International Women’s Day 2026
8 March 2026
To celebrate International Women’s Day, taking place on 8 March 2026, Moorfields Eye Charity spoke to Ana Sanchez, head of of clinical engineering at Moorfields Eye Hospital and Lynn Kandakji who completed a PhD funded by the charity, to learn more about their work and what inspired them to build a career as a woman in science.
Ana Sanchez - Head of clinical engineering
Ana is the head of clinical engineering at Moorfields Eye Hospital and has worked in clinical engineering for over 15 years, specialising in the safe introduction, management, and optimisation of medical technology across healthcare services. Her role allows her to collaborate closely with clinicians, operational teams, and external partners to ensure patients receive the highest standard of care supported by reliable, innovative medical equipment.
Ana’s advice has also helped Moorfields Eye Charity decide what equipment to fund. She supported the evaluation and procurement of the sterile air zone device for theatre that enhances the workflow and safety in surgery. She also helped introduce the Optos Silverstone ultra‑widefield imaging system into the paediatric service at St George’s which provides high‑resolution retinal imaging with minimal discomfort for young patients.
The charity has had a big impact on my work. Their willingness to invest in advanced technology allows me, as a clinical engineer, to push for the best possible equipment, solutions that are not only safe and reliable but also cutting edge. This collaboration helps bridge the gap between clinical need and technological capability, enabling us to deliver service improvements that would not be achievable through operational budgets alone. Ultimately, their support helps us provide better outcomes for patients, and that is incredibly motivating
Ana Sanchez
Ana was inspired to pursue clinical engineering because it sits at the intersection of healthcare, innovation, and problem‑solving. She has always been passionate about technology that has a direct, meaningful impact on people’s lives.
What I find most interesting is how rapidly medical technology evolves. Every project presents a new challenge, whether it’s integrating advanced imaging systems, improving device safety, or supporting clinical teams to adopt new tools confidently. I love being part of a profession where technology and patient care come together so directly.
Ana Sanchez
Ana’s advice to women who are interested in building a career in healthcare is to be curious, confident, and not afraid to step into roles that may not traditionally have been filled by women. Surround yourself with mentors and colleagues who support your growth, and always remember that your voice matters, especially in shaping the future of healthcare.
I absolutely love what I do. Eye healthcare is a field full of innovation, compassion, and opportunity, and women have an important role to play at every level, from clinical practice to science, engineering, research, and leadership…This field changes lives every single day, and there has never been a more exciting or meaningful time to be part of it.
Ana Sanchez
Lynn Kandakji - PhD scholarship
Lynn recently completed a PhD funded by Moorfields Eye Charity at the UCL Institute of Ophthalmology, working closely with clinicians at Moorfields Eye Hospital. Her research sits at the intersection of artificial intelligence and early-stage eye disease, specifically using AI to detect disease earlier and more accurately than current clinical methods allow.
Lynn’s PhD
Learn more
The question
Lynn’s PhD started from a simple but fundamental question: are we limiting ourselves by defining early disease in binary terms?
The condition she focused on was keratoconus, a progressive corneal condition, detected through advanced imaging. The standard clinical approach uses a handful of summary parameters and fixed thresholds to decide whether a patient has the condition or not. The argument was that this is too reductive as the underlying imaging data is rich, multi-dimensional, and structurally complex.
The method
She modelled corneal structure in a 21-dimensional space and reframed the problem as anomaly detection. Instead of asking “does this eye have the disease?”, the question became “how far does this eye deviate from healthy structure?” That shift allowed her to quantify risk continuously rather than forcing a hard boundary, which matters most for the patients sitting in an ambiguous zone.
She also benchmarked several vision models to understand whether their architectural assumptions and inductive bias align with the disease signal. Not all models are equal; different architectures can achieve similar accuracy while relying on very different internal signals.
The findings
The core finding was that early disease is more coherently modelled as a probabilistic pattern across multiple interacting dimensions, and that architectures which integrate context hierarchically outperform those that rely on isolated features.
Altogether, this points towards a more personalised, quantitative future for diagnostics that is more sensitive to the patients who are hardest to catch.
Moorfields Eye Charity’s support made a genuine difference. It provided the stability and protected time needed to pursue technically ambitious research and develop open-source tools that are not quick wins but require sustained focus and the freedom to test ideas that may not work on the first attempt. The funding also enabled close collaboration with clinicians, ensuring the work was grounded in real patient data and clinically meaningful from the outset.
Lynn Kandakji
During her masters, she took a course on consciousness that explored how the brain constructs internal models of the world from incomplete and noisy information and learned that we rarely observe reality directly but rather infer it, and that idea stayed with her. This closely parallels artificial intelligence. Deep learning models, which are loosely inspired by neural computation, also try to infer an underlying structure from imperfect, high-dimensional data.
In both cases, the challenge is the same: how do you build a model that meaningfully represents something you cannot observe directly? That connection led Lynn to pursue a PhD and she became interested in applying those ideas to medicine, where diagnosis is fundamentally an inference problem under uncertainty.
Lynn shared that the most interesting part of her PhD was the mechanistic side. Questions like: How does a model represent structure? What assumptions is it making about variation? Does its inductive bias align with the underlying biological signal?
Lynn’s advice to women interested in building a career in eye healthcare is to not be afraid to ask ambitious questions and don’t limit your scope.
Eye healthcare is one of the most technologically advanced specialities, and some of the most exciting work is happening at the intersections. Oculomics, for example, is an emerging field where ophthalmology and AI meet neurology, cardiology, endocrinology, and more. The eye is a remarkable window into the rest of the body. The opportunities that have shaped me most were the ones that felt slightly bigger than what I thought I was ready for.
Lynn Kandakji
