Pint of Robotics: Manisha Waterston, Hessah Alzahrani, Dr. Louis Masters (PhD)

Speaker 1: Manisha Waterston (School of Computer Science, University of Leeds)

Title: Computational methods to optimise ultrasound-guided high intensity focused ultrasound (USgHIFU) treatment plans.

Bio: Manisha is a PhD student at the University of Leeds and is part of the UKRI Centre for Doctoral Training in AI for Medical Diagnosis and Care. Her research focuses on applying AI techniques to increase the efficiency of ultrasound-guided HIFU treatment through optimised real-time treatment planning. She attended the University of Edinburgh, receiving a First Class Bachelor’s Degree with Honours in Theoretical Physics, in 2022.

Abstract: High-Intensity Focused Ultrasound (HIFU) is a non-invasive, non-ionising treatment that uses high-amplitude ultrasound waves to thermally ablate targeted tissue. It is a highly attractive therapeutic option due to its reduced risk of complications compared to conventional surgical approaches. HIFU has been applied to a wide range of medical conditions, including cancers of the thyroid, breast, pancreas, and brain. A key factor in improving the efficiency and effectiveness of HIFU is treatment planning. Current approaches typically rely on clinicians to outline the planning tumour volume and target region, as in a surgical method. In addition, the selection of acoustic parameters is largely clinician-dependent. The lack of standardised planning methods can therefore lead to inconsistent outcomes, including over-treatment or under-treatment of the target region. This talk will explore how constraint programming can enhance the efficiency of ultrasound-guided HIFU (USgHIFU) through optimised real-time treatment planning. It will further examine how these optimised plans can be integrated into a co-robotic-assisted clinical USgHIFU system, with a particular focus on the treatment of benign thyroid nodules.

Speaker 2: Hessah Mattar Alzahrani (School of Physics and Astronomy, University of Leeds)

Title: From Abstraction to Classroom Practice: Robotics Approach to STEM Physics Education

Bio: Hessah is a PhD student in the School of Physics and Astronomy, under the Physics Education Research Group (PERG) at the University of Leeds. She holds a Master’s degree in information communication technology in education and has extensive experience in teaching and teacher professional development. Her doctoral research explores the use of educational robotics to support STEM physics education and enhance teachers’ professional development (confidence and self-efficacy).

Abstract: In alignment with Saudi Vision 2030, developing teachers’ innovative pedagogical skills is essential for advancing education. Educational robotics offers a promising approach for supporting STEM education by transforming abstract physics concepts into observable experiences and promoting active learning and engagement. This study evaluated the impact of a STEM-oriented professional development programme on secondary physics teachers’ confidence and self-efficacy in integrating educational robotics. Guided by the TPACK framework, the programme combined hands-on training with classroom implementation, addressing the limited evidence on the use of educational robotics in authentic educational contexts. Using a pre–post questionnaire design and planned post-interviews, the study examined changes in teachers’ confidence, self-efficacy, and technology integration. Preliminary findings indicate positive improvements across these areas, together with stronger alignment between technology and physics content. The findings highlight the value of practice-based, technology-enhanced professional development and demonstrate the potential of educational robotics to strengthen physics teaching and STEM integration.

Speaker 3: Louis Masters (PhD), (Chief Executive Officer at Hydra Manufacturing)

Title: Closed-loop Defect Detection for a Hybrid Manufacturing Platform

Bio: Louis is the CEO of Hydra Manufacturing, a University of Leeds spinout company, who are commercialising a hybrid additive manufacturing process for advanced materials. During his PhD, Louis developed a control system to detect and repair extrusion-related defects within the hybrid manufacturing process, leading to improvements in process efficiency and part quality. He now leads the Hydra team through the early stages of the spinout journey, where they have already achieved their first commercial sales and industrial partnerships, and recently raised their first round of equity investment.

Abstract: This talk will focus on Louis’ research in defect detection and correction within a hybrid manufacturing platform for the production of advanced ceramic components, and the transition of this research into a commercial venture. It will cover the integration of monitoring hardware into manufacturing platforms alongside the training and validation of deep learning models for defect detection. The proposed method identified voids with a precision of 91%, and the corrective actions demonstrated a 68% reduction in porosity when compared to non-corrected samples, creating new opportunities for the manufacture of advanced ceramic components. The talk will also discuss Hydra Manufacturing’s transition from academic research into a commercial venture, including the opportunities and challenges facing early-stage spinouts in the UK.