I am an Assistant Professor in Robotics and Automation at Warwick Manufacturing Group, University of Warwick, and an Honorary Lecturer in the Department of Electronic and Electrical Engineering at University College London. My work connects engineering education with wearable sensing, human biomechanics and healthcare engineering, bringing together practical teaching and research into human posture and movement.
My background spans mechatronic engineering, academic and clinical research, and university teaching. Before joining Warwick, I was a Teaching Associate in Robotics and Intelligent Systems at Queen Mary University of London and held research appointments at the Universities of Liverpool and Cambridge. I hold a first-class MEng in Mechatronic Engineering from the University of Nottingham and a PhD in Engineering from the University of Liverpool. I am a Chartered Scientist and a Fellow of the Higher Education Academy.
Robotics and automation teaching
I help undergraduate and postgraduate students turn engineering theory into working systems. My teaching spans robotics, mechatronics, control, artificial intelligence and engineering computing, using authentic practical laboratories, design-build activities and project supervision to develop technical skills, critical thinking and professional judgement. At UCL, I contribute to Robotics for Medicine and Industry, teaching prosthetics, wearable technologies and biomechanics.
Wearable sensing and biomechanics research
I develop and evaluate methods to understand human posture and movement, combining wearable sensors, machine learning, experimental measurements and computational modelling. My doctoral research focused on intelligent wearable sensing for sleep posture assessment. My subsequent research experience includes clinical gait analysis and the biomechanics of ageing foot tissues, working with engineers and clinicians to connect engineering methods with healthcare questions.
Engineering education
I design and investigate practical, active learning experiences that help students understand complex engineering concepts and apply them with confidence. My educational research and development includes virtual engineering laboratories, game-based learning and AI-supported interactive materials. I combine these approaches with authentic assessment, inclusive teaching and constructive feedback to support students’ participation and development.
Robotics, sensing and embedded systems
Wearable sensor development, embedded C/C++, PCB design, microcontroller-based prototyping, sensor fusion, digital signal processing and feedback control. Experience with the Robot Operating System (ROS) and programmable logic controllers (PLCs).
Programming, machine learning and data analysis
Python and MATLAB/Simulink for engineering computation, signal analysis and algorithm development; machine learning and deep learning using TensorFlow and PyTorch, alongside data visualisation and interpretable approaches to sensor-based analysis.
Human movement measurement and biomedical imaging
Optical and wearable motion capture, including Vicon, OptiTrack, Qualisys and inertial sensors; force-plate and plantar-pressure measurements; ultrasound, MRI and biplanar X-ray imaging. Experimental data acquisition, preprocessing and validation against reference measurements.
Computational biomechanics
Musculoskeletal modelling and inverse kinematic and dynamic analysis with OpenSim; medical image segmentation with 3D Slicer and Avizo; subject-specific finite-element modelling and tissue analysis using Abaqus.
Educational technology and interactive development
Virtual engineering laboratories, game-based resources and AI-supported interactive learning materials. HTML/CSS, 3D modelling and animation, with experience using Moodle, Blackboard and Canvas to support teaching and learning.
- Human-centred robotics and assistive technologies
- Wearable technologies for health and mobility
- Sleep posture, gait and healthy ageing
- Interpretable machine learning for sensing applications
- Engineering education and inclusive learning
- Virtual laboratories and game-based learning
- Patient and public involvement in research
MEd in Academic Practice | 2026 - present
Queen Mary Academy
Queen Mary University of London
In progressPostgraduate Certificate in Academic Practice | 2026
Queen Mary Academy
Queen Mary University of LondonPhD in Engineering | 2025
Department of Mechanical, Materials and Aerospace Engineering
University of Liverpool
Thesis: intelligent wearable sensing for human sleep posture classification and temporal analysis.MEng in Mechatronic Engineering | 2019
Department of Electrical and Electronic Engineering
University of Nottingham
First-class honours.