About Me
Hi, I’m Simon — a data scientist and software developer currently working on my Master’s in Data Science at Bryant University in Rhode Island. I also work as a Research Assistant in the Information Systems & Analytics Department, where I conduct research in agentic AI and help support various academic and data-related initiatives.
Before this, I studied Computer Science at Mendel University in Brno, Czech Republic, and spent part of my undergraduate degree at Oregon State University, where I also took business courses to see how technology and data shape business decisions. I’ve worked in data analysis, full-stack development, and automation, from collaborating with national sports organizations to developing commercial software that thousands of people use worldwide.
I’m enthusiastic about applying data to solve practical problems, especially where it can help us understand the world better and create positive change.
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Projects
StatistIQ: AI-Driven NBA Performance Prediction App
Developed an iOS application focused on predicting NBA performance metrics using machine learning. The app processes real-world basketball data to estimate win probabilities, projected points, overtime likelihood, and other advanced indicators. The full workflow covers data preprocessing, model training, cloud deployment, and mobile delivery, turning raw sports data into clear and actionable insights.
Python
Swift
Pandas
NumPy
Scikit-learn
XGBoost
Firebase
Google Cloud
Google AdMob
Tennis Video Analysis: Automated Player & Ball Tracking
Working on a training-oriented computer vision project for tennis match analysis. The pipeline focuses on player and ball tracking, court line detection, and shot trajectory visualization, serving as hands-on practice with deep learning and classical computer vision methods.
Python
NumPy
OpenCV
YOLO
Matplotlib
Shot Lakehouse: End-to-End Basketball Analytics Platform
End-to-end data platform that streams raw basketball shot events through Kafka and Delta Lake (Bronze, Silver, Gold) into interactive Streamlit dashboards. Includes data validation, feature engineering, and secure OAuth access to Databricks SQL, designed to mirror a real production analytics stack.
Python
MySQL
Kafka
Spark
Databricks
Streamlit
AWS
S3
Docker
Airflow
Predictive Analytics for Czech Basketball League: Player Performance & Strategy Optimization
Built machine learning models including Random Forest, XGBoost, CatBoost, and Keras neural networks to predict player performance and optimize game strategies for teams in the Czech basketball league. By applying advanced analytics, I provided coaches and management with actionable insights that supported smarter decisions and a stronger competitive edge.
Python
Pandas
NumPy
Scikit-learn
Matplotlib
Seaborn
Flask
Jinja
SQLAlchemy
MySQL
Reawote Material Loader Plugins for 3D Programs
Developed a set of plugins with Reawote ↗ that let 3D artists easily load PBR materials from the Reawote library into major tools like Cinema 4D, Blender, SketchUp, and 3ds Max. The plugins streamline workflows across different platforms and scripting environments, making it faster and simpler for designers to work with high-quality materials.
Python
Ruby
MAXScript
JavaScript
HTML
CSS
Modular PHP System for Dynamic Form Management
Developed a PHP-based module for managing user-specific forms and workflows within a larger platform. The system enables dynamic form assignment, role-based access, file uploads, and status tracking, and integrates directly with user data. Built with flexibility in mind, it is adaptable to various internal use cases such as onboarding, progress monitoring, and administrative automation.
PHP
JavaScript
MySQL
HTML
CSS
Email
LinkedIn
GitHub