Pierre Boulanger, Ph.D., P.Eng


Professor and CISCO Chair in Healthcare


Director of the Advanced Human-Computer Interfaces


Department of Computing Science

University of Alberta


Athabasca Hall, Room 411

Edmonton, Alberta

T6G 2E8, Canada

Tel: (780) 492-3031
Fax: (780) 492-1071

Email: pierreb@ualberta.ca

Who am I?
Date of Birth: April 24, 1957


Hometown: Beautiful Quebec City

I am a man who loves life, music, fine food, and most importantly, ideas


A Short CV


Dr. Boulanger cumulates more than 36 years of experience in 3D computer vision, rapid product development, and the applications of virtual reality systems to medicine and industrial manufacturing. Dr. Boulanger worked for 18 years at the National Research Council of Canada as a senior research officer. His primary research interest was in 3D computer vision, rapid product development, and virtualized reality systems. He now 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 Man-Machine Interface Laboratory (AMMI) 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.


His research topics consist of developing new telemedicine techniques, patient-specific modeling using sensor fusion, and applying telepresence technologies to medical training, simulation, and collaborative diagnostics. His work has contributed to gaining international recognition in this field, publishing more than 450 scientific papers and collaborating with numerous universities, research labs, and industrial companies worldwide. He is on the editorial board of two major academic journals. Dr. Boulanger is also on many international committees and frequently lectures on computational medicine and augmented reality systems. He is also the CTO of Naiad Lab Inc., a start-up dedicated to using advanced technology solutions to enhance the health and quality of life of our clientele worldwide.

Full CV



University Education

Ph.D. in Electrical Engineering (1994), University of Montreal (Ecole Polytechnique), Department of Electrical Engineering, Montreal, Canada.

Advising Professor: Dr. P. Cohen

Dissertation: Multi-Scale Extraction of Geometric Elements

MSc in Physics (1982), Laval University, Department of Physics Quebec City, Canada.

Advising Professor: Dr. M. Baril

Dissertation: Multi-Passage Mass Spectrometer

BSc in Engineering Physics (1980), Laval University, Department of Engineering Physics, Quebec City, Canada.

Dissertation: Design and Construction of a Multi-Channel Analyzer for an Electron Spectrometer

Research Interests

3D Computer Vision

Neural Networks

Virtualized Reality Systems

Collaborative Virtual Environments


Medical Imaging

Physical Modeling

Sensor-Based Geometric Modeling


Sensor Fusion

Quantum Computing

Parallel Computing


Current and Past Projects


See Advance Human Computer Interfaces Laboratory Website



Publication List

The most recent publication list: Publications


Recent Committee Work


Director of the Advanced Human-Computer Interfaces Laboratory

Scientific Director of the SERVIER Virtual Heart Center

Chief Technology Officer of Naiad Lab Inc.

Member of the Scientific Advisory Board of CRIM

Member of the editorial board of the Journal of Computer Science and Informatics

Member of the editorial board of the Journal of Radiology

Member of the editorial board of the Revue SENSOR

Review Editor of Frontier in Virtual Reality

Member of the CIHR Reviewers

President of the FQRS Selection Committee for a Double Chair in AI and Medicine


Current Grants


CISCO Chair in Healthcare Solution

Heart and Stroke Foundation

NSERC Alliance

Alberta Innovate

NSERC Discovery Grant

NSERC Equipment Grant



In September 2021, I will be teaching Introduction to Virtual/Augmented Reality and Telepresence as well as Quantum Computing for Computer Scientist.


Introduction to Computer Graphics

This course is an introduction to computer graphics concentrating on two- and three-dimensional graphics and interactive techniques. Course topics include fundamental concepts of raster graphics, simple output primitives, windowing, clipping, and 2D transformations, 3D transformations, modeling and viewing, hidden-line and hidden-surface removal, illumination and shading models, morphing and warping, texture mapping, raytracing, radiosity, and introduction to animation.

Introduction to Multimedia Technology

This course is an introduction to basic principles and algorithms used in the current technologies of multimedia systems. One of these course goals is to give the student hands-on experience in multimedia data representation, compression, processing, and retrieval. The course also addresses sound transmission, music streaming, 2-D and 3-D graphics, image, and video. It also explores human perceptual problems associated with multimedia technologies.

Introduction to Scientific Visualization

Among the most significant scientific challenges of the 21st century will be to effectively understand and use the vast amount of information produced by supercomputers, sensors, and extensive simulations. By its very nature, visualization addresses the challenges created by such excess: too many data points, too many variables, too many time steps, and too many potential explanations. Thus, as we work to tame the accelerating information explosion and employ it to advance scientific, biomedical, and engineering research, visualization will be among our most essential tools. This course aims to introduce scientists, engineers, and practitioners in medicine to data visualization fundamentals.

Haptics Systems

This graduate-level course introduces haptics, focusing on teleoperated and virtual environments displayed through the sense of touch. Topics covered include human haptic sensing and control, design of haptic interfaces (tactile and force), haptics for teleoperation, haptic rendering and modeling of virtual environments, control and stability issues, and medical applications as telesurgery and surgical simulation. This course addresses students with interests in robotics, virtual reality, or computer-integrated surgical systems.

Point-Based Graphics


This course presents the latest research results in point-based computer graphics. After an overview of the critical research issues, we will discuss 3D scanning devices and novel concepts for the mathematical representation of point-sampled shapes. The course describes high-performance and high-quality point model rendering, including advanced shading, anti-aliasing, and transparency. It also offers efficient data structures for hierarchical rendering on modern graphics processors and summarizes geometric processing methods, filtering, re-sampling point models, and physical modeling.


Sensor-Based Modeling

In recent years, sensors and algorithms for three-dimensional (3D) imaging and modeling of real objects have received significant attention. In the computer vision and graphics research communities, they are also increasingly used as tools for various applications in medicine, manufacturing, archeology, and any field requiring 3D modeling of real environments. This course's primary goal is to present a general overview of digital 3D imaging technology from photogrammetry to tomographic systems and the various modeling techniques necessary to create 3D models of large and small structures compatible with multiple manufacturing and medical applications. 

Advanced Signal Processing for Computer Scientists

This class addresses the representation, analysis, and design of discrete-time signals and systems. The central concepts covered include discrete-time processing of continuous-time signals; decimation, interpolation, and sampling rate conversion; flow-graph structures for DT systems; time-and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters; linear prediction; discrete Fourier transform, FFT algorithm; short-time Fourier analysis and filter banks; Wavelet Transform; Wiener and Kalman Filters, and various applications. This course qualifies as a breadth requirement in theory.

Real-time Digital Signal Processing Using GPU

This class addresses the representation, analysis, and design of discrete-time signals and systems. The central concepts covered include discrete-time processing of continuous-time signals; decimation, interpolation, and sampling rate conversion; flow-graph structures for DT systems; time-and frequency-domain design techniques for recursive (IIR) and non-recursive (FIR) filters; linear prediction; discrete Fourier transform, FFT algorithm; short-time Fourier analysis and filter banks; multivariate techniques; Wavelet Transform; Cepstral analysis, Wiener and Kalman Filters, and various applications. We also discuss and analyze the GPU implementations of many of these algorithms.


Fundamentals of Medical Imaging


The course will first review the two-dimensional signal processing theory after reviewing one-dimensional signal processing and sampling. We will then study four general medical imaging modalities such as projection radiography, computed tomography, magnetic resonance imaging, and ultrasound. The goal will be to understand these modalities in terms familiar to engineers and physicists. Flexibility exists to vary each topic area's depth and penetration after determining the students' general background and experience.


Computers and Society


The course deals with moral, legal, and social issues of computer technology. Many ethical problems that did not exist before and are now omnipresent. For example, one can still get news from many mainstream sources that employ professional reporters who gather and validate the information before publishing. Unfortunately, numerous online news media deliver rumors and false news with dubious political agendas. Social media are a great way to interact with your family and friends, but they can threaten personal privacy. This course explores these issues and more.


Introduction to Human-Computer Interaction


This course introduces students to human-computer interaction topics, focusing on human capabilities and limitations, interaction design, current, and future interactive systems and devices, and evaluating its usability.


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 Virtual/Augmented Reality and Telepresence


Virtual reality 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. The use of interactive techniques and sensor-based devices, such as haptic and head-mount display, creates a virtual environment for scientific analysis, visualization exploration, and Tele-presence. How mobile users can participate in these applications will be discussed.


Quantum Computing for Computer Scientist


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 utilizing 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 revolutionized how medicine is practiced 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 to perform automatic segmentation, multimodal sensor fusion and registration, and computer-aided diagnosis. This course will review the various DNN architectures found in the literature and then explore its practical clinical applications. Course work includes homework, programming assignments, reading, and discussion of research papers, presentations, and a final project.


Current Graduate Students



Post-docs and Visiting Professors



None at the moment



Ph.D. Students


Hong Zu Li, Ph.D. CS, Continuous Heart Anomaly Detection System with Motion Artifacts Suppression


Thea Wang, Ph.D. CS, Training of Appendix Removal Procedure Using Proxy Haptic

Shrimanti Ghosh, Ph.D. CS, Anatomy Deformation Estimation During Gynecological Brachytherapy Treatments


Deepa Krishnaswamy, Ph.D. Medicine, A Novel 4D Semi-Automated Algorithm for Volumetric Segmentation in Echocardiography


Athar Mahmoudi-Nejad, Ph.D. CS, Optimizing the effect of VR-based exposure therapy using reinforcement learning based on the automatic recognition of stress levels from physiological measurements.


Mohsen Soltanpour, Ph.D. CS, Ischemic Stroke Lesion Segmentation from CT Perfusion Scans


Bernal Manzanilla, Ph.D. CS, Robotically Controlled Multi-View Ultrasound Imaging



Master Students


Farnoosh Fatemi Pour, MSc CS, Visualizing Neural Networks in Action Using Virtual Reality


Scott Assen, MSc CS, Early Detection of Pancreatic Cancer in CT



Technical Support


Xuping Fang, Programmer for the MedROAD Project


Michael Feist, Programmer for the MedROAD Project


Davinderjit Kaur, Programmer for the MedROAD Project


Michael Yogar, Programmer for the MedROAD Project


Talwinder Punni, UI Designer for the MedROAD Project


Azal Mansouri, UI Designer for the MedROAD Project



Administrative Support


Melanie Calvert, Deals with all admin issues in the lab


Esmatullah Naikyar, Project management and business development for the MedROAD Project






Current Collaborations


Naiad Lab, Inc.

CISCO Systems

Siemens Canada

InnovMetric Inc.


Smart Network

National University of Columbia, Colombia

UofA Department of Electrical and Computer Engineering

UofA Mechanical Engineering Department

CNRS/LIMSI Laboratory, Orsay, France

INSA, Ampere Laboratory, Lyon, France

UofA Department of Radiology and Diagnostic Imaging

UofA School of Public Health

Centre for Advancement of Surgical Education and Simulation (CASES), an Alberta Health Services (AHS)

Institute for Reconstructive Sciences in Medicine

Faculty of Rehabilitation Medicine

Surgical Simulation Research Lab

Medical Physics Division, Dept. Oncology, Cross Cancer Institute


Last Update July 2021