Zachary Bennett

As a Software Development Consultant at Feel Good AI (2023–2024), I contributed to AI-driven products by integrating large language models, building backend systems on Google Cloud Platform, and creating JavaScript APIs. Additionally, I developed a chatbot avatar using Unity3D and a progressive web application for both mobile and desktop platforms with React and CSS.

As an Independent Unity Game Developer (2020–2021), I designed real-time multiplayer networking solutions, built functional prototypes, and documented detailed technical designs. My work included testing and optimizing performance for device compatibility.

Earlier in my career at EPAM Systems (2019–2020), I focused on automating testing and data processing tasks using Python and Bash, streamlining data collection processes, and executing SQL queries to support analytics.

I hold a Bachelor of Science in Computational Mathematics (3.6 GPA) from Michigan State University (2019), where I developed strong analytical and problem-solving skills applicable to software development and machine learning.

I also completed the following certifications:

Machine Learning on GCP: Expertise in ETL processes, statistical models, and ML pipelines.

Machine Learning by Stanford University: Advanced understanding of neural networks, logistic regression, and clustering methods.

I was also a contributing author to the following research papers:

"MUVA: A New Large-Scale Benchmark for Multi-view Amodal Instance Segmentation in the Shopping Scenario." IEEE/CVF ICCV 2023.

"Making Autonomous Stores Smarter (MASS): A Practical Solution to Improve Product Detection Performance Using Synthetic Dataset at Scale." IEEE SmartCloud 2023.