What is Principled Interfaces?

In Principled Interfaces, we build research tools to understand the impact of new technologies on our quality of life. We focus is on understanding the science of interface design – how does the design or our technology affect our life?

Our goal is to usher in a future of principled interfaces that are in tune with human nature, understand their users, and help support meaningful living.

What Approaches Do we Take?

Our group is unique in a few ways:

(1) We focus on real-world naturalistic study. We are constantly developing new hardware systems to study real-world, long-term behavior in as unobtrusive a way as possible; we also design interventions to alter real-world behavior that are product-quality, so people can really live with the technology we use in our experiments.

(2) We take an idiographic approach; meaning we are not trying to make generalizations across large groups of people. The same technology affects people very differently depending on their personality and motivations; it can even affect the same person very differently depending on their mood and their context.

Instead of trying to make broad general claims based on small average effect sizes (and attempting to average out the effects of the individual and their context), we’re instead interested in large effects for specific individuals in specific contexts. We believe deep exploration of <intervention, individual, context> constellations is the fastest approach to predictive, generalizable science.

Research Approaches

– Creating software systems to monitor and alter real-world technology usage.

– Creating consumer-grade hardware systems for physiological and behavioral monitoring.

– Designing signal processing, machine learning, and probabilistic signal fusion algorithms for psycho-physiological and psychological models.

– Applying mixed methods approaches to naturalistic field study of behavioral, psychological, and cognitive phenomena and their causal antecedents.

– Creating provocative new interfaces, especially intelligent and adaptive interfaces, that embody our latest intuitions about human nature, and testing these new interfaces in the field.

Relevant Domains

psycho-physiological monitoring; system engineering; psychological and behavioral research methods; computational psychology; probabilistic modelling of user cognition and experience; user experience design; new interface design; human computer interaction

Relevant Skills

Hardware: Electrical Engineering, Mechanical Engineering, Fabrication, Hardware development, Manufacturing and Testing (Fusion 360, Solidworks, etc; Altium, KiCAD, etc; Debugging and Prototyping skills)

Software: Software Engineering, Full-stack development, System Engineering, Embedded Firmware (Networking, Web Development, Javascript, Database Infrastructure, C, Free RTOS and STM32/Eclipse, Python, React-Native, App Development)

Algorithms: Signal Processing, Deep Learning (especially edge applications), Probabilistic Programming, AI, Data Analysis and Applied Statistics (Pyro, Pytorch, Tensorflow, TinyML, DSP, Pandas, Signal conditioning theory and modeling)

HCI/UX Research: User Experience Design, Human Computer Interaction, Media Theory (user research methods, IRB processes, CHI publications, Don Norman, Marshall McLuhan, Neil Postman, Aldous Huxley)

Computational Psychology: Social Psychology, Behavioral Economics, Replication Crisis and Statistics (particularly Bayesian approaches), Affective Computing, Psychophysiology, Computational Cognitive Science (See my class on the replication crisis, read Richard McElreath’s statistical rethinking, etc)