Welcome to my online hub. This website was originally intended as a knowledge dump, but I later decided to double as my personal landing page. If you are a recruiter, you will find that this page greatly overlaps with my resume. Feel free to visit the last link under the above section. Otherwise, please visit whatever you find interesting on the sidebar. Cheers! 🥂
About
For my undergraduate studies, I earned my dual degree in Computer Science and Statistics from the University of Florida. While there, I became invested in several projects, research programs, and research assistantships in the areas of applied natural language processing (NLP). The applications ranged from indexing ancient Latin and Greek that have undergone digitization to judging the performance between different machine learning models on classifying legal contracts and documents.
After graduating, I landed my first serious employment as a software engineer at Amazon Web Services, Inc. in Seattle. In my almost 2.5 years there, I chiefly worked on support systems used by various teams in the Elastic Load Balancing (ELB) division. My longest term accomplishment there was designing, constructing, and iteratively refining an automated patching system for EC2 instance fleets while under the constraint of minimizing downtime.
Currently, I am pursuing a M.S. in Computer Science from Georgia Institute of Technology as a means to re-upskill. This is one major step in my future goal in pivoting towards the language and compiler space within software engineering.
Outside of school and work, I split my free time amongst running, reading science fiction novels, and playing logic intensive games such as chess and go.
Education
01/2025 – 12/2026
Georgia Institute of Technology M.S. in Computer Science
08/2019 – 05/2022
University of Florida B.S. in Computer Science | B.A. in Statistics
Professional Experience
10/2022 – 01/2025
Software Development Engineer Amazon Web Services, Inc.
06/2022 – 10/2022
Software Engineer Internship UKG, Inc.
Selected Projects
Evaluating Tree-based Models for Survival Analysis
Course Project | Department of Statistics, University of Florida
Compared selection of tree-based machine learning methods against traditional survival analysis methods, namely Kaplan-Meier and Cox-Hazard, on predicting lifetimes of Kickstarter projects being funded
Experimental results concluded the traditional methods performed similarly to each other but were dominated by tree-based methods, most prominently conditional inference trees across all scoring metrics
Network Cache System Simulator
Course project | Department of CISE, University of Florida
Designed caching policy for discrete-event simulation study of a network file system, which was tested against well-known caching policies in literature
Ranking based on average network request completion time, performance analysis revealed that evicting largest file first is fastest on average
Using AI to Trace the History of Race and Inequality
Research assistantship | Department of Classics, College of Liberal Arts & Sciences, University of Florida | Advisor: Dr. Eleni Bozia
Engineered NLP pipeline to retrieve, transform, and index Latin and Greek from archived XML sources, allowing easy search to support sentiment analysis of daily life in the classical world
Supervised undergraduate teams on digital text extraction and XML indexing to compare metadata between pieces of text volumes during text processing
Data Analytics and Information Retrieval" NSF Research Experience for Undergraduates
NSF REU Recipient • Department of Information Science, College of Information, University of North Texas | Advisor: Dr. Junhua Ding
Experimentally evaluated traditional versus deep learning algorithms on legal text classification to identify models that could help legal teams quickly identify legal contract type from corporate documents
Analyzed dataset factors to explain why traditional ML, especially boosting algorithms, outperformed deep learning models transferred from BERT and Sentence-BERT models
Publications & Writing
Qin, C., Yang, Y., Chen, H., & Ding, J. (2021). A Comparison Study of Machine Learning and Deep Learning for Legal Contract Understanding [Manuscript submitted for publication], Department of Computer & Information Science & Engineering (CISE), University of Florida.
Qin, C. (2021). Predictive Sampling Method for Spread Models in Networks. UF Journal of Undergraduate Research, 23(Fall 2021). https://doi.org/10.32473/ufjur.v23i.128429
Awards & Recognition
06/2021
NSF REU: College of Information at UNT $7000 | University of North Texas, Denton, TX
03/2021
Gartner Group Information Technology Fund $1000 | University of Florida, Gainesville, FL
05/2020
Russell and Mary Hyatt McCaughan Scholarship $1000 | University of Florida, Gainesville, FL
02/2020
University Scholars Program Stipend $1750 | University of Florida, Gainesville, FL
05/2018
University Freshman Scholarship $1200 / Semester • Florida State University, Tallahassee, FL
Skills
Programming/Scripting/DB languages Python, C++, Java, Ruby, JavaScript/TypeScript, SQL