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Pierre Boulanger, Ph.D., P.Eng Professor
Director of the Advanced Human-Computer Interfaces Laboratory
University of Alberta
Athabasca Hall, Room 411 Edmonton, Alberta T6G 2E8, Canada
Email: pierreb@ualberta.ca |
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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
My
best furry friend Milou
A Short CV
Dr. Boulanger cumulates more than 38 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 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 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.
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 frequently lectures on computational medicine and augmented reality systems.
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
Tele-Immersion
Medical Imaging
Physical Modeling
Sensor-Based Geometric Modeling
Tele-Medicine
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
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
Heart and Stroke Foundation
NSERC Alliance
Alberta Innovate
NSERC Discovery Grant
NSERC Equipment Grant
Teaching
In Fall 2022, I am teaching Introduction to GPU Programming and Introduction to Virtual/Augmented Reality and Telepresence
.
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 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 introduces scientists, engineers, and practitioners in medicine to data visualization fundamentals.
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 as telesurgery and surgical simulation. In addition, this course addresses students with interests in robotics, virtual reality, or computer-integrated surgical systems.
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 summarizes geometric processing methods, filtering, re-sampling point models, and physical modelling.
In recent years, sensors and algorithms for three-dimensional (3D) imaging and modelling of natural 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 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 analyze 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.
The course deals with computer technology's moral, legal, and social issues. 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 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. Interactive techniques and sensor-based devices, such as haptic and head-mount displays, create 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 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 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
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
Shadan Golestan-Irani, Ph.D. CS,
Optimal Sensor Placement for Activity Recognition
Master Students
Scott Assen, MSc CS, Early Detection of Pancreatic Cancer
in CT
Technical Support
Michael Feist, 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
Esmatullah Naikyar, Project management and business development for the MedROAD Project
Current Collaborations
TeleMED
Diagnostic Management Inc.
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
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 June 2022