Javier Gonzalez-Sanchez

Personal Details

Bio

I am an Assistant Professor at California State Polytechnic University. I earned a Ph.D. in Computer Science from Arizona State University, an MS in Electrical Engineering with a Computer Science major from the Mexican National Polytechnic Institute, and a BS degree in Computer Engineering from the Universidad de Guadalajara. I am a Senior Member of the Association for Computing Machinery (ACM) and a Senior Member of the IEEE. And an ACM Distinguished Speaker.

Currently, my work includes manufacturing personalized and adaptive intelligent tutors, developing affect-aware video games, and using affect-driven approaches to improve rehabilitation outcomes for children with disabilities. I have designed and managed the development of software frameworks, scalable web applications, and mobile apps; improved avatars for interpersonal communication; prototyped augmented reality environments; and created visual programming languages for parallel computing. I hold two software patents and a provisional application. I have published dozens of technical articles and have been a tutorial speaker at diverse conferences. I have mentored and advised thesis research, undergraduate capstone projects, and students participating in programming contests. As a practitioner, I have worked as a software engineer and consultant and participated as CTO of two startup companies.

Current position (1)

Assistant Professor

California State Polytechnic University

Degrees (1)

Computer Science

Arizona State University

2009 to 2016

Presentations

Presentations (2)

Affect-Driven Self-Adaptation: A Step Forward in Human-Centered Software

This talk describes the fundamentals and a step-by-step approach to jumpstart the development of affect-driven self-adaptive systems. As fundamentals, it introduces concepts and mechanisms related to monitoring affect and detecting improvement opportunities, selecting a course of action, and effect changes. It describes a domain-specific architecture and well-documented process guidelines using software patterns.

Affective Computing: A Roadmap Through Approaches, Technologies, and Data Analysis

This talk provides a description and demonstration of devices and methodologies for automatically detecting affective states with a multimodal approach. It does not intend to present a comprehensive survey, but instead, a roadmap through the description and demonstration of a selection of devices and methodologies. It presents examples of data samples, collected in experimental studies, and discusses experiences using devices and methodologies in learning, entertainment, and healthcare scenarios.