Pierre Boulanger, Ph.D., P. Eng




Director of the Advanced Human-Computer Interfaces


Department of Computing Science

University of Alberta


Athabasca Hall, Room 411

Edmonton, Alberta


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 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 commercialise the technologies developed during the CISCO chair. A final report on the activities of the CISCO Chair can be found in Report-2022.


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. His work has contributed to gaining international recognition in this field, publishing more than 400 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.

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 editorial board of the Journal of Radiology

Member of the editorial board of the Journal SENSORS

Review Editor of Frontier in Virtual Reality

Member of the CIHR Reviewers

Member of the University of Alberta Ethics Committee

Member of the Faculty of Science IT Committee

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

Member of FQRS Selection Committee for Artificial Intelligence and Health Cluster


Current Grants


Heart and Stroke Foundation

NSERC Alliance

Alberta Innovate

NSERC Discovery Grant





In Winter 2023, I am teaching Quantum Computing for Computer Scientists



Introduction to Computer Graphics

This course introduces 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, 2D transformations, 3D transformations, modelling and viewing, hidden-line and hidden-surface removal, illumination and shading models, morphing, etc., warping, texture mapping, raytracing, radiosity, and introduction to animation.

Introduction to Multimedia Technology

This course introduces 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 effectively understanding and using the vast amount of information produced by supercomputers, sensors, and extensive simulations. By its very nature, visualisation 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, visualisation will be among our most essential tools. This course introduces scientists, engineers, and practitioners in medicine to data visualisation 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 modelling of virtual environments, control and stability issues, and medical applications such as telesurgery and surgical simulation. In addition, 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. Next, 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 summarises geometric processing methods, filtering, re-sampling point models, and physical modelling.


Sensor-Based Modeling

In recent years, sensors and algorithms for three-dimensional (3D) imaging and modelling of natural objects have received significant attention. The computer vision and graphics research communities are also increasingly used as tools for various applications in medicine, manufacturing, archaeology, and any field requiring 3D modelling of natural 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 modelling 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 analyse the GPU implementations of many of these algorithms.


Fundamentals of Medical Imaging


After reviewing one-dimensional signal processing and sampling, the course will first review the two-dimensional signal processing theory. We will then study four general medical imaging modalities: 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 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 rumours 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 their 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 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.


Current Graduate Students

I no longer take new graduate students!



Description automatically generated


Post-docs and Visiting Professors



None at the moment



Ph.D. Students


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.



Bernal Manzanilla, Ph.D. CS, Sparse Methods for Image Denoising and Feature Selection in Lung Ultrasound and Echocardiography



Master Students


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


Vishwajeet Uttam Ohal, MSc CS, Physics Based Neural Networks


Bharathvaj Kumba Mothilal, MSc CS, Classical Data Representation in Variational Quantum Classifiers




Naiad Lab Inc.

Big Data Analysis and AI Solutions


Spinoff of Dr. Boulanger Lab, Naiad Lab Inc. is committed to using the latest advancements in artificial intelligence to solve complex problems and drive innovation. We have a team of experienced and skilled professionals who specialize in Big Data Analytics, AI/ML, Signal Processing, and Computer Vision. We understand the unique challenges facing industries. Our team provides cutting-edge solutions based on big data analysis that help our clients make informed decisions and achieve their goals.


Esmatullah Naikyar, CEO in charge of project management and business development


Pierre Boulanger, CTO in Charge of R&D and new software development


Michael Feist, Chief Software Architect


Talwinder Punni, CFO in charge of marketing and financial management


Azal Mansouri, Business development manager




Current Collaborations


TeleMED Diagnostic Management Inc.

CISCO Systems

Siemens Canada

KUKA Robotics

InnovMetric Inc.


Smart Network

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)

Institute for Reconstructive Sciences in Medicine

Faculty of Rehabilitation Medicine

Medical Physics Division, Dept. Oncology, Cross Cancer Institute


Last Update April 2023