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Postgraduate Students
Postgraduate
r.frith@sms.ed.ac.uk
2.03 Scottish Microelectronics Centre
Civil and Environmental Engineering
Imaging, Data and Communications
Postgraduate
s1913717@sms.ed.ac.uk
Electronics and Electrical Engineering
Integrated Micro and Nano Systems
Postgraduate
s2659803@sms.ed.ac.uk
1.04-E Alrick Building
Mechanical Engineering
Energy Systems
Postgraduate and Postgraduate
S2758679@sms.ed.ac.uk
2.26 Murchison House
Electronics and Electrical Engineering
Imaging, Data and Communications
Postgraduate
E.E.Bowman@sms.ed.ac.uk
Electronics and Electrical Engineering
Integrated Micro and Nano Systems
Postgraduate
s1837774@sms.ed.ac.uk
3.03 Scottish Microelectronics Centre
Electronics and Electrical Engineering
Integrated Micro and Nano Systems
Postgraduate
s2309335@sms.ed.ac.uk
3.05 Scottish Microelectronics Centre
Electronics and Electrical Engineering
Integrated Micro and Nano Systems
Postgraduate
X.Ling-7@sms.ed.ac.uk
1.116 Sanderson Building
Mechanical Engineering
Materials and Processes
Postgraduate
B.Ye-10@sms.ed.ac.uk
1.26 Murchison House
https://bochen-ye.github.io/
https://www.linkedin.com/in/bochen-ye/
Electronics and Electrical Engineering
Integrated Micro and Nano Systems
Bochen Ye is currently a first-year PhD student at the Centre for Electronics Frontiers, University of Edinburgh. Before that, he received his Master degree in Eletrical Engneering from Eindhoven University of Technology(TU/e), Netherlands in 2024 and Bachelor degree in Integrated Circuit Design and Integrated Systems from Hefei University of Technology(HFUT), China in 2022. He was a intern at NXP Semiconductor and Intrinsic ID(now part of Synopsys).
PhD student in Engineering - UoE, UK, Now
M.S.(ir.) in EE - TU/e, NL, 2024
B.Eng. in IC design - HFUT, China, 2022
Bochen's research focuses on designing digital hardware acceleration systems for large-scale AI models using novel architectures, aiming to overcome memory and computational bottlenecks. His work emphasizes efficient dataflow, high-performance accelerators, and energy-efficient AI systems on digital ASIC chips. His current focus is on advancing hardware accelerators for LLMs, VLMs, and generative AI to enable next-generation intelligent computing.
Postgraduate
A.T.Don@sms.ed.ac.uk
2.03 Scottish Microelectronics Centre
Electronics and Electrical Engineering
Imaging, Data and Communications