Master’s student in Embedded Artificial Intelligence with a background in Computer Science and Finance. Experienced in multi-modal data annotation and AI data pipelines. Passionate about AI applications and software development, currently seeking opportunities in Europe.
On-site installation and debugging of food delivery robots & robot vacuum cleaners; Robot hardware system assembly and disassembly; Robot after-sales issues; PUDU operating system training.
Performed annotation of multi-modal data for machine learning model training; Contributed to data preprocessing and dataset structuring for AI pipelines; Supported the development of reliable training datasets for downstream AI tasks
Built an end-to-end sales analytics system with FastAPI backend and Streamlit dashboard. Designed a Pandas-based data pipeline for KPI computation and trend analysis. Deployed backend on Render and frontend on Streamlit Cloud, and implemented CI/CD with GitHub Actions for automated testing and deployment.
Developed an autonomous driving system using RoboMaster platform, implemented object detection and tracking using YOLOv5 and PP-PicoDet, designed a PID controller for motion control and target following, integrated multi-sensor data for obstacle avoidance in dynamic environments
Built an end-to-end voice recognition pipeline from data acquisition to inference, converted audio signals (WAV) into image representations for feature extraction, extracted features using Local Binary Patterns (LBP), trained and evaluated machine learning models for real-time voice recognition
Developed a facial recognition system using PaddlePaddle framework, performed image annotation and dataset preparation, trained and evaluated models for face identification tasks
Developed a tourism mini-program enabling users to explore attractions remotely, designed and implemented user interfaces using web technologies (HTML/CSS/JavaScript)
Developed a license plate detection system using image processing techniques, applied MATLAB to locate and extract license plate regions from images
Built an LSTM-based model for sentiment classification, processed textual datasets and classified sentiment into positive and negative categories
Developed a simple image viewer application using Android Studio
Developed a basic drawing application using Java
Major courses: Embedded C Progamming, Artificial Intelligence for Smart Systems, Virtual Instrumentation, Smart Sensors, Project Management, Data Structures and Algorithms, Fundamentals of Machine Learning, etc.
Major courses: Advanced Mathematics, Linear Algebra, Computer Principles, Computer Networks, Database, operating system, Algorithm Analysis and Design, Computer Graphics, mobile Application Development, Machine Learning, etc.
Major courses: Micro Economics, International Economics, Statistics, Insurance, Accounting Financial Engineering, Financial Marketing, Financial Risk Management, International Credit, Stock investment, etc.