Dr Mingjun Zhong
Lecturer
- About
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- Email Address
- mingjun.zhong@abdn.ac.uk
- School/Department
- School of Natural and Computing Sciences
Memberships and Affiliations
- Internal Memberships
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- Currently I am serving as an Exam Officer and a Tutor.
- External Memberships
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- I serve as an Associate Editor for the journal Neural Processing Letters.
- I serve as a Review Editor for the journal Frontiers in Applied Mathematics and Statistics (Statistics section).
- I am a FHEA (Fellow of the Higher Education Academy)
- I review grants for multiple funding bodies, a variety of international journals and several prestigious machine learning and artifial intellegence conferences.
- Research
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Research Overview
My research interests are mainly (application-driven) machine learning and computational statistics. My research mission is to understand patterns and phenomena observed in real-world data by devising probabilistic and statistical machine learning methodologies.
Current Research
Currently I am working on the following application domains and inferential machine learning algorithms:- Health care data.
- Non-intrusive load monitoring (energy disaggregation).
- Spectroscopy data.
- EEG and fMRI.
- Variational inference
- Markov chain Monte Carlo
- High-dimentional inference
- Variance reduction
- Intractable likelihood models
- Bayesian matrix factorization
- Teaching
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Teaching Responsibilities
I am teaching the following courses (20/21):
- CS4048/5059 Robotics
- CS5062 Machine Learning
- CS551J Knowlege Representation and Reasoning
- Publications
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Transfer Learning for Non-Intrusive Load Monitoring
IEEE Transactions on Smart Grid, vol. 11, no. 2, pp. 1419-1429Contributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1109/TSG.2019.2938068
- [ONLINE] University of Lincoln Repository
- [ONLINE] View publication in Scopus
Neural Control Variates for Monte Carlo Variance Reduction
Chapters in Books, Reports and Conference Proceedings: Conference Proceedings- [ONLINE] DOI: https://doi.org/10.1007/978-3-030-46147-8_32
- [ONLINE] View publication in Scopus
A demonstration of reproducible state-of-the-art energy disaggregation using NILMTK
Chapters in Books, Reports and Conference Proceedings: Conference Proceedings- [ONLINE] DOI: https://doi.org/10.1145/3360322.3360999
- [ONLINE] View publication in Scopus
Efficient Gradient-Free Variational Inference using Policy Search
Chapters in Books, Reports and Conference Proceedings: Conference ProceedingsSequence-to-Point Learning with Neural Networks for Non-Intrusive Load Monitoring
Chapters in Books, Reports and Conference Proceedings: Conference ProceedingsLatent Bayesian melding for integrating individual and population models
Contributions to Journals: Conference ArticlesSignal aggregate constraints in additive factorial HMMs, with application to energy disaggregation
Chapters in Books, Reports and Conference Proceedings: Conference Proceedings