Omar Choudhry

Research Topic: AI-Driven Surgical Skill Training in Resource-Constrained Environments

Supervisors: Dr Dominic Jones, Dr Sharib Ali, Mr Shekhar Biyani

About Omar: Having graduated from Leeds in Computer Science with AI, Omar joined the AI-Medical CDT in its final cohort. Alongside his research, he is a postgraduate teaching assistant, Associate Fellow of Advance HE, and recipient of multiple academic prizes, with extensive leadership and outreach roles including President of the AI Society, student representative for the CDT, Education Outreach Fellow of the Faculty of Engineering and Physical Sciences, and committee member for Scientific Machine Learning. His contributions have connected nearly 1,000 students, staff, and the wider public to AI, while his academic achievements include multiple best paper, pitch, and presentation awards at national and international conferences. Beyond academia, Omar has served as Chief AI Scientist and developer in an AI EdTech startup, worked with UNICC, Discover Financial Services, and the NHS, and directs OC Solutions Ltd, all while maintaining international outreach and teaching roles, including through the prestigious Mawhiba programme in Saudi Arabia.

Project description: The Lancet Commission on Global Surgery (LCGS) in 2015 highlighted the urgent need for increased volume and quality of surgery as an indispensable component of global health. It has been estimated that 11% of deaths in low- and middle-income countries (LMICs) are due to conditions treatable by surgery. 80% of these deaths are preventable as they are caused by the lack of surgeons, consisting of cases that require only general surgical emergencies such as surgical site infections or trauma. Current training camps for laparoscopic surgery in the UK are performed in a 1-to-1 nature, a trainer will spend around an hour with a trainee before they are required to practice alone with little to no oversight. To speed up this training process, an AI system able to analyse the trainees’ skills from a recorded video feed and provide them with feedback could reduce the learning curve and increase the throughput of surgical trainees.