People

Director

• • 

    Ali Sadeghi-Naini, PhD, PEng

    York Research Chair in Quantitative Imaging and Smart Biomarkers
    Dr. Sadeghi-Naini is an Associate Professor and York Research Chair in the Department of Electrical Engineering and Computer Science at Lassonde School of Engineering, York University. He is also a cross-appointed Scientist at Sunnybrook Research Institute and Odette Cancer Centre, and a Member of Temerty Centre for AI Research and Education in Medicine in the Faculty of Medicine at University of Toronto. Dr. Sadeghi-Naini is recipient of numerous research awards and recognition including an Early Researcher Award from the Ontario Ministry of Colleges and Universities. The focus of his research program is to develop quantitative imaging and intelligent biomarker technologies for precision medicine and personalized therapeutics.

Postdoctoral Researchers

• • 

    Maryam Parsian

    Postdoctoral Fellow
    Maryam is working on biotechnology-related project development at Quantimb Lab.

Graduate Students

• • 

    Nasrin Sheibani

    PhD Student
    Nasrin is working on development of data-driven models for quantitative ultrasound imaging.
    Awards:
    -

• • 

    Nauman Bashir

    PhD Student
    Nauman is working on development of MRI deep analytic models for precision neuro-oncology.
    Awards:
    - Lassonde Research Photo Contest Prize, 2023.

• • 

    Abdullah Tauqeer

    MASc Student
    Abdullah is working on development of data-driven models for automated annotation of regions of interest in digital pathology.
    Awards:
    -

• • 

    Hassan Hamidi

    PhD Student
    Hassan is working on implementation of fairness in AI-assisted medical imaging.
    Awards:
    - VISTA PhD Scholarship, 2023-2027.

Alumni

• • 

    Reza Yaghoubi Emami

    Research Associate: 2020-2023
    Project: Development of a smart ultrasound system for cancer screening.

• • 

    Shirin Saednia

    PhD Student: 2019-2022
    Project: Machine learning and digital histopathology analysis for tissue characterization and treatment response prediction in breast cancer.
    Awards:
    - Parya Trillium Foundation Scholarship, 2019.
    Patents:
    - Deep learning of digital pathology images of pre-treatment tumor biopsies to predict breast cancer response to chemotherapy, US63/495390, 2023.

• • 

    Seyed Ali Jalalifar

    PhD Student: 2018-2022
    Project: Machine learning and quantitative imaging for the management of brain metastasis.
    Awards:
    - Lassonde Graduate Entrance Scholarship, 2018.
    - Parya Trillium Foundation Scholarship, 2019.
    - Mitacs Accelerate Internship, 2020.
    Patents:
    - System and methods for automatic assessment of radiotherapy outcome in tumours using longitudinal tumour segmentation on serial MRI, US63/352881 & PCT/CA2023/050840, 2022.

• • 

    Mohamed Aboutaleb

    MASc Student: 2020-2022
    Project: An enhanced method for full-inversion-based ultrasound elastography of the liver.

• • 

    Niusha Kheirkhah

    PhD Student (Western): 2018-2022
    Project: A novel ultrasound elastography technique for evaluating tumor response to neoadjuvant chemotherapy in patients with locally advanced breast cancer.

• • 

    Hamidreza Taleghamar

    MSc Student: 2019-2021
    Project: Machine learning strategies to analyze quantitative ultrasound multi-parametric images for prediction of therapy response in breast cancer patients.
    Awards:
    - Faculty of Graduate Studies Exceptional Thesis Prize, 2021. (Awarded to up to three master’s theses annually across the university)
    Patents:
    - Deep learning of quantitative ultrasound multi-parametric images at pre-treatment to predict breast cancer response to chemotherapy, US63/302492 & PCT/CA2023/050074, 2022.
    - Systems and methods for characterizing intra-tumor regions on quantitative ultrasound parametric images to predict cancer response to chemotherapy at pre-treatment, US63/215353 & PCT/CA2022/051020, 2021.

• • 

    Yaniv Khaslavsky

    Undergrad Research Student: 2020-2021
    Project: Accelerated generation of quantitative ultrasound envelope statistics parametric maps.
    Awards:
    - NSERC Undergraduate Student Research Award (USRA), 2021.
    - Plenary Presentation Award, Lassonde Undergraduate Research Conference, 2021.

• • 

    Ameer Zaghi

    Undergrad Research Student: 2019-2021
    Project: Automated annotation of medical imaging data.

• • 

    Majid Jaberipour

    Postdoctoral Fellow: 2019-2021
    Project: Machine learning and quantitative imaging to predict radiotherapy outcome in brain metastasis.

• • 

    Mohammad Sotoudehfar

    Undergrad Research Student: 2020
    Project: Automatic segmentation of breast tumours in ultrasound images.
    Awards:
    - NSERC Undergraduate Student Research Award (USRA), 2020.
    - Best Presentation Award, Lassonde Undergraduate Research Conference, 2020.

• • 

    Shahin Ebrahimi

    Postdoctoral Fellow: 2019-2020
    Project: Low-complexity methods for deep learning of ultrasound RF signal to characterize breast lesions.

• • 

    Zahra Zeinolabedin Rafi

    Undergrad Research Student: 2019-2020
    Project: Automated annotation of medical imaging data.
    Awards:
    - NSERC Undergraduate Student Research Award (USRA), 2020.

• • 

    Hadi Moghadas

    Postdoctoral Fellow: 2018-2020
    Project: Smart quantitative computed tomography (qCT) for personalized breast cancer therapeutics.

• • 

    Elham Karami

    Postdoctoral Fellow (Sunnybrook): 2017-2019
    Project: Quantitative MRI biomarkers to predict local control in brain metastasis after stereotactic radiotherapy

• • 

    Parya Jafari

    MESc Student (Western): 2017-2019
    Project: Development of heterogeneous patient-specific biomechanical models of the lung for tumour motion compensation and effective lung radiation therapy
    Awards:
    - Finalist for IEEE EMBS student paper competition, 2019.