Alvaro Joffre Uribe Quevedo is an Associate Professor in the Faculty of Business and Information Technology at Ontario Tech University where he teaches courses associated with immersive technologies, computer graphics, and game engines in the Game Development and Interactive Media Undergraduate program. He also teaches immersive technology courses in the Computer Science graduate programs and conducts research in Virtual Reality and Human-Computer Interactions. Dr. Uribe Quevedo received his bachelor's degree in Mechatronics Engineering from Universidad Militar Nueva Granada in Bogotá, Colombia in 2003. After receiving his bachelor’s degree, he worked developing software and simulations for engineering and medical applications. In 2008, Dr. Uribe Quevedo completed his Master’s in Mechanical Engineering, and in 2011 his Doctoral degree in the same field and institution, the Universidade Estadual de Campinas in Campinas, São Paulo, Brazil. In 2012, he became an Assistant Professor at Universidad Militar Nueva Granada teaching in the Industrial Engineering and Multimedia Engineering undergraduate programs, as well as in the Master's of Mechatronics Engineering. During his tenure at Universidad Militar Nueva Granada, Dr. Uribe Quevedo's research focused on immersive technologies and medical applications. In 2015 he became a Post-Doctoral fellow at the Games Institute at the University of Waterloo in Waterloo, ON, Canada, conducting research on the effects of games in medical training as part of the IMMERSe network jointly working with Ontario Tech University.

​

His research interests are in virtual reality to develop applications and assessment tools to tailor the immersion and interactions towards effective inclusive and meaningful experiences.

Currently, Dr. Uribe Quevedo has established working partnerships with researchers and industry partners in the fields of training and healthcare employing immersive technologies.

​

His current research program focuses on VR usability to create tailored and effective experiences for task complation in training scenarios.

​

Member of the MaxSIM Health Research Group since 2019.

IEEE member

ACM member

​

https://orcid.org/0000-0002-6728-3848

​

​

​

​