 Developed and maintained data models for the website, generating synthetic data for development and testing.

 Transformed raw data from various sources, applied statistical and ML algorithms to uncover patterns and trends.

 Automated data analysis workflows, enhancing efficiency and visualization algorithms related to DNA sequencing data.

reader for INDENG 164 Introduction for Optimization Methods

Grading weekly assignments and Midterm

Provide solution and corresponding code for homework

Hold 2hr weekly office hour

 Cleaned up redundant calculations and modified the risky operations for group’s code. Supplemented the unit-test of the function without coverage by any test. Used git to update, modify and upload local code. Finished 4 complete closed-loop work and familiarized with the company's workflow. Code volume: 0.5k.

 Learned wireless network knowledge through 3Gpp protocol, summarized notes and making slides on data processing in base station for uplink and downlink, and organized sharing among group members.

 Delivered a requirement on determining the user type and transmitting the relevant information. Added new functions and covered them by MTT. Test the results on the virtual environment by bin packages generated by code. Completed the module, test design and corresponding result summary. Code volume: 0.6k.

 Processed open resume data collections from Kaggle, cleaned and processed the dataset using Pandas, made Dice coefficient comparisons, made dataset classification by using KNN and K-mean clustering.

 Extracted skills set by spaCy from sample resumes and placing in the dataset for similarity matching. Compiled as a package and corresponding API and pytest for secondary data analysis of the team.

Applied Mob Programming approach with other colleagues to develop the virtual networking software.

https://github.com/xilin-tian/Resume_Classification