Designing circuits and systems demands extensive expertise and robust Electronic Design Automation (EDA) tools to reduce time-to-market. AI can significantly aid in this process by supporting various design stages, from high-level architectural conceptualization to physical implementation. Pillar 3 focuses on guiding the future directions of AI in circuit and system design. One of our current activities involves exploring how Large Language Models can assist in developing functional and efficient circuit architectures from high-level specifications.

Dr Christos Bouganis

Anuoluwa Adeleye

University of Southampton

MEng Electronics with Industrial Studies

Jingyi Li

University of Manchester

BEng Electrical and Electronic Engineering

Research Interests:

I’ve loved learning the statistical foundation behind methods such as Principal Component Analysis at university, allowing me to analyse large amounts of data. However, I am especially interested in exploring machine learning in computer vision and system modelling as well as accelerating these processes through hardware. 

Experience:

FPGA Hardware Engineer Intern Intel/Altera

Lead Hardware Engineer Exciting Escapes 

Research Interests: 

Strong foundation in power systems, embedded systems, and control theory. Currently exploring AI integration with advanced topics such as data networking, sensor and instruments, and numerical analysis to develop intelligent solutions for applications in electrical systems and industrial automation. 

Experience: 

Power System Design Engineering Intern at China Energy Engineering Group Guangdong Electric Power Design Institute 

Issa Saddiq

University College London

MSci Chemistry

Sara Anurag Somani

University of Leeds

BECH in Mechantronic and Robotics

Research Interests: 

I am passionate about applying data-driven methods to solve scientific challenges, particularly in materials discovery, characterization, and process optimization. I enjoy working with statistics, programming, and computational approaches (especially machine learning) and I'm looking forward to getting involved in projects at APRIL. 

Experience: 

Student Curriculum Partner at UCL 

Research Intern at RBG Kew 

Assistant Scientist at Wessex Water 

Designing machine learning algorithms for automated analysis of X-ray Photoelectron spectra (XPS). 

Research Interests: 

My research interests lie in the field of human-machine interaction, focusing on enhancing the predictability and responsiveness of real-time systems. I integrate knowledge from mechanical, electronic, electrical, and computer engineering, with a keen interest in how combined hardware and software systems can improve safety, usability, and automation in real-world applications. 

Experience: 

Internship in semiconductor manufacturing at SSMC in Singapore - Characterisation Team and Test Engineering

This month Santhosh traveled to Corsica, France to attend the Tools for Accelerating the Modeling of Energy Materials (TOTEMIC) training school. TOTEMIC aims to explore the critical role of materials science in the ecological transition and raise awareness within the scientific community about the new paradigm of AI integration in materials development. TOTEMIC explored broad topics such as automating labs, building digital twins, modelling, advancing explainable AI and harnessing large language models for materials science and engineering.

Santhosh presenting in Corsica

This year, the Graduate School’s annual Postgraduate Research Conference invited contributions from AI Hubs across the University of Edinburgh. The APRIL AI Hub took part with a poster presented by student Lai Gan and his colleagues, showcasing their work on automated measurement and unsupervised labelling in the characterisation of memristive devices. Their project introduced a scalable end-to-end pipeline from fabrication to AI analysis, powered by a custom-designed structured database and deep clustering models—demonstrating how AI can accelerate research on emerging electronic devices. It was a great opportunity to present our ongoing work, whilst also seeing the variety of research and opportunities across the School. We look forward to attending future PGR Conferences!

AI/ML in Design Verification at the University of Bristol

Dr Cristian Sestito from Pillar 3 attended the AI/ML in Design Verification DVClub Meeting organised by Tessolve, the University of Bristol and TechWorks. The DVClub consider how we can save time and effort whilst improving time-to-market through the application of AI/ML to verification. There was a fantastic variety of speakers from the university, Analog Devices India, Tessolve, and Cadence.