Python has emerged as a versatile tool for 3D computer graphics, offering powerful capabilities in modeling, animation, and simulation. This presentation explores the application of Python in creating dynamic and visually engaging 3D graphics using Blender. The session will showcase practical examples that demonstrate Python's potential in various aspects of 3D graphics
basics of Python
Explore techniques for programmatically creating and manipulating 3D models in Blender using Python scripting. Illustrate how Python can be utilized to animate statistical data in a 3D environment. Present a Python implementation of the Game of Life cellular automaton within Blender. Showcase Python scripts for creating randomized animations in Blender.
Through these demonstrations, attendees will gain insights into Python's role as a powerful tool for enhancing creativity and productivity in 3D computer graphics. The presentation aims to inspire participants to leverage Python's capabilities for innovative and expressive 3D visualizations across various domains.
JURGIS ZAGORSKAS (1977-09-08) Assoc. prof., Vilnius Gediminas Technical University (VILNIUS TECH)
PROFESSIONAL SUMMARY Experienced researcher and academic at Vilnius Gediminas Technical University (VILNIUS TECH), specializing in computer graphics, 3D modeling, Python programming, and data visualization. Focused on developing interactive 3D visualizations and applying AI and machine learning for data analysis and urban planning. Actively researching LiDAR data processing and geospatial applications for smart city development and digital mapping. Passionate about leveraging computational methods and advanced data visualization tools to address modern challenges in engineering, urban design, and environmental sustainability.
EDUCATION Ph.D. in Engineering Sciences Vilnius Gediminas Technical University (VILNIUS TECH), 2008
RESEARCH INTERESTS • Computer Graphics & 3D Modeling – Python-based scripting for 3D visualization, modeling, and rendering techniques. • Data Visualization & Interaction – Development of interactive data visualizations using 3D rendering and data-driven approaches for various applications. • Machine Learning & AI for Data Analysis – Applying AI algorithms to analyze and predict patterns in complex datasets, including for smart urban planning. • LiDAR & GIS Data Processing – Automated processing and visualization of LiDAR data for urban mapping, including the recognition of trees, buildings, and other city elements. • Geospatial Data & Digital Mapping – Integrating geospatial data into digital models for urban analysis and decision-making.________________________________________ ACADEMIC & TEACHING EXPERIENCE Associate Professor / Researcher Vilnius Gediminas Technical University (VILNIUS TECH) | [2008–Present] • Teaching computer graphics, 3D modeling, engineering visualization, and Pyth