Machine Learning Computer Science Internship

Tu Mai The Nhan

+ Ho Chi Minh City # ****.******@*****.*** 086******* ð The Nhan § The Nhan

Summary

Passionate AI/ML enthusiast with a strong foundation in machine learning, deep learning, and data analysis. Currently studying Computer Science at HCMUT, I have experience working with structured and unstructured data, optimizing model performance, and handling large-scale datasets. Seeking an internship to apply my skills to real-world AI/ML challenges and further develop my expertise.

Education

BS Ho Chi Minh University of Techonology (HCMUT), Computer Science

• GPA: 3.5/4.0 (Academic Transcript 2)

• Coursework: Computer Vision, Natural Language Processing

• Achievement: AwardedtheEncouragementScholarshipforSemester232 and the Local Scholarship for the 2023-2024 academic year. Sept 2021 – Now

Experience

IAS Lab, Undergraduate Researcher

• WorkedwithLargeLanguageModels(LLMs)ontemporalreasoning,includingdataset creation, evaluation, and benchmarking.

• Researched knowledge graphs and Neo4j, exploring their integration with LLMs for enhanced reasoning and retrieval.

• Fine-tuned deep learningmodelsusingTensorFlowandPyTorchtoimproveaccu- racy.

• Processed and analyzed large datasets with Pandas, NumPy, and Scikit-learn for feature engineering and data augmentation.

Thu Duc City, HCMC

May 2024 – Now

NUS Technology, Software Engineer Intern

• Built web applications using Ruby on Rails, SQL databases.

• Designed and deployed RESTful APIs, hosting applications on Render for scalabil- ity and reliability

• Collaborated in an agile team, participating in code reviews, debugging, and ver- sion control with Git.

Tan Binh District, HCMC

June 2024 – July 2024

Projects

Titanic Machine Learning Workflow

Video presentation: Ensemble Learnning 2

• Developed a machine learning pipeline to predict Titanic passenger survival.

• Performed data preprocessing: handled missing values, engineered new features

(AgeGroup, Title, FareBand).

• Trained and evaluated multiple models: Logistic Regression, KNN, SVM, Decision Tree, Random Forest, XGBoost, and Stacking Classifier.

• Deployed the model using FastAPI with a simple HTML/CSS web interface.

• Tools: Python (pandas, scikit-learn, XGBoost), FastAPI, HTML, CSS. Titanic Workflow 2

YOLO Smart Farm

• Designedamodern,responsiveUIinFigmaandimplementeditusingReactNative Yolo Smart Farm 2

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for efficient farm management.

• Integrated IoT connectivity via Adafruit IO & MQTT for real-time device monitoring and control.

• Developed and deployed AI models for leaf disease detection and speech recog- nition, enabling automated alerts and voice-based commands.

• Connected the frontend to a MongoDB backend for efficient data storage and re- trieval.

• Tools: React Native, Figma, MongoDB, MQTT, Adafruit IO, Python (TensorFlow). Smart Document QA

• Built an intelligent document-based chatbot using LangChain, LlamaIndex, and Hugging Face Transformers.

• Implemented document retrieval (PDF, TXT) with embedding-based search using FAISS.

• Designed an interactive Streamlit UI for real-time question-answering.

• Tools: Python, PyTorch, LangChain, FAISS, LlamaIndex, Streamlit, Hugging Face. DocChat AI 2

Statement Anomaly Detector

• Developed a web app for transaction anomaly detection and statement verifica- tion.

• Implemented an API for transaction validation using FastAPI.

• Trained an LSTM Autoencoder to detect fraudulent transactions.

• Designed a user-friendly frontend with HTML, CSS, and JavaScript.

• Tools: FastAPI, Pandas, TensorFlow, HTML, CSS, JavaScript. Fraud Checker 2

Solar/Wind Energy Prediction

• Builtmachinelearningmodels(LinearRegression,DecisionTrees,LSTM) fromscratch for energy output prediction.

• Processed meteorological data to improve forecasting accuracy.

• Deployed an interactive visualization dashboard using Streamlit.

• Tools: Python, NumPy, Pandas, Scikit-learn, Streamlit. Energy Forecast 2

Technologies

Programming Languages: Python, SQL, Java, JavaScript, Ruby, C++, PHP Machine Learning & Deep Learning: TensorFlow, PyTorch, Scikit-Learn, XGBoost, LSTM, Autoencoder Data Processing & Analysis: Pandas, NumPy, Scipy, BigQuery, Neo4j Model Evaluation&Optimization: Classificationmetrics,Hyperparameter tuning, Feature engineering, Transfer learning Knowledge Graph & Databases: Neo4j, Google BigQuery, Firebase, SQL databases, MongoDB Cloud & Deployment: Render, Docker, FastAPI, RESTful APIs Tools & Frameworks: FastAPI, Git, Jupyter Notebook, Streamlit, LangChain, LlamaIndex, Flutter, React Native, ReactJS, MQTT, Adafruit IO, Figma

Relevant Coursework

Language: TOEIC 705 (Listening & Reading)

Coursework: Data Engineering - HCMUT

Coursework: Machine Learning and Applications - HCMUT Certification: AI Agents – Hugging Face

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