Pierre Boulanger, Ph.D., P.Eng

Professor, Faculty of Science - Computing Science


Professor, Faculty of Science - Computing Science
(780) 492-3031
411 Athabasca Hall
9119 116 St NW
Edmonton AB
T6G 2E8


Area of Study / Keywords

Virtual and Augmented Reality Medical Imaging Machine Learning for Biosensors Quantum Computing


 Dr Boulanger cumulates more than 40 years of experience in 3D computer vision, rapid product development, and the applications of virtual reality systems to medicine and industrial manufacturing. Dr Boulanger was a senior research officer for 18 years at the National Research Council of Canada. His primary research interest was 3D computer vision, rapid product development, and virtualised reality systems. He has a double appointment as a professor at the University of Alberta Department of Computing Science and the Department of Radiology and Diagnostic Imaging. He is currently the Director of the Advanced Human-Computer Interface Laboratory (AHCI) and the Scientific Director of the SERVIER Virtual Cardiac Centre. In 2013, Dr Boulanger was awarded the CISCO chair in healthcare solutions, a ten-year investment by CISCO Systems to develop new IT technologies for healthcare in Canada. The chair ended in March 2022, and most of the MedRoad activities will be transferred to Naiad Lab Inc, where I will continue my research work as the CTO of the company. Naiad Lab Inc is a start-up dedicated to using advanced technology solutions to enhance our clientele's health and quality of life worldwide and to commercialize the technologies developed during the CISCO chair. A final report on the activities of the CISCO Chair can be found in Report-2022.

Personal webpage


His research topics include developing new telemedicine techniques, patient-specific modelling using sensor fusion, and applying telepresence technologies to medical training, simulation, and collaborative diagnostics. I am also working on applying Quantum Computing to image processing algorithms. His work has contributed to gaining international recognition in this field, publishing more than 390 scientific papers, and collaborating with numerous universities, research labs, and industrial companies worldwide. In addition, he is on the editorial board of two major academic journals. Dr. Boulanger is also on many international committees and lectures on computational medicine and augmented reality systems.


Introduction to Virtual/Augmented Reality and Telepresence

 Virtual and augmented reality can provide an immersive environment for testing scenarios, games, and training. For example, manufacturing and engineering tasks, medical planning and training, art and design, rehabilitation, Physics, Biology and Chemistry concept exploration, and many others can benefit from a virtual reality environment. This course focuses on the challenges of setting up a user-friendly virtual reality scene where users can interact intuitively and naturally. Interactive techniques and sensor-based devices, such as haptic and head-mount displays, create a virtual environment for scientific analysis, visualisation exploration, and Tele-presence. How mobile users can participate in these applications will be discussed.

Quantum Computing for Computer Scientists

 This course introduces the theory and applications of quantum information and quantum computation from the computer science perspective. The course will cover classical information theory, compression of quantum information, quantum entanglement, efficient quantum algorithms, quantum error-correcting codes, fault-tolerant quantum computation, and quantum machine learning. The course will also cover quantum computation physical implementations into real quantum computers. We also explore programming languages using the real-world utilising state-of-the-art quantum technologies through the IBM Q Experience, TensorFlow Quantum, Microsoft Quantum Development Kit, and D-Wave.

 Deep Learning for Medical Image Analysis

 The past twenty years of clinical applications of multimodal medical imaging (CT, MRI, US, PET/CT/MR, etc.) have revolutionised how medicine is practised today by improving disease diagnostics and treatment. In the last decade, Deep Neural Networks (DNN) usage in this field has opened new doors to process those images, allowing automatic segmentation, multimodal sensor fusion and registration, and computer-aided diagnosis. This course will review the various DNN architectures found in the literature and explore their practical clinical applications. Coursework includes homework, programming assignments, reading, and discussion of research papers, presentations, and a final project.

Introduction to GPU Programming

 This course introduces how to program heterogeneous parallel computing systems such as GPUs. The course covers CUDA language, functionality, and maintainability of GPU, how to deal with scalability, portability issues, technical subjects, parallel programming API, tools and techniques, principles and patterns of parallel algorithms, processor architecture features, and constraints.

Introduction to Computer Graphics

CMPUT 411/511 is an introductory course to computer graphics concentrating on two- and three-dimensional graphics and interactive techniques. It focuses on fundamental concepts and techniques and their relationship to multiple graphic problem domains (rendering, animation, geometry, imaging).

For a complete list of course see the AHCI website


CMPUT 411 - Introduction to Computer Graphics

2D and 3D transformation; 3D modeling and viewing; illumination models and shading methods; texture mapping; ray tracing. Prerequisites: CMPUT 204 or 275, 301; one of CMPUT 340, 418 or equivalent knowledge, and MATH 214.

CMPUT 511 - Topics In Computer Science

CMPUT 604 - Topics in Computing Science

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