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.

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.

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:
      -

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.

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:
      -

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.

Hassan Hamidi

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

Undergraduate Students
    • Shaun Francis

      BSc Student
      Shaun is working on development of a high-throughput framework for automatic tracking of tumor cells on microscopy videos.
      Awards:
      - Lassonde Undergraduate Research Award (LURA), 2024.

Shaun Francis

BSc Student
Shaun is working on development of a high-throughput framework for automatic tracking of tumor cells on microscopy videos.
Awards:
- Lassonde Undergraduate Research Award (LURA), 2024.

Alumni
    • Reza Yaghoubi Emami

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

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.

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.

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.

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.

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.

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.

Yaniv Khaslavsky

Undergrad Research Assistant: 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.

Ameer Zaghi

Undergrad Research Assistant: 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.

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.

Mohammad Sotoudehfar

Undergrad Research Assistant: 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.

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.

Zahra Zeinolabedin Rafi

Undergrad Research Assistant: 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.

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

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.

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.