Dr. Mimi Zhang
Assistant Professor, Statistics
Biography
Mimi Zhang joined TCD as an assistant professor in October 2017. She holds a B.Sc. in statistics from University of Science and Technology of China (Sep. 2007-Jul. 2011), and a Ph.D. in industrial engineering from City University of Hong Kong (Nov. 2011-Jan. 2015). Before joining TCD, she was a research associate at University of Strathclyde and Imperial College London. Her main research areas are machine learning and operations research, including cluster analysis, Bayesian optimization, functional data analysis, reliability & maintenance (engineering), etc. She is the strand leader of the Data Science MSc programme and an AE for Journal of Classification.
Current PhD students:
- Sukriti Dhang, 2022, co-supervise with Dr Soumyabrata Dev
Xiantao Zhao, 2021
Former PhD students:
- Joshua Tobin, thesis title "Consistent Mode-Finding for Parametric and Non-Parametric Clustering".
Bernard Fares (part time), thesis title "Incorporating Ignorance within Game Theory: An Imprecise Probability Approach".
Teaching Activities
- 09/21-now: Introduction to Statistical Concepts and Methods (10 ECT), Coordinator
- 09/21-now: Implementing Statistical Methods in R (5 ECT), Coordinator
- 09/17-now: Software Application (5 ECT), Coordinator
- 09/17-08/21: Statistics Base Module (15 ECT), Coordinator
Open positions: I am currently seeking applications for PhD candidates, working on (unsupervised) machine learning of functional data.
- [1] A Bachelor's degree in statistics, math, or closely related subjects is required.
- [2] The time from your completion of Bachelor study is no more than four years.
For Chinese students, we have up to 14 scholarships every year to award for PhD positions as part of the China Scholarship Council - Trinity College Dublin Joint Scholarship Programme. The funding package supports a student registered for a PhD for up to 4 years and includes living expenses (typically 1,300 EUR/ month) plus airfare, visa and passport fees. If you want to apply for this scholarship, please contact me before Feb.
Publications and Further Research Outputs
Peer-Reviewed Publications
Mimi Zhang and Andrew Parnell, Review of Clustering Methods for Functional Data, ACM Transactions on Knowledge Discovery from Data , 2023
Joshua Tobin, Chin Pang Ho and Mimi Zhang, Reinforced EM Algorithm for Clustering with Gaussian Mixture Models, Proceedings of the 2023 SIAM International Conference on Data Mining (SDM), 2023
Bernard Fares and Mimi Zhang, Incorporating Ignorance within Game Theory: An Imprecise Probability Approach, International Journal of Approximate Reasoning, 2023
Nuno Neto, Sinead O'Rourke, Mimi Zhang, Hannah Fitzgerald, Aisling Dunne and Michael Monaghan, Non-Invasive classification of macrophage polarisation by 2P-FLIM and machine learning, eLife, 11, 2022, pe77373
Mimi Zhang, Matthew Revie and John Quigley, Saddlepoint Approximation for the Generalized Inverse Gaussian Levy Process, Journal of Computational and Applied Mathematics, 411, 2022, p114275
Mimi Zhang and Bin Liu, Discussion of signature‐based models of preventive maintenance, Applied Stochastic Models in Business and Industry, 2022, p1 - 2
Mimi Zhang, Weighted Clustering Ensemble: A Review, Pattern Recognition, 124, 2022, p108428
Muhannad Ahmed Obeidi, Medad Monu, Cian Hughes, Declan Bourke, Merve Nur Dogu, Joshua Francis, Mimi Zhang, Inam Ul Ahad and Dermot Brabazon, Laser beam powder bed fusion of nitinol shape memory alloy (SMA), Journal of Materials Research and Technology, 14, 2021, p2554-2570
Min Xie and Mimi Zhang, Discussion of "Virtual age, is it real?", Applied Stochastic Models in Business and Industry, 37, (1), 2021, p30 - 31
Joshua Tobin and Mimi Zhang, DCF: An Efficient and Robust Density-Based Clustering Method, 2021 IEEE International Conference on Data Mining (ICDM), 2021, p629 - 638
Zhang, M., A heuristic policy for maintaining multiple multi-state systems, Reliability Engineering and System Safety, 203, (107081), 2020
Mimi Zhang, A Heuristic Policy for Maintaining Multiple Multi-State Systems, Reliability Engineering and System Safety, 203, 2020, p107081
Mimi Zhang, Forward-Stagewise Clustering: An Algorithm for Convex Clustering, Pattern Recognition Letters, 128, 2019, p283 - 289
Mimi Zhang and Tim Bedford, Vine Copula Approximation: A Generic Method for Coping with Conditional Dependence, Statistics and Computing, 28, (1), 2018, p219 - 237
Mimi Zhang and Matthew Revie, Continuous-Observation Partially Observable Semi-Markov Decision Processes for Machine Maintenance, IEEE Transactions on Reliability, 66 (1), 2017, p202 - 218
Song, S. and Liu, H. and Zhang, M. and Xie, M., A Bi-level Weibull model with applications to two ordered events, International Journal of Prognostics and Health Management, 8, (2), 2017, p1-9
Mimi Zhang and Min Xie, An Ameliorated Improvement Factor Model for Imperfect Maintenance and Its Goodness of Fit, Technometrics, 59 (2), 2017, p237 - 246
Mimi Zhang and Matthew Revie, Model selection with application to gamma process and inverse Gaussian process, CRC/Taylor & Francis Group, European Safety and Reliability Conference 2016, Glasgow, Sep, 2016
Zhang, M. and Ye, Z. and Xie, M., Optimal burn-in policy for highly reliable products using inverse Gaussian degradation process, Lecture Notes in Mechanical Engineering, 19, 2015, p1003-1011
Mimi Zhang, Olivier Gaudoin and Min Xie, Degradation-Based Maintenance Using Stochastic Filtering for Systems under Imperfect Maintenance, European Journal of Operational Research, 245 (2), 2015, p531 - 541
Mimi Zhang, Zhisheng Ye and Min Xie, A Stochastic EM Algorithm for Progressively Censored Data Analysis, Quality and Reliability Engineering International, 30 (5), 2014, p711 - 722
Zhang, M. and Ye, Z. and Xie, M., A stochastic em algorithm for progressively censored data analysis, Quality and Reliability Engineering International, 30, (5), 2014, p711-722
Mimi Zhang, Zhisheng Ye and Min Xie, A Condition-Based Maintenance Strategy for Heterogeneous Populations, Computers & Industrial Engineering, 77, 2014, p103 - 114
Mimi Zhang, Qingpei Hu, Min Xie and Dan Yu, Lower Confidence Limit for Reliability Based on Grouped Data with a Quantile Filling Algorithm, Computational Statistics & Data Analysis, 75, 2014, p96 - 111
Zhang, M. and Ye, Z. and Xie, M., A condition-based maintenance strategy for heterogeneous populations, Computers and Industrial Engineering, 77, 2014, p103-114
Mimi Zhang, Min Xie and Olivier Gaudoin, A Bivariate Maintenance Policy for Multi-State Repairable Systems with Monotone Process, IEEE Transactions on Reliability, 62 (4), 2013, p876 - 886
Zhang, M. and Xie, M., Degradation modeling using stochastic filtering for systems under imperfect maintenance, Chemical Engineering Transactions, 33, 2013, p7-12
Zhang, M. and Xie, M. and Gaudoin, O., A bivariate maintenance policy for multi-state repairable systems with monotone process, IEEE Transactions on Reliability, 62, (4), 2013, p876-886
Research Expertise
Description
As with most statisticians and data scientists, my research is built on math, probability & statistics and algorithms, with applications in various fields (manufacturing, materials, health, etc.). I like to deal with data-analysis problems that involve mathematical statistics and optimization.Projects
- Title
- Fluorescent Lifetime Imaging Microscopy in Biomedical Applications
- Summary
- a fully funded PhD scholarship by MSCA Doctoral Networks 2021, working on fluorescence microscopy data analysis
- Funding Agency
- European Union
- Date From
- Jan/2023
- Date To
- Dec/2026
- Title
- AIM4HEALTH
- Summary
- artificial intelligence approaches to addressing mental health inequalities in Ireland through improved diet and lifestyle
- Funding Agency
- Higher Education Authority
- Date From
- Sep/2022
- Date To
- Feb/2024
- Title
- Centre for Research Training in Digitally-Enhanced Reality (D-REAL)
- Summary
- a fully funded 4-year PhD scholarship on "Real-time Vision-based Product Placements in Multimedia Videos"
- Funding Agency
- Science Foundation Ireland
- Date From
- Sep/2022
- Date To
- Aug/2026
- Title
- I-Form, the SFI Research Centre for Advanced Manufacturing
- Summary
- a fully funded 4-year PhD scholarship on "Machine Learning for Additive Manufacturing"
- Funding Agency
- Science Foundation Ireland
- Date From
- Sep/2020
- Date To
- Oct/2023