Pint of Robotics: Sung Hin (Adrian) Lam, Yushi Guo, Dr. Benjamin Jackson (PhD)

Speaker 1: Sung Hin (Adrian) Lam (School of Mechanical Engineering, University of Leeds)

Title: Digitalisation of Advanced Extrusion-Based Manufacturing with Numerical Modelling

Bio: Sung Hin (Adrian) Lam is a second-year PhD student in Mechanical Engineering at the University of Leeds. He completed both his BEng and MSc in Aerospace Engineering at Leeds before continuing into doctoral research. His PhD builds on his master’s thesis on numerical simulation of 3D printing and now focuses on modelling flow behaviour in extrusion-based manufacturing of batteries. His research bridges multiphase Computational Fluid Dynamics (CFD) with machine learning, rheology, and advanced manufacturing. He is currently transitioning his models from commercial CFD software to open-source platforms, using the university’s high-performance computing facilities.

Abstract: Traditional methods for testing new designs and formulations in manufacturing often rely on costly and time-consuming laboratory trials. With the rapid growth of computing power, numerical modelling has become a powerful tool to accelerate innovation. This talk explores how Computational Fluid Dynamics (CFD) can capture the complex flow behaviour in extrusion-based manufacturing and help optimise the process. It will also highlight how the University of Leeds’ high-performance computer, Aire, is being used to run computationally heavy simulations and support the digitalisation of advanced manufacturing.

Speaker 2: Yushi Guo (Stormlab, School of Electronic and Electrical Engineering)

Title: Towards Situation Awareness for Robot-Assisted Minimally Invasive Surgery

Bio: Yushi is a second-year PhD student in the STORM Lab at the University of Leeds. Her research focuses primarily on surgical video understanding and anticipation.

Abstract: Situation awareness is essential for safe and efficient surgery, enabling clinicians to perceive intraoperative cues and use them to inform decision-making. Surgical phase recognition is a key component of situation awareness in the operating room, supporting real-time assessment and postoperative analysis. Within this framework, accurate recognition of surgical phases provides a structured view of procedural progress and is crucial for enhancing both safety and efficiency. This talk offers an overview of situation awareness in minimally invasive surgery and illustrates how a clearer understanding of surgical workflow can enhance the safety and reliability of robot-assisted minimally invasive surgery.

Speaker 3: Dr. Benjamin Jackson (PhD), (STORM Lab, School of Electronic and Electrical Engineering)

Title: Tele-operated Robotic Mechanical Thrombectomy in Acute Stroke

Bio: Ben Jackson is a researcher specializing in interventional robotics and minimally invasive surgery. He completed his undergraduate studies in Robotics at the University of Reading, followed by a Master’s in Medical Robotics and Image-Guided Intervention at Imperial College London. He earned his PhD in Surgical and Interventional Engineering from King’s College London, focusing on robotic systems for Mechanical Thrombectomy. Ben is currently based at the University of Leeds, where he works with the da Vinci robotic system to advance minimally invasive surgical techniques. His interdisciplinary expertise supports the development of next-generation interventional platforms that improve clinical precision and patient outcomes.

Abstract: This talk presents research conducted during a PhD in Surgical and Interventional Engineering at King’s College London, focused on advancing autonomous robotic systems for mechanical thrombectomy. The work explores the integration of interventional robotics, real-time imaging, and intelligent control to enhance precision and safety in neurovascular procedures. Key developments include catheter navigation algorithms, force sensing, and image-guided decision-making frameworks. The goal is to enable autonomous or semi-autonomous intervention in acute ischemic stroke treatment,