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About#

I am a seasoned AI engineering leader with 18+ years of experience driving transformative healthcare innovation through artificial intelligence. Currently serving as Head of AI Engineering at Harrison.ai, I lead teams developing breakthrough AI solutions that impact millions of patients worldwide.

Leadership & Impact#

As Head of AI Engineering at Harrison.ai, I oversee the development and deployment of regulatory-cleared medical AI systems serving:

  • 6M+ patients through AI-powered diagnostic solutions
  • 1,000+ healthcare facilities across global markets
  • 45% improvement in diagnostic accuracy for early cancer detection

Key achievements include:

  • Leading development of Harrison.rad.1, radiology's first foundation model
  • Building comprehensive regulatory-approved medical devices across UK, ANZ, and US markets
  • Building and scaling engineering teams across Australia and global markets

Recognition & Awards#

  • Women in AI 2025 Award Winner - Global recognition for AI leadership and impact
  • O'Reilly Author - Deep Learning at Scale (2024)
  • Multiple Patent Holder - Display of information in computing devices

Education & Research#

Ph.D. in Medical Image Analysis (2019) - University of Sydney
Thesis: Modelling the Interpretation of Digital Mammography Using High Order Statistics and Deep Machine Learning

Master of Applied Science (2015) - University of Sydney
Medical Image Optimisation and Perception (Research)

B.Tech in Computer Science (2007) - Harcourt Butler Technological Institute, India

Research Publications#

My research spans medical imaging, machine learning, and human perception with publications in leading journals:

Key Papers:

  • Can a Machine Learn from Radiologists' Visual Search Behaviour and Their Interpretation of Mammograms - Journal of Digital Imaging, 2019 [Link]
  • Missed Cancer and Visual Search of Mammograms: What Feature-based ML Can Tell Us That Deep Learning Cannot - SPIE Medical Imaging, 2019 [Link]
  • Can Digital Breast Tomosynthesis Perform Better Than Standard Digital Mammography - European Radiology, 2018 [Link]
  • Modeling Visual Search Behavior of Breast Radiologists Using Deep CNN - SPIE Journal of Medical Imaging, 2018 [Link]

Additional Publications:

  • Fixated and Not Fixated Regions of Mammograms: Higher-Order Statistical Analysis - Academic Radiology, 2017 [Link]
  • The Role of Digital Breast Tomosynthesis in Breast Assessment - Journal of Medical Radiation Science, 2017 [Link]
  • Implementation of Split-Plot Reader Design in Digital Breast Tomosynthesis - SPIE Medical Imaging, 2015 [Link]

Published Works#

Books#

Patents#

Teaching & Mentorship#

O'Reilly Interactive Learning Series#

Reproducible Deep Learning - Comprehensive four-part course:

  1. Semantic Segmentation on Oxford Pets Dataset
  2. Identifying the Reproducibility Challenge
  3. Random Seeds and Process-Parallelism
  4. Achieving 100% Reproducibility

Technical Writing#

Technical Expertise#

AI/ML Specialties: Medical imaging, computer vision, deep learning at scale, foundation models, regulatory AI

Leadership Areas: Team building, technical strategy, product development, cross-functional collaboration

Industry Focus: Healthcare AI, medical devices, diagnostic imaging, responsible AI deployment