About
Machine Learning and Computer Engineer: accelerating AI at the software-hardware…
Experience
Education
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University of Cambridge
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Includes both Bachelor and Master of Engineering (Honours with Distinction)
Master Dissertation: Sparse Approximate Inference in Gaussian Processes: inducing variables
Courses taken:
ML/AI: Deep Learning, Probabilistic Machine Learning, Computational Statistics
Information: statistical signal processing, time series analysis, linear systems&control, optimisation
Electrical: Embedded Systems, Digital electronics, radio frequency, semiconductor technology
Computer: Computer…Includes both Bachelor and Master of Engineering (Honours with Distinction)
Master Dissertation: Sparse Approximate Inference in Gaussian Processes: inducing variables
Courses taken:
ML/AI: Deep Learning, Probabilistic Machine Learning, Computational Statistics
Information: statistical signal processing, time series analysis, linear systems&control, optimisation
Electrical: Embedded Systems, Digital electronics, radio frequency, semiconductor technology
Computer: Computer Systems, Data Structure & Algorithm -
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Represented school as an invited speaker in "12th Grand Contest on Chemistry for High School Students" held in Osaka, Japan, in Oct 2015
Worked on Carbon NanoTubes Thin Film Transistors for Organic LED display application, as part of Nanyang Research Programme 2015 (Gold award)
Publications
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Physics-Based Stochastic Three-Dimensional Modeling for Metal-Oxide Resistive Random Access Memory
IEEE Transactions on Electron Device
Patents
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Device for separating various metal ions and solid particles from waste liquid at the same time
Issued CN 201420866442
The patent discloses a device for separating various heavy metal ions and solid particles from waste liquid by incorporating principles of centrifugal acceleration and electrolysis.
Languages
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English
Native or bilingual proficiency
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Chinese
Native or bilingual proficiency
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