Associate Professor Ehsan Vaghefi

BSc, MSc, PhD


I hold PhD in bioengineering and I am a senior lecturer on Medical Imaging and Artificial Intelligence in Optometry and Ophthalmology, at the School of Optometry and Vision Sciences. I received my Masters of Science in Biomedical Sciences in 2006 from the University of New South Wales. I then joined the Auckland Bioengineering Institute for my doctoral degree.

So far in my career, I have published 43 peer-reviewed journal articles and hold 3 patents. My publications have been focused on non-invasive imaging of ocular tissue and use of artificial intelligence in ocular disease diagnosis. So far, I have been the named investigator on more than $16,000,000 of external research funding, and I am the PI for over $3,000,000 in grant funding. These grants include two HRC projects, one HRC early career award, two Marsden projects, one NIH grant and two MBIE awards. 

I am the founder\CEO of Toku Eyes (, where we are focused on developing AI-based tool to provide accessible and inexpensive eyecare. Our first product (THEIA™) is now being considered to offer clinical decision-making assistance as part of New Zealand National Diabetic Screening Program.  


Research | Current

Ehsan is currently focused on

  • Clinically applied physiological optics
  • Ophthalmic imaging
  • Ophthalmic Artificial Intelligence 


UNISERVICES – Return on Science

Vaghefi, Ehsan


 $            100,000.00

Convertible notes to develop THEIA for national diabetic screening

Spark Health 

Vaghefi, Ehsan


 $            50,000.00

Optical Laser Biometer in practice 

Spark Health 

Vaghefi, Ehsan


 $            50,000.00

THEIA for national diabetic screening 

The University of Auckland -ABI-Medtech

Vaghefi, Ehsan


 $            95,000.00

Second-generation Optical Laser Biometery (OLB) - Laser Bio-meter 2.0

Areas of expertise

  • Artificial Intelligence
  • Ophthalmic imaging
  • Computational modelling of the eye tissue

Selected publications and creative works (Research Outputs)

As of 29 October 2020 there will be no automatic updating of 'selected publications and creative works' from Research Outputs. Please continue to keep your Research Outputs profile up to date.
  • Vaghefi, E., Yang, S., Xie, L., Hill, S., Schmiedel, O., Murphy, R., & Squirrell, D. (2020). THEIA™ development, and testing of artificial intelligence-based primary triage of diabetic retinopathy screening images in New Zealand. Diabetic medicine : a journal of the British Diabetic Association10.1111/dme.14386
    Other University of Auckland co-authors: Rinki Murphy, Song Yang
  • Lie, A. L., Pan, X., White, T. W., Donaldson, P. J., & Vaghefi, E. (2020). Using the Lens Paradox to Optimize an In Vivo MRI-Based Optical Model of the Aging HumanCrystalline Lens. TRANSLATIONAL VISION SCIENCE & TECHNOLOGY, 9 (8)10.1167/tvst.9.8.39
    Other University of Auckland co-authors: Alyssa Lie, Wilson Pan, Paul Donaldson
  • Muir, E. R., Pan, X., Donaldson, P. J., Vaghefi, E., Jiang, Z., Sellitto, C., & White, T. W. (2020). Multi-parametric MRI of the physiology and optics of the in-vivo mouse lens. Magnetic resonance imaging, 70, 145-154. 10.1016/j.mri.2020.04.015
    Other University of Auckland co-authors: Wilson Pan, Paul Donaldson
  • Thakur, S. S., Pan, X., Kumarasinghe, G. L., Yin, N., Pontre, B. P., Vaghefi, E., & Rupenthal, I. D. (2020). Relationship between rheological properties and transverse relaxation time (T2) of artificial and porcine vitreous humour. Experimental Eye Research, 19410.1016/j.exer.2020.108006
    Other University of Auckland co-authors: Sachin Thakur, Wilson Pan, Beau Pontre, Ilva Rupenthal
  • Vaghefi, E., Hill, S., Kersten, H. M., & Squirrell, D. (2020). Quantification of Optical Coherence Tomography Angiography in Age and Age-Related Macular Degeneration Using Vessel Density Analysis. Asia-Pacific journal of ophthalmology (Philadelphia, Pa.), 9 (2), 137-143. 10.1097/apo.0000000000000278
    Other University of Auckland co-authors: Hannah Kersten
  • Vaghefi, E., Hill, S., Kersten, H. M., & Squirrell, D. (2020). Multimodal Retinal Image Analysis via Deep Learning for the Diagnosis of Intermediate Dry Age-Related Macular Degeneration: A Feasibility Study. Journal of ophthalmology, 202010.1155/2020/7493419
    Other University of Auckland co-authors: Hannah Kersten
  • Hari, N., Burgess, C., & Vaghefi, E. (2020). Repeatability, reproducibility, and accuracy of a novel imaging technique for measurement of ocular axial length.. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging.
  • Hill, S., Vaghefi, E., Kersten, H., & Squirrell, D. (2019). Multi-input artificial intelligence design for multi-modal retinal imaging diagnosis of intermediate dry age related macular degeneration. CLINICAL AND EXPERIMENTAL OPHTHALMOLOGY. (pp. 2).


Contact details

Primary office location

M&HS BUILDING 501 - Bldg 501
Level 3, Room 303
New Zealand

Social links

Web links