Principal Investigator
|
Yiming Xiao, PhD, PEng, SM IEEE
Associate Professor, Department of Computer Science and Software Engineering Concordia University Research Chair in Intelligent and Intuitive Surgical Technology Junior 1 Research Scholar, Fonds de Recherche du Québec - Santé Research member, School of Health & Applied AI Institute Concordia University Dr. Yiming Xiao is a medical technology researcher. In his research, he combines novel techniques in medical imaging principles, computer vision, and machine learning to improve the efficiency and accuracy of image-based diagnosis and medical procedures for the brain and body. He obtained his Ph.D. in Biomedical Engineering at McGill University in 2016 on the surgical treatment of Parkinson's disease. Soon after, he joined the PERFORM Centre as a PERFORM postdoc fellow. From 2018-2020, he was a CIHR and BrainsCAN postdoctoral researcher at the Robarts Research Institute of Western University. He is the co-organizer of 2023 and 2024 MICCAI workshop on Machine Learning in Clinical Neuroimaging (MLCN), 2020 MICCAI Learn2Reg Image registration Challenge, CuRIOUS 2018, 2019 and 2022 MICCAI Challenge, and the joint AECAI-CereVis 2018 MICCAI Workshop on medical data visualization. He is also the area chair of MICCAI 2024 and 2025. |
Prospective students
Health-X Lab is looking for motivated graduate students to join the lab. There are a range of exciting projects in computational neuroimaging (interface of AI and neuroimaging), image-guided surgery, and computer-assisted diagnosis. You will be exposed to advanced medical imaging technology, artificial intelligence methods, augmented/virtual reality, and close collaboration with clinicians. For those who are interested, please forward your complete CV, the transcript, and a brief introduction of yourself to yiming.xiao-AT-concordia.ca. While image processing and medical AI are crucial themes of Health-X, we strongly encourage candidates who are interested in medical VR/AR development (previous experience with Unity/UNREAL and game development will be an asset) to apply.
We also welcome undergraduate students with computational (and physiological) backgrounds to participate in various aspects research activities at the lab. Similar to the prospective graduate students, please forward your CV, transcript and your research interests to yiming.xiao-AT-concordia.ca.
For prospective postdoc researchers, please forward your CV, research statement and references to the same email.
Health-X Lab is strongly committed to diversity within its community and especially welcomes applications from racialized persons/persons of colour, women, Indigenous/ Aboriginal People of North America, persons with disabilities, LGBTQ persons, and others who may contribute to the further diversification of ideas. For candidates who have faced personal challenges that affected their academic achievements and research productivity, we will take full consideration of these factors when assessing the applications.
We also welcome undergraduate students with computational (and physiological) backgrounds to participate in various aspects research activities at the lab. Similar to the prospective graduate students, please forward your CV, transcript and your research interests to yiming.xiao-AT-concordia.ca.
For prospective postdoc researchers, please forward your CV, research statement and references to the same email.
Health-X Lab is strongly committed to diversity within its community and especially welcomes applications from racialized persons/persons of colour, women, Indigenous/ Aboriginal People of North America, persons with disabilities, LGBTQ persons, and others who may contribute to the further diversification of ideas. For candidates who have faced personal challenges that affected their academic achievements and research productivity, we will take full consideration of these factors when assessing the applications.
Useful resources
7 reasons to study in Montreal
Quebec Merit Scholarship Program for Foreign Nationals (PBEEE)
Concordia University Entrance Awards
Scholarships at the Fonds de recherche du Québec - Nature et technologies (FRQNT)
Scholarships at Natural Sciences and Engineering Research Council of Canada (NSERC)
Quebec bio-imaging network (QBIN) scholarships
NSERC Undergraduate Research Awards
Quebec Merit Scholarship Program for Foreign Nationals (PBEEE)
Concordia University Entrance Awards
Scholarships at the Fonds de recherche du Québec - Nature et technologies (FRQNT)
Scholarships at Natural Sciences and Engineering Research Council of Canada (NSERC)
Quebec bio-imaging network (QBIN) scholarships
NSERC Undergraduate Research Awards
Lab members
Graduate trainees
Tristan Manni-Mirolla
MSc Student |
Emmanuel Ajaero
MSc Student |
Taha Koleilat
PhD Student |
Erin Rainville
MSc Student |
Soorena Salari
Ph.D. Student |
Adam Graves
Ph.D. Student |
David Perron
MSc Student |
Melissa Ananian
MSc Student |
Research Assistants and Associates
Shuo Feng
Research Assistant |
Previous members
Postdoctoral Associate
Maryam Alizadeh, Postdoc Associate, 09/2022 ~ 08/2024
Graduate trainees
Pascal Spiegler, MSc Student, 09/2023 ~ 08/2025, now Mitacs Intern with Alpha Tau Medical
Thesis: New paradigms for radiological segmentation with AI foundation models: automatic prompting and interactive VR Agent Design
Hafsa Moontari Ali, PhD candidate, 09/2021 ~ 12/2024
Thesis: Hyperspectral imaging in biomedical applications
Arash Harirpoush, MSc Student, 09/2022 ~ 12/2024, now Data Science Analyst at Sobeys
Thesis: Optimization of pre-operative planning in minimally invasive thoracic surgeries with deep-learning-based patient-specific 3D modelling and intuitive VR interaction.
Christopher Neves, MSc Student, 09/2022 ~ 12/2024, now Data Analyst at FlightHub
Thesis: Novel deep learning techniques for the detection and classification of neurodegenerative diseases using resting-state electroencephalography
Bahar Jahani, MSc Student, 01/2022 ~ 08/2024, now Game developer at Trebuchet
Thesis: Mobile Augmented Reality Application for the Education of Neurovascular System
Zirui Qiu, MSc Student, 09/2022 ~ 07/2024, now Developer at Coohom
Thesis: Enhancing Visual Interpretability in Computer-Assisted Radiological Diagnosis: Deep Learning Approaches for Chest X-Ray Analysis
Simon Crete, MSc Student, 09/2021 ~ 07/2024, now Machine Learning Engineer at Wearm.ai
Thesis: MRI-based brain age estimation using supervised contrastive learning
Reihaneh Teimoori, MSc Student, 09/2021 ~ 04/2024, now Machine Learning Scientist at Prenuvo
Thesis: Deep learning-based brain ventricle segmentation in Computed Tomography using domain adaptation
Amirhossein Rasoulian, MSc Student, 01/2022 ~ 12/2023, now Image analysis software developer at NeuroRX Research
Thesis: Cerebrovascular Pathology Segmentation Using Weakly Supervised Deep Learning Methods
Parinaz Roshanzamir, MSc Student, 01/2022 ~ 12/2023, now Software Engineer at Zetane
Thesis: Visualization, Quantification, and Analysis of Inter-rater Variability to Enhance Deep learning-based Medical Image Segmentation of Parspinl Muscles
Haitham Abdelsalam, Graduate Research Assistant, 01/2024 ~ 08/2024
Thesis: New paradigms for radiological segmentation with AI foundation models: automatic prompting and interactive VR Agent Design
Hafsa Moontari Ali, PhD candidate, 09/2021 ~ 12/2024
Thesis: Hyperspectral imaging in biomedical applications
Arash Harirpoush, MSc Student, 09/2022 ~ 12/2024, now Data Science Analyst at Sobeys
Thesis: Optimization of pre-operative planning in minimally invasive thoracic surgeries with deep-learning-based patient-specific 3D modelling and intuitive VR interaction.
Christopher Neves, MSc Student, 09/2022 ~ 12/2024, now Data Analyst at FlightHub
Thesis: Novel deep learning techniques for the detection and classification of neurodegenerative diseases using resting-state electroencephalography
Bahar Jahani, MSc Student, 01/2022 ~ 08/2024, now Game developer at Trebuchet
Thesis: Mobile Augmented Reality Application for the Education of Neurovascular System
Zirui Qiu, MSc Student, 09/2022 ~ 07/2024, now Developer at Coohom
Thesis: Enhancing Visual Interpretability in Computer-Assisted Radiological Diagnosis: Deep Learning Approaches for Chest X-Ray Analysis
Simon Crete, MSc Student, 09/2021 ~ 07/2024, now Machine Learning Engineer at Wearm.ai
Thesis: MRI-based brain age estimation using supervised contrastive learning
Reihaneh Teimoori, MSc Student, 09/2021 ~ 04/2024, now Machine Learning Scientist at Prenuvo
Thesis: Deep learning-based brain ventricle segmentation in Computed Tomography using domain adaptation
Amirhossein Rasoulian, MSc Student, 01/2022 ~ 12/2023, now Image analysis software developer at NeuroRX Research
Thesis: Cerebrovascular Pathology Segmentation Using Weakly Supervised Deep Learning Methods
Parinaz Roshanzamir, MSc Student, 01/2022 ~ 12/2023, now Software Engineer at Zetane
Thesis: Visualization, Quantification, and Analysis of Inter-rater Variability to Enhance Deep learning-based Medical Image Segmentation of Parspinl Muscles
Haitham Abdelsalam, Graduate Research Assistant, 01/2024 ~ 08/2024
Undergradaute trainees
Li Wah D'Angelo, Research Assistant, 2024/10 ~ 2025/07
David Gu, Research Assistant, NSERC USRA 2024, 05/2024 ~ 08/2024; Research Assistant, 01/2025 ~ 04/2025
Alain Yalman, Research Assistant, 09/2022~12/2023; NSERC USRA 2023, 05/2023 ~ 08/2023;
Phuong Thao Quach, Concordia USRA, 05/2023 ~ 08/2023
Tongwei Zhang, Concordia USRA, 05/2022 ~ 08/2022
Terrance Liang, Concordia USRA, 05/2022 ~ 08/2022
Owen Hellum, Concordia USRA, 05/2023 ~ 08/2023, 05/2021 ~ 08/2021; Research Assistant, 05/2022~12/2022
David Gu, Research Assistant, NSERC USRA 2024, 05/2024 ~ 08/2024; Research Assistant, 01/2025 ~ 04/2025
Alain Yalman, Research Assistant, 09/2022~12/2023; NSERC USRA 2023, 05/2023 ~ 08/2023;
Phuong Thao Quach, Concordia USRA, 05/2023 ~ 08/2023
Tongwei Zhang, Concordia USRA, 05/2022 ~ 08/2022
Terrance Liang, Concordia USRA, 05/2022 ~ 08/2022
Owen Hellum, Concordia USRA, 05/2023 ~ 08/2023, 05/2021 ~ 08/2021; Research Assistant, 05/2022~12/2022