I teach several courses in Systems Engineering, surrounding topics of Human Factors, Human Computer Interaction, User Experience Design, Psychophysics, and Haptics.
Have you ever dreamed of creating the next Instagram, TikTok, or what the industry likes to call the next “killer app”—a software application that is spectacularly designed that everyone wants it and wonders how they ever lived without it? Do you want to be able to redesign current systems that just don’t quite meet the needs of its users (i.e., UVA's Student Information System) so users don’t ask themselves, “Why did they design it like this? They clearly don’t understand my needs!” This class will provide you some of the tools and knowledge to do so! Specifically, this course will introduce the fundamentals for the analysis, design, and evaluation that considers a critical element of almost all systems—the PEOPLE.
This course takes a case-based, project approach to the design of user interfaces. Real-world clients enrich the nature of the problems and student interactions. This is a very interactive course, with much time in design working groups and design reviews. Students interact with and present designs to real industrial clients and give short talks on emerging design concepts. By the end of the course each student has put together a professional portfolio of three designs, vital for future jobs!
A design project course extending over the fall and spring semesters. Involves the study of an actual open-ended situation with a real-world client, including problem formulation, data collection, analysis and interpretation, model building for the purpose of evaluating design options, model analysis, and generation of solutions.
This course provides an introduction to the measurement and modeling of human perceptual information processing, with approaches from neurophysiology to psychophysics, for the purposes of system design. Measurement includes classical psychophysics, EEG field potentials, and single-neuron recordings. Modeling includes psychophysical approaches (limits, constant stimuli, adjustment; as well as ratio scaling methods), signal detection theory, neuronal models (leaky integrate-and-fire, Hodgkin-Huxley, and models utilizing regression, probability, and ordinary differential equations).
This course is taught as part of Systems Engineering's Accelerated Masters Program. Covers principles of human factors engineering, understanding and designing systems that take into account human capabilities and limitations from cognitive, physical, and social perspectives. The AMP is taught in a weekend format over the course of one year and features faculty from engineering and business.
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