Prashant Pandey

About

About me

Hello there! I’m Prashant Pandey, an engineer and scientist working at the intersection of medicine and technology. I’m currently a Senior Staff Engineer at Stryker in Toronto, where I develop computer vision, machine learning and sensing technology for the MOLLI breast tumour localization system. I joined Stryker through its 2024 acquisition of MOLLI Surgical, where I was an Engineering Scientist and an inventor of MOLLI 2, a wire-free system for localizing breast tumours during surgery that was cleared by the US FDA in 2023. At MOLLI I also raised over $2M in competitive funding for an ultrasound-based tumour localization system, and I’m a named inventor on four pending patent families.

Previously, I completed my PhD in Biomedical Engineering at the Surgical Technologies Laboratory, under the supervision of Prof. Antony Hodgson and Dr. Pierre Guy at the University of British Columbia, Canada, as a Vanier Canada Graduate Scholar, and was shortlisted as one of UBC’s top graduating PhDs for the Governor General’s Gold Medal. My PhD thesis explored the use of ultrasound imaging for guiding orthopaedic surgeries (specifically pelvic fractures), for which I built and tested an integrated system for computer-assisted surgery which used imaging data from a conventional medical ultrasound probe and pose information from an optical tracking camera. In cadaver trials, the system placed screws as accurately as conventional X-ray guidance, without any radiation during surgery. Along the way I was the engineering lead for Retinographer, an AI-powered retinal screening project with Dr. Jovi Wong, and helped teach AI to medical students across Canada.

Prior to this, I did my undergraduate and Master’s in Engineering Science at the University of Oxford. For my MEng project, I worked with Prof. Eleanor Stride in the BUBBL group at the Oxford Institute of Biomedical Engineering on using injectable microbubbles to measure pressure inside the body with ultrasound.

Feel free to get in touch by email or on the other platforms linked on this page.

Experience

  1. Sep 2024 – Present

    Senior Staff Engineer

    Stryker · Toronto, Canada

    Joined Stryker through its acquisition of MOLLI Surgical, continuing to develop the MOLLI breast tumour localization portfolio.

    • Developing computer vision and machine learning systems that integrate the MOLLI localization system with Stryker’s open-field and endoscopic cameras.
    • Leading development of next-generation breast tumour localization devices from MOLLI Surgical’s portfolio, including ultrasound-based sensing technologies.
    • Software, machine learning and operating-system development for the next generation of the MOLLI localization system.
    • Computer vision
    • Machine learning
    • Ultrasound
    • Embedded software
    • Medical devices
  2. Nov 2021 – Sep 2024

    Engineering Scientist

    MOLLI Surgical · Toronto, Canada

    Toronto start-up developing wire-free magnetic localization of breast tumours for surgery; acquired by Stryker in 2024.

    • Inventor of MOLLI 2, a breast tumour localization system for use during surgery, cleared by the US FDA in January 2023.
    • Developed a machine learning pipeline that localizes magnetic markers from high-dimensional sensor data.
    • Raised over $2M in competitive funding (INOVAIT Pilot and Focus Funds) for an ultrasound-based surgical navigation system for locating tumours.
    • Named inventor on four pending patent families, including first-named inventor on neural-network rejection of spurious magnetic fields during marker localization.
    • Magnetic localization
    • Machine learning
    • Ultrasound
    • Sensor design
    • Medical devices
  3. May 2020 – Sep 2023

    Engineering Lead

    Retinographer · Toronto, Canada

    AI-powered retinal disease screening for rural and remote parts of Canada, developed with Dr. Jovi Wong.

    • Developed a deep learning model that detects disease in retinal fundus photographs more accurately than board-certified ophthalmologists (British Journal of Ophthalmology).
    • Developed hardware and algorithms to automate retinal screening with smartphone cameras, supported by a Joule Innovation Grant from the Canadian Medical Association.
    • Released a public prototype at retinographer.com.
    • Deep learning
    • Ophthalmology
    • Smartphone imaging
  4. Aug 2016 – Aug 2023

    Surgical Technologies Laboratory, University of British Columbia

    Vancouver, Canada

    • PhD Researcher (Vanier Scholar)Dec 2018 – Aug 2023
    • MASc ResearcherAug 2016 – Dec 2018

    Graduate research in computer-assisted orthopaedic surgery with Prof. Antony Hodgson and Dr. Pierre Guy, from ultrasound image analysis to a human cadaver trial of a complete navigation system.

    • Built NOFUSS, a radiation-free surgical navigation system using tracked ultrasound and automatic bone registration. In cadaver surgeries it matched fluoroscopic screw accuracy with no intraoperative radiation and a shorter median insertion time (IEEE TBME 2024).
    • Proposed and led BonUS, an eight-institution ultrasound bone segmentation dataset and benchmark (CAOS 2022; data).
    • Developed Shadow Peak real-time bone segmentation and automatic ultrasound–CT registration for the full pelvis (IJCARS 2018; code).
    • Ran a 21-participant user study that identified the most effective targeting displays for navigated screw insertion (Arch Orthop Trauma Surg 2023).
    • Research funded by an Orthopaedic Trauma Association Research Grant and a WorkSafeBC Research Grant.
    • Ultrasound
    • Image registration
    • Deep learning
    • Optical tracking
    • Cadaver studies
  5. Sep 2015 – Jun 2016

    MEng Researcher

    BUBBL Group, Institute of Biomedical Engineering, University of Oxford · Oxford, UK

    Investigated ultrasound and gas microbubbles for non-invasive blood pressure measurement (thesis).

    • Ultrasound
    • Microbubbles

Education

  1. Dec 2018 – Aug 2023

    PhD, Biomedical Engineering

    University of British Columbia · Vancouver, Canada

    Thesis: An integrated system for ultrasound-based surgical navigation of iliosacral screws

    Supervised by Prof. Antony Hodgson and Dr. Pierre Guy

    • Vanier Canada Graduate Scholar; Governor General’s Gold Medal finalist (see awards)
  2. Aug 2016 – Dec 2018

    MASc, Biomedical Engineering

    University of British Columbia · Vancouver, Canada

    Thesis: Real-time ultrasound bone segmentation and robust US-CT registration for surgical navigation of pelvic fractures

    Supervised by Prof. Antony Hodgson, Dr. Pierre Guy and Prof. Rafeef Garbi

    • Engineers in Scrubs: an eight-month engineer–clinician team project on low-cost scoliosis screening
  3. 2013

    Sophomore College, Great Ideas in Computer Science

    Stanford University · Stanford, CA, USA

  4. Oct 2012 – Jul 2016

    MEng, Engineering Science

    University of Oxford, Brasenose College · Oxford, UK

    Fourth-year project: Injectable bubbles for physiological pressure measurement

    Biomedical ultrasonics research in the BUBBL group at the Oxford Institute of Biomedical Engineering, plus industrial placements in aerospace technology.

    Supervised by Prof. Eleanor Stride and Prof. Robin Cleveland

Awards & honours

  • 2024

    Governor General’s Gold Medal, finalist

    University of British Columbia; shortlisted as one of UBC’s top graduating PhDs

  • 2020–2023

    Vanier Canada Graduate Scholarship ($150,000)

    Government of Canada (NSERC), for “Ultrasound-based surgical navigation for iliosacral screw insertions in pelvic fractures”

  • 2020–2023

    Four Year Doctoral Fellowship

    University of British Columbia

  • 2017

    Award of Distinction ($2,500)

    Medical Device Development Centre

  • 2016–2018

    Oxford-Canada Scholarship ($50,000)

    Canadian Rhodes Scholars Foundation, for graduate study in Canada

  • 2015

    IT Innovation Grant ($12,300)

    University of Oxford

Grants & funding

  • 2024–2026

    INOVAIT Focus Fund $2,000,000

    Three-year commercialization grant to develop a tumour localization system using ultrasound imaging and machine learning.

  • 2023–2024

    INOVAIT Pilot Fund $125,000

    Industrial research and development grant to prototype a tumour localization system using ultrasound imaging and machine learning.

  • 2021–2023

    Orthopaedic Trauma Association Research Grant US$48,000

    Competitive research grant funding two years of research for my PhD thesis.

  • 2021

    Joule Innovation Grant, Canadian Medical Association $10,000

    Development of Retinographer, an AI-powered handheld camera for imaging and diagnosing retinal disease.

  • 2019–2021

    WorkSafeBC Research Grant $45,000

    Competitive grant providing two years of support for doctoral research.

Teaching, outreach & service

Skills & expertise

  • Expertise
    • Medical imaging
    • Image analysis
    • Computer vision
    • Surgical navigation
    • Ultrasound
    • Image registration
    • Magnetic localization
    • Machine learning & deep learning
    • Generative models (GANs
    • DDPMs)
    • High-performance computing
  • Languages & tools
    • Python
    • MATLAB
    • C
    • C++
    • HTML/CSS
    • Git
    • Docker
    • Weights & Biases
    • tmux
    • SSH
    • Linux & Slurm
  • Libraries
    • PyTorch
    • OpenCV
    • scikit-learn
    • pandas
    • NumPy
    • Matplotlib
    • Flask
  • Software
    • 3D Slicer
    • PLUS Toolkit
    • Blender
    • Autodesk Fusion 360
    • SolidWorks
    • LaTeX
  • Research
    • Cadaver & phantom studies
    • User studies
    • Clinical collaboration
    • Statistical analysis
    • Grant writing
    • Teaching