Faculty profile

Ali Sadeghi-Naini

ResearcherElectrical Engineering & Computer ScienceYork University

This profile is built from public research funding records (CIHR, NSERC and SSHRC) and PubMed. We have not imported them from a York University directory, so their courses may be missing. Find their university profile.

Ali Sadeghi-Naini

Researcher

Electrical Engineering & Computer Science

Engineering

York University

Toronto, Ontario, Canada

Supervision signals

Has led research grants, which requires an independent research appointment. Ask their department whether they supervise graduate students.
18 publications in the last five years, latest in 2026.
Senior (last) author on 11 recent papers, a sign of leading a research group.
Principal investigator on 2 research grants (2 NSERC), most recently in 2024.

These signals come from public records, including CIHR, NSERC and SSHRC funding decisions. Ask the professor or the graduate program whether they are taking new students.

Academic metrics

Publications

344

Citations

Collaborators

Grants

Publications by year

Counts cover the publications linked to this profile. Citations and the h-index appear when the source records them.

Profiles and links

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Signals and details

Research

quantitative ultrasound imaging elastography noninvasive tissue characterization medical image processing and analysis machine learning deep learning image-guided cancer therapeutics breast cancer

Latest papers

AI-enabled RF data synthesis for breast ultrasound: efficacy in quantitative ultrasound tissue characterization.
Scientific reports · 2026 · senior author
Longitudinal assessment of radiosurgery response in small brain metastases: AI-driven precision tumor segmentation and monitoring on serial MRI.
Medical physics · 2026 · senior author
Attention-Guided Deep Learning of Chemical Exchange Saturation Transfer Magnetic Resonance Imaging to Differentiate Between Tumor Progression and Radiation Necrosis in Brain Metastasis.
International journal of radiation oncology, biology, physics · 2026 · senior author

All 69 publications

Latest funding

Smart ultrasound platform for tissue characterization and monitoring
NSERC · 2024 · Principal investigator
$48,000
A Low-Cost Accessible Smart Platform for Determination of Homologous Recombination Deficiency (HRD) in Ovarian Tumours Using Routine Histology Slides
SSHRC · 2024 · Co-investigator
$125,000
Training in Applied Biotechnology for Environmental Sustainability (TABES)
NSERC · 2021 · Co-investigator
$1,049,240

All 7 grants and awards

69 publications.

AI-enabled RF data synthesis for breast ultrasound: efficacy in quantitative ultrasound tissue characterization.

Sheibani-Asl N, Osapoetra LO, Czarnota GJ, Sadeghi-Naini A

Scientific reports2026Senior author

DOI: 10.1038/s41598-026-43319-9 PMID: 41795012

Longitudinal assessment of radiosurgery response in small brain metastases: AI-driven precision tumor segmentation and monitoring on serial MRI.

Bhatti NB, Stewart J, Chugh B, Detsky J, Tseng CL, Heyn C, Maralani PJ, Sahgal A, Soliman H, Sadeghi-Naini A

Medical physics2026Senior author

DOI: 10.1002/mp.70273 PMID: 41527513

Attention-Guided Deep Learning of Chemical Exchange Saturation Transfer Magnetic Resonance Imaging to Differentiate Between Tumor Progression and Radiation Necrosis in Brain Metastasis.

Bhatti NB, Young D, Lam WW, Chan RW, Maralani PJ, Sahgal A, Soliman H, Stanisz GJ, Sadeghi-Naini A

International journal of radiation oncology, biology, physics2026Senior author

DOI: 10.1016/j.ijrobp.2025.10.040 PMID: 41348074

Validation of a Quantitative Ultrasound Texture Analysis Model for Early Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer: A Prospective Serial Imaging Study

Moore-Palhares D, Sannachi L, Chan AW, Dasgupta A, DiCenzo D, Gandhi S, Pezo R, Eisen A, Warner E, Wright F

Cancers20255 citations

DOI: 10.3390/cancers17152594

Quantitative ultrasound imaging for predicting response and guiding personalized neoadjuvant chemotherapy in breast cancer: randomized phase 2 clinical trial results

Moore-Palhares D, Alberico D, Chan AW, DiCenzo D, Sannachi L, Dasgupta A, Yip J, Pena MLA, Gandhi S, Pezo R

npj Precision Oncology20252 citations

DOI: 10.1038/s41698-025-01134-x

Validation of Quantitative Ultrasound and Texture Derivative Analyses-Based Model for Upfront Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer

Chan AW, Sannachi L, Moore-Palhares D, Dasgupta A, Gandhi S, Pezo R, Eisen A, Warner E, Wright FC, Hong NL

Journal of Imaging20252 citations

DOI: 10.3390/jimaging11040109

Detection, localization, and staging of breast cancer lymph node metastasis in digital pathology whole slide images using selective neighborhood attention-based deep learning.

Tauqeer A, Asif A, Sadeghi-Naini A

Scientific reports2025Senior author

DOI: 10.1038/s41598-025-21787-9 PMID: 41162515

Quantitative ultrasound radiomics guided adaptive neoadjuvant chemotherapy in breast cancer: early results from a randomized feasibility study

Dasgupta A, DiCenzo D, Sannachi L, Gandhi S, Pezo RC, Eisen A, Warner E, Wright FC, Look-Hong N, Sadeghi-Naini A

Frontiers in Oncology20249 citations

DOI: 10.3389/fonc.2024.1273437

A hierarchical self-attention-guided deep learning framework to predict breast cancer response to chemotherapy using pre-treatment tumor biopsies.

Saednia K, Tran WT, Sadeghi-Naini A

Medical physics2023Senior author

DOI: 10.1002/mp.16574 PMID: 37403567

Predicting Patterns of Distant Metastasis in Breast Cancer Patients following Local Regional Therapy Using Machine Learning.

Shiner A, Kiss A, Saednia K, Jerzak KJ, Gandhi S, Lu FI, Emmenegger U, Fleshner L, Lagree A, Alera MA, Bielecki M, Law E, Law B, Kam D, Klein J, Pinard CJ, Shenfield A, Sadeghi-Naini A, Tran WT

Genes2023

DOI: 10.3390/genes14091768 PMID: 37761908

Smart ultrasound platform for tissue characterization and monitoring

Principal investigatorNSERC2024Discovery Grants Program - Individual

Principal investigators: Sadeghi-Naini, Ali

Keywords: quantitative ultrasound imaging; elastography; noninvasive tissue characterization; medical image processing and analysis; machine learning; deep learning; image-guided cancer therapeutics; breast cancer

$48,000

A Low-Cost Accessible Smart Platform for Determination of Homologous Recombination Deficiency (HRD) in Ovarian Tumours Using Routine Histology Slides

Co-investigatorSSHRC2024New Frontiers in Research Fund - Exploration

Principal investigators: Akbari, Mohammad Reza

$125,000

Training in Applied Biotechnology for Environmental Sustainability (TABES)

Co-investigatorNSERC2021Collaborative Research and Training Experience

Principal investigators: Brar, Satinder Kaur SK

Keywords: applied biotechnology; bioprocesses; bioproducts; biorefinery; fermentation; microorganisms; policy; residues; sustainability; value-addition

$1,049,240

Ultrasound Platform for A Priori Therapy Response Prediction

Co-investigatorCIHR2018Collaborative Health Research Projects (NSERC partnered)

Principal investigators: Kolios, Michael C; Trudeau, Maureen E; Czarnota, Gregory J

Keywords: Cancer Imaging; Cancer Treatment Monitoring; Machine Learning; Photoacoustic Imaging; Therapy Response; Utrasound Imaging

$453,500

Quantitative Ultrasound for A Priori Breast Cancer Chemoerthapy Response Prediction

Co-investigatorCIHR2018Project Grant

Principal investigators: Czarnota, Gregory J; Kolios, Michael C

Keywords: Chemotherapy; Quantitative Ultrasound; Response Prediction; Ultrasound

$598,995

Quantitative Ultrasound for A Priori Breast Cancer Chemotherapy Response Prediction

Co-investigatorCIHR2017Project Grant

Principal investigators: Czarnota, Gregory J; Kolios, Michael C

Keywords: Chemotherapy; Quantitative Ultrasound; Response Prediction

$100,000

Development of ultrasound-based integrated techniques for biomechanical and bioacoustical characterization of tissue

Principal investigatorNSERC2016Discovery Grants Program - Individual

Principal investigators: Sadeghi-Naini, Ali

$189,000

From CIHR, NSERC and SSHRC funding decisions: CIHR since 2008, NSERC since 1991 and SSHRC since 1998, including their latest published competition results.

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Ali Sadeghi-Naini

Research

Latest papers

Latest funding

AI-enabled RF data synthesis for breast ultrasound: efficacy in quantitative ultrasound tissue characterization.

Longitudinal assessment of radiosurgery response in small brain metastases: AI-driven precision tumor segmentation and monitoring on serial MRI.

Attention-Guided Deep Learning of Chemical Exchange Saturation Transfer Magnetic Resonance Imaging to Differentiate Between Tumor Progression and Radiation Necrosis in Brain Metastasis.

Validation of a Quantitative Ultrasound Texture Analysis Model for Early Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer: A Prospective Serial Imaging Study

Quantitative ultrasound imaging for predicting response and guiding personalized neoadjuvant chemotherapy in breast cancer: randomized phase 2 clinical trial results

Validation of Quantitative Ultrasound and Texture Derivative Analyses-Based Model for Upfront Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer

Detection, localization, and staging of breast cancer lymph node metastasis in digital pathology whole slide images using selective neighborhood attention-based deep learning.

Quantitative ultrasound radiomics guided adaptive neoadjuvant chemotherapy in breast cancer: early results from a randomized feasibility study

A hierarchical self-attention-guided deep learning framework to predict breast cancer response to chemotherapy using pre-treatment tumor biopsies.

Predicting Patterns of Distant Metastasis in Breast Cancer Patients following Local Regional Therapy Using Machine Learning.

Smart ultrasound platform for tissue characterization and monitoring

A Low-Cost Accessible Smart Platform for Determination of Homologous Recombination Deficiency (HRD) in Ovarian Tumours Using Routine Histology Slides

Training in Applied Biotechnology for Environmental Sustainability (TABES)

Ultrasound Platform for A Priori Therapy Response Prediction

Quantitative Ultrasound for A Priori Breast Cancer Chemoerthapy Response Prediction

Quantitative Ultrasound for A Priori Breast Cancer Chemotherapy Response Prediction

Development of ultrasound-based integrated techniques for biomechanical and bioacoustical characterization of tissue

Frequent collaborators

Maureen Trudeau

Arjun Sahgal

Nicole Look Hong

Andrea Eisen

Frances Wright

Abbas Samani

Eileen Rakovitch

Lee Chin

Rossanna Pezo

Daniel Moore Freitas Palhares

Martin Yaffe

Greg Stanisz

Gregory Czarnota

Alireza Sadeghian

Angus Lau

Amir Asif

Pejman Jabehdar Maralani

Stewart Gaede

Urban Emmenegger

Hassan Rivaz

Muriel Brackstone