Mingjun Zhong

Associate Professor

Aberdeen City, Scotland, China
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Summary

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Senior
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Top School
Mingjun Zhong is an Associate Professor and machine learning lecturer with 11 years of research and teaching experience spanning universities in China and the UK. He holds a PhD in Mathematics from Dalian University of Technology and applies mathematical modeling, Bayesian inference, and deep learning to both theoretical and applied problems. Mingjun has held roles from research associate positions at Glasgow and Edinburgh to senior lecturer and current teaching posts at Lincoln and Aberdeen, blending rigorous research with practical course delivery. He is proficient in MATLAB and Python and routinely bridges probabilistic methods and modern neural approaches in his work. Colleagues note his ability to translate advanced mathematical ideas into accessible coursework and reproducible code for students and collaborators. Based in Aberdeen but maintaining strong ties to China, he brings an international perspective to curriculum development and research collaborations.
code11 years of coding experience
job11 years of employment as a software developer
book学士, Applied Mathematics, 学士, Applied Mathematics at 大连理工大学
bookDoctor of Philosophy (Ph.D.), School of Mathematics, Doctor of Philosophy (Ph.D.), School of Mathematics at Dalian University of Technology
languagesChinese, English
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Github Skills (12)

forecasting10
algorithms10
energy10
forecast10
python10
transfer-learning9
monitoring9
bayesian8
bayesian-inference7
mcmc7
variational-inference6
probabilistic-programming6

Programming languages (2)

Jupyter NotebookPython

Github contributions (5)

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MingjunZhong/NeuralNetNilm

Dec 2017 - Jul 2020

Sequence-to-point learning for non-intrusive load monitoring (energy disaggregation)
Contributions:10 commits, 10 pushes, 1 branch in 2 years 7 months
monitoring
MingjunZhong/transferNILM

Jun 2019 - Jul 2020

Transfer Learning for Non-Intrusive Load Monitoring
Contributions:16 commits, 13 pushes, 1 branch in 1 year 1 month
monitoringtransfer-learning
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