Research
My research combines quantitative medical imaging (ultrasound and MRI), machine learning, and image analysis, with applications in liver and fetal brain imaging. My work spans elastography, image reconstruction, registration, and segmentation. I pursue AI research with an uncompromising focus on data quality and rigorous validation of new ideas. See my papers here.
Experience
University of British Columbia
Research Associate · Ph.D. in Electrical & Computer Engineering, 2016–2022.
Robotics and Control Laboratory (RCL) · Supervisor: Prof. Septimiu (Tim) Salcudean.
Boston Children’s Hospital / Harvard Medical School
Postdoc, 2024–2025 · Fetal brain imaging.
Computational Radiology Laboratory (CRL) · PI: Prof. Davood Karimi.
University of Alberta
M.Sc. in Electrical & Computer Engineering, 2014–2016.
Advanced Alarm Management and Design (AAMD) · Supervisor: Prof. Tongwen Chen.
B.Sc. in Electrical Engineering, 2010–2014 · With Distinction.
Awards
IEEE UFFC Outstanding Paper Award 3-D Ultrafast Shear Wave Absolute Vibro-Elastography Using a Matrix Array Transducer
IEEE TUFFC, 2023.
MICCAI MedIA Best Paper Award Accurate and robust deep learning-based segmentation of the prostate clinical target volume in ultrasound images
Medical Image Analysis, 2019.
C.R. James Award for Best Master of Science Thesis — ECE, University of Alberta.
Ventures

Piko · Co-founder & CSO
Translating AI ideas into practical ML and data systems for pet owners and local communities.
Coact · AI & Ultrasound Lead
Developing AI tools for object tracking and 3D ultrasound reconstruction, and supporting data acquisition for clinical applications. Our team completed UBC Venture Founder and is preparing for HATCH.

