Le Anh Quan

LE ANH QUAN Phone: Email: Linkedin Github: --www.linkedin.com/in/lê-quân-174b73222 https://github.com/Qismeeee SUMMARY Final-year Information Technology student transitioning into AI Engineer and Data Scientist roles, bringing hands-on experience developing RAG-powered conversational systems and implementing deep learning models for network security applications. My practical work analyzing complex datasets and extracting actionable insights has strengthened data-driven decision-making capabilities across machine learning and generative AI domains. With proven expertise in Python, TensorFlow, and PyTorch, I am positioned to contribute immediately to innovative AI projects that deliver measurable business impact and advance data science solutions. EDUCATION Can Tho University Major in Information Technology(High-quality program) Cumulative GPA: 3.58/4 LINK October 2021 - Present WORK EXPERIENCE AI Engineer Intern, BIWOCO March 2025 - May 2025 Collaborated on developing RPAAsgard, a serverless RPA platform leveraging AWS cloud infrastructure to automate business processes. Engineered browser automation capabilities by integrating Playwright Codegen with XPath output. Built automated testing agent using Playwright framework, reducing manual testing time and ensuring consistent quality across platform deployments. GenAI Engineer Intern, Cake by VPBank May 2025 - July 2025 Contributed to developing advanced Speech-to-Text models for Vietnamese language processing, achieving improved accuracy through custom dataset labeling and model finetuning. Implemented Retrieval-Augmented Generation (RAG) architecture for intelligent chatbot systems, integrating knowledge retrieval with generative responses for enhanced conversational accuracy. Engineered and optimized Large Language Models (LLMs) for conversational AI applications, implementing efficient training pipelines and evaluation metrics. PROJECTS University Regulations Chatbot LINK August 2024 - December 2024 Led development of an advanced AI-powered chatbot using Retrieval-Augmented Generation (RAG) technology. Designed and implemented a multimodal system integrating speech-to-text conversion with Whisper for enhanced user accessibility. Engineered a robust vector database using Milvus for efficient retrieval of university regulations. Created a flexible architecture combining local LLMs (Ollama) and cloud-based solutions (OpenAI) to optimize performance and cost-effectiveness. Network Intrusion Detection System - Team Leader LINK June 2024 - November 2024 Spearheaded research on multiple deep learning architectures for network intrusion detection, achieving about 98% detection accuracy on the UNSW-NB15 dataset. Implemented and benchmarked various neural network models (CNN, RNN, Transformer, GRU) to identify optimal architecture for different attack types. Conducted comprehensive performance analysis using key metrics (accuracy, precision, recall, F1score) to enhance detection capabilities. Housing Price Prediction System LINK June 2024 - July 2024 Developed a sophisticated regression model to predict housing prices using RandomForest and Linear Regression algorithms, achieving high prediction accuracy with RMSE optimization. Implemented feature selection techniques to identify the most predictive variables, optimizing model efficiency and interpretability. Performed in-depth exploratory data analysis with visualization techniques to understand price distributions and correlations between housing features. CERTIFICATION IBM Data Science Professional Certificate LINK Google Data Analytics Professional Certificate LINK LLM Engineering: Master AI, Large Language Models & Agents LINK TOEIC 860 LINK Certificate of IoT Workshop LINK Certificate of Medical Imaging Workshop LINK Certificate of Participation in APU Study Abroad Programme LINK Student with 5 Good Criteria at City-level LINK Advanced Youth Following President Ho Chi Minh's Wills LINK Typical Advanced Student in the Education Sector for the period- LINK Academic Awards(Achieve scholarships in total 2 semesters) LINK TECHNICAL SKILLS Core AI/ML Skills: Machine Learning, Deep Learning (GRU, LSTM, CNN, Transformer), NLP and Computer Vision Frameworks: TensorFlow, PyTorch, Scikit-Learn, Pandas Development: Git, Docker, Model Deployment Workflows Cloud: AWS, Cloud Services Databases: MySQL, SQL Server, Vector Databases (Milvus) SOFT SKILLS Problem-Solving & Analytical Thinking Self-Learning & Research Team Collaboration & Cross-Disciplinary Work Continuous Improvement & Adaptability Proactive & Entrepreneurial Mindset