Welcome to my GitHub repository! This is where I showcase my projects and skills as a computer science major at Rensselaer Polytechnic Institute (RPI).
💻 I'm Ryan, a CS major passionate about coding and technology.
- 🎓 Currently pursuing a degree in Computer Science at RPI.
- 📧 You can reach me at [email protected] or [email protected] or [email protected].
Here are some of the languages and technologies I'm proficient in:
- Python
- Algorithm design and analysis
- C
- Java
- R
- C++
- HTML/CSS
Work on logistics routing problem and use Python to model the VRPTW model. The dijkstra algorithm, kmeans and hierarchical clustering algorithms are mainly used to complete the path finding of the model and clustering of all orders. At the same time, the two-opt algorithm is also used to solve the self-intersection problem of the path. In the test results of multiple data sets, the full load rate exceeds 80%, and the result graph can show excellent routing effect.
- Using: Python, sklearn, numpy, algorithm design
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Used OpenCV, pytorch, COCO, and other language libraries to process large image databases, divide image datasets and convert them into coco format json files, and used YOLOv8 and EfficientDet models to perform target detection on image data.
- Using: Python, pytorch, coco, Yolov8, OpenCV
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Accomplish the design and implementation of a classification model development framework for survival data analysis alone, taking responsibility for key components including data preprocessing, model development and optimization, and performance evaluation. Developed efficient preprocessing scripts to clean data, engineer features, and address class imbalance; created customized evaluation functions to consolidate multiple performance metrics with intuitive visualizations; and implemented and optimized various classification algorithms (Logistic Regression, Decision Tree, Random Forest, etc.), transforming complex survival datasets into actionable classification tasks with high predictive accuracy.
- Using: R
Perform data mining and feature engineering on Decentralized finance data, and use sklearn's five machine learning models to predict the rise or fall of a certain currency price in the future. The highest success rate reaches 79.17%.
- Using: Python
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Research on Contemporary Issues in Artificial Intelligence and Machine Learning Models. Prediction and Classification on Diverse Datasets using sklearn.
- Using: Python
- Utilized the sklearn library for prediction and classification tasks on datasets
- Analyzed and evaluated model performance, and conducted tuning
Led team in the Edge-X competition supported by Intel, focusing on developing an interactive program named TT -- an open-source tracking network providing IoT devices with relative location information independent of high power consumption or satellite signals. Spearheaded API creation for seamless integration, utilizing Matter for Bluetooth transmission and location recognition akin to AirTag. Undertook diverse responsibilities, including API writing, computational algorithm development, documentation,and C++ implementation for Matter connections.
- Using: Python, C++, Go
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Developed a Python-based system to manage vending machine data, including real-time availability and location. Implemented algorithms for shortest path optimization and finding nearest vending machines based on user needs. Demonstrated strong skills in data modeling and algorithm design.
- Using: Python
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Focus on data processing, web crawling and extracting valuable information for the website development team.
- Using: Python
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Write a paper called "Enhancing Automotive Interior Automation through Face Analysis Techniques", and successfully accepted by CONF-CDS 2024.
Write a paper called "The Application of Machine Learning Algorithms in Data Mining", and successfully accepted by International Journal of Intelligent Information and Management Science.
Feel free to contact with me on LinkedIn or shoot me an email if you'd like to collaborate on a project or just chat about coding and tech.
Thanks for stopping by! 🚀