Mirela Gyurova

Activities

1

talks

Principal Consultant Kubrick

Mirela is a Principal Consultant in ML and AI at Kubrick Group, spearheading the delivery of extensive technical training to data consultants and fostering talent in the fields of Advanced Analytics and Data Science. She provides expert advisory, project and thought leadership, guiding and mentoring teams to deliver innovative AI and data solutions. Mirela is an active member of the Women in Data community, involved in a number of Women's Health initiatives that leverage Data Science and Generative AI for societal good. Throughout her career in data and tech, she has been a strong advocate for diversity and inclusion, driving practices that honour transparency and integrity at the workplace. Mirela's commitment to guiding consultants through their first steps in data and her contributions to Corporate Social Responsibility initiatives highlight the transformative impact of data and AI on people's lives and businesses.

Bio from: Big Data LDN 2025

Filtering by: Big Data LDN 2025 ×

Filter by Event / Source

Big Data LDN 2025 1

Talks & appearances

Showing 1 of 1 activities

Search activities →

AI for Health Equity: A Double-Edged Sword

2025-09-25 · Big Data LDN 2025

Face To Face

with Mirela Gyurova (Kubrick) , Coziana Ciurtin (University College London)

AI/ML GenAI

A leading rheumatologist teamed up with an AI specialist to help with a systematic review of lupus research, a condition of which 90% of patients are women. Together, they revealed the deep-rooted biases in research methodologies - and the machine learning models that underpin them.

Professor Coziana Ciurtin (UCL) and Mirela Gyurova (Kubrick) share the story behind their GenAI tool which can revolutionise underfunded and underexplored areas of medical research, including identifying ML-enforced biases.

When gender and ethnic disparities in healthcare persist, what responsibilities do data professionals have in shaping ethical, impactful AI? And how can partnerships between industry and academia unlock new standards for evidence, equity, and trust in ML?

For anyone building, using, or regulating AI, this session will challenge assumptions and make the case for responsible, cross-sector innovation.

Powered by Women in Data®