Ji Hwan Park
Assistant Professor
School of Interactive Games and Media
Golisano College of Computing and Information Sciences
Office Location
Office Mailing Address
20 Lomb Memorial Drive, Rochester, NY 14623
Ji Hwan Park
Assistant Professor
School of Interactive Games and Media
Golisano College of Computing and Information Sciences
Bio
Dr. Ji Hwan Park is a data visualization researcher who analyzes and visualizes various types of data, ranging from 2D and 3D data to high-dimensional and biomedical sequence data. Before joining RIT, he was an assistant computational scientist at Brookhaven National Lab and an assistant professor in the School of Computer Science at the University of Oklahoma. His research interests are accessible data visualization, digital twins, human-AI teaming, VR/AR, and crowdsourcing.
Areas of Expertise
Artificial Intelligence
Digital Twins
High-Performance Graphics
Interactive Media and Wellness
Virtual Reality
Currently Teaching
IGME-309
Data Structures & Algorithms for Games & Simulations II
3 Credits
This course continues the investigation into the application of data structures, algorithms, and fundamental Newtonian mechanics required for the development of video game applications, simulations, and entertainment software titles. Topics covered include quaternion representation of orientation and displacement, cubic curves and surfaces, classifiers, recursive generation of geometric structures, texture mapping, and the implementation of algorithms within game physics engines for collision detection and collision resolution of rigid bodies, and the numerical integration of the equations of motion. In addition, advanced data structures such as B+ trees and graphs will be investigated from the context of game application and entertainment software development. Programming assignments are a requirement for this course.
IGME-460
Data Visualization
3 Credits
Our world is flooded with data, and making sense of it can be a challenge. Visualizations help by exposing information, trends, and correlations that might otherwise go unnoticed in the raw data. In this course, students will learn to collect, clean, organize, and filter data sets of their own choosing. They will learn and apply principles from multiple fields including visual design, the psychology of perception, user experience design, and ethics. They will create static and interactive visualizations with a variety of information structures (hierarchies, maps, timelines, etc.). Students will learn to develop exploratory experiences that tell the story within the data. Programming projects are required.