Education
Northeastern University, Boston, MA
Master of Electrical and Computer Engineering
Concentration in Computer Vision, Machine Learning, and Algorithms
May 2026 (Expected)
Relevant Courses: Advanced Machine Learning, Data Visualization, Introduction to Algorithms
Wenzhou-Kean University, Wenzhou, China
Bachelor of Science in Computer Science and Technology
Minor in Math and Applied Math
June 2024
Relevant Courses: Artificial Intelligence, Introduction to Computer Vision, Software Engineering, Game Programming
Professional Experience
Research and Teaching Assistant
College of Science, Mathematics and Technology, Wenzhou-Kean University
March 2021 – May 2024
- Hosted the largest academic symposium at the university with 300+ attendees.
- Taught Python, data analysis, and algorithms to over 30 students.
- Led event organization and student ambassador team of 60+, executing large events like Open Day and International Cultural Exchange Festival.
Software Testing Engineer
Beijing DXC Technology, Wenzhou, China
July 2021 – September 2021
- Designed and executed test cases, completing 40% of project test requirements.
- Coordinated with 15-person development team to align on iterative development.
- Improved workflow between QA and developers, shortening feedback loops.
Technical Skills
Programming Languages: Java, Python, C, C++, C#
Libraries & Tools: OpenCV, NumPy, TensorFlow, PyTorch, Pandas, Matplotlib, Scikit-learn
Machine Learning Techniques: Random Forest, SVM, KNN, Decision Tree, Naive Bayes, K-Means, Ensemble Models
Academic Projects
Spam Detection with Machine Learning
Nov 2024 – Dec 2024
- Achieved over 95% accuracy with Random Forest & SVM models.
- Used PCA for dimensionality reduction, improving accuracy by 5%.
- Applied Matplotlib for heatmaps and visualization during data analysis.
Correction of Pen-Holding Posture Using Computer Vision
Apr 2024 – Jun 2024
- Led full project cycle from data acquisition to modeling.
- Used MediaPipe for optimized image acquisition.
- Built Random Forest model with 92% real-time accuracy.
Farm Suitable Crop Data Analysis
Apr 2024 – Jun 2024
- Conducted feature analysis and preprocessing.
- Built and evaluated Random Forest model using scikit-learn.
- Used data visualization for effective results presentation.
Service and Leadership
Led a team of 60+ student ambassadors and organized university-wide events for 300+ participants.