Mingxuan Gong

Professional software developer skilled in creating efficient, scalable code using languages such as Java and Python. Strong focus on team collaboration, adaptable to changing project requirements, and driven to deliver impactful results. Expertise includes debugging, problem-solving, and maintaining effective communication with cross-functional teams. Known for reliability and proactive approach to meeting development goals.

Malicious Email Detection via Machine Learning Approaches 05/2021-07/2021

https://doi.org/10.1117/12.2624886

Supervisor: Professor Nick Feamster, University of Chicago

• Compared 6 algorithms and decided to design the system based on Naïve Bayes to classify spam corpus, pre- detect, and filter spam

• Collected email data from the Text Retrieval Conference; programmed with Dictionary in Python to extract important information; pre-processed and cleaned data, applying Map function in Python to transform text data into numeric data and adopting an open-source jieba to split sentences into single words

• Conducted K-Fold cross-validation to verify the effectiveness of Naïve Bayes regarding the accuracy, recall score, F1 score, and time cost; concluded Naïve Bayes algorithm has the highest success rate of spam filtering.