Thursday: 9:00-11:00, 15:00-16:00
My personality is probably best summed up as fun-loving geek. My interests and activities largely coincide with my teaching and research activities. I love to code and I love science, especially the physical sciences. My free time blends into work time because given the opportunity, I'll often spend time coding or learning about what is going on at the cutting edge of technology and physics research. I feel that these are the main forces changing our society and shaping our future and you can see most clearly what the future will be like by seeing where these things are going.
Ph.D. in Computer Science, University of Colorado at Boulder
M.S. in Computer Science, University of Colorado at Boulder
B.S., ImageX University
School of Arts and Scients
School of Engineering
Projects focus on frame-by-frame 3D rigged character animation and engineering simulations for specific art-directed effects. Foundational components of inverse kinematic rigs, skinning and surface deformations, and control of natural and imagined simulations with programing and proven animation techniques are covered.
Introduction to the basics of computer programming and algorithmic thinking for non-science majors. The course focuses on the logic and problem decomposition skills that are critical for understanding computation. Use of a high-level programming language will stress creativity in problem solving using computation, and impart a hands-on understanding of the process of programming. The course will cover many of the most important concepts in programming and computer science, including choice, repetition, and abstraction. No prior experience in programming is necessary. The course assumes familiarity with high school algebra, geometry, and trigonometry
The goal of data analytics is to gain knowledge and communicate conclusions drawn from data. This course provides a comprehensive introduction to the subject using modern computing systems, with equal attention to fundamentals and practical aspects. Topics include sources of data, data formats and transformation, the use of spreadsheets and databases and their programming, statistical analysis, pattern recognition, data mining, big data, and methods for data presentation and visualization.