mistakes, edge-case handling, and debugging limitations.

• Proposed improvements including algorithm-aware retrieval augmentation (RAG) and automated test case generation for planning verification.

Certifications

Applications of AI for Anomaly Detection NVIDIA Certificate

• Learned machine learning techniques for anomaly detection, including feature engineering, outlier detection, and model evaluation.

Languages

English — TOEIC: 790 (Listening & Reading), 290 (Speaking & Writing)

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