Dr. Mimi Zhang

• Mimi Zhang and Tim Bedford, Vine Copula Approximation: A Generic Method for Coping with Conditional Dependence, Statistics and Computing, 28, (1), 2018, p219 - 237Journal Article, 2018, TARA - Full Text
• Mimi Zhang and Min Xie, An Ameliorated Improvement Factor Model for Imperfect Maintenance and Its Goodness of Fit, Technometrics, 59 (2), 2017, p237 - 246Journal Article, 2017, TARA - Full Text
• Mimi Zhang and Matthew Revie, Continuous-Observation Partially Observable Semi-Markov Decision Processes for Machine Maintenance, IEEE Transactions on Reliability, 66 (1), 2017, p202 - 218Journal Article, 2017, TARA - Full Text
• 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 - 541Journal Article, 2015, TARA - Full Text
• 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 - 111Journal Article, 2014, TARA - Full Text
• Mimi Zhang, Zhisheng Ye and Min Xie, A Condition-Based Maintenance Strategy for Heterogeneous Populations, Computers & Industrial Engineering, 77, 2014, p103 - 114Journal Article, 2014, TARA - Full Text
• 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 - 886Journal Article, 2013, TARA - Full Text
• 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 - 722Journal Article, 2014, TARA - Full Text
• Mimi Zhang, Weighted Clustering Ensemble: A Review, Pattern Recognition, 124, 2022, p108428Journal Article, 2022, TARA - Full Text
• Mimi Zhang, Forward-Stagewise Clustering: An Algorithm for Convex Clustering, Pattern Recognition Letters, 128, 2019, p283 - 289Journal Article, 2019, TARA - Full Text
• Min Xie and Mimi Zhang, Discussion of "Virtual age, is it real?", Applied Stochastic Models in Business and Industry, 37, (1), 2021, p30 - 31Journal Article, 2021
• Mimi Zhang, A Heuristic Policy for Maintaining Multiple Multi-State Systems, Reliability Engineering and System Safety, 203, 2020, p107081Journal Article, 2020, TARA - Full Text
• 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, p2554-2570Journal Article, 2021, DOI , URL
• Joshua Tobin and Mimi Zhang, DCF: An Efficient and Robust Density-Based Clustering Method, 2021 IEEE International Conference on Data Mining (ICDM), 2021 IEEE International Conference on Data Mining (ICDM), Auckland, New Zealand, 7 - 10 Dec, 2021, 2021, pp629 - 638Conference Paper, 2021, TARA - Full Text
• Mimi Zhang, Matthew Revie and John Quigley, Saddlepoint Approximation for the Generalized Inverse Gaussian Levy Process, Journal of Computational and Applied Mathematics, 411, 2022, p114275Journal Article, 2022, TARA - Full Text
• Mimi Zhang and Bin Liu, Discussion of signature-based models of preventive maintenance, Applied Stochastic Models in Business and Industry, 39, (1), 2022, p54 - 56Journal Article, 2022
• 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, pe77373Journal Article, 2022
• Mimi Zhang and Andrew Parnell, Review of Clustering Methods for Functional Data, ACM Transactions on Knowledge Discovery from Data, 17, (7), 2023, p1 - 34Journal Article, 2023
• Bernard Fares and Mimi Zhang, Incorporating Ignorance within Game Theory: An Imprecise Probability Approach, International Journal of Approximate Reasoning, 154, (March), 2023, p133 - 148Journal Article, 2023, TARA - Full Text
• 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 SIAM International Conference on Data Mining (SDM), Minnesota, U.S., 27 - 29 April, 2023, 2023, pp118 - 126Conference Paper, 2023, TARA - Full Text
• Joshua Tobin and Mimi Zhang, A Theoretical Analysis of Density Peaks Clustering and the Component-wise Peak-Finding Algorithm, IEEE Transactions on Pattern Analysis and Machine Intelligence, 46, (2), 2024, p1109 - 1120Journal Article, 2024, TARA - Full Text
• Emmanuel Akeweje and Mimi Zhang, Learning Mixtures of Gaussian Processes through Random Projection, Proceedings of the 41st International Conference on Machine Learning (ICML 2024), 41st International Conference on Machine Learning, Vienna, Austria, 21 - 27 July, 2024, 2024Conference Paper, 2024, TARA - Full Text
• Pangbo Ren, Charles Stuart, Mimi Zhang, Ryosuke Inomata, Kazuaki Nakamura, Isao Morita, Stephen Spence, Investigation of the surrogate model in an ANN-Meanline Hybrid model for Radial Turbine Performance Prediction, International Journal of Gas Turbine, Propulsion and Power Systems, 15, (2), 2024, p9 - 18Journal Article, 2024, DOI , TARA - Full Text
• Sukriti Dhang, Mimi Zhang and Soumyabrata Dev, AdSegNet: A deep network to localize billboard in outdoor scenes, Signal, Image and Video Processing, 18, 2024, p7221 - 7235Journal Article, 2024
• Joshua Tobin, Michaela Black, James Ng, Debbie Rankin, Jonathan Wallace, Catherine Hughes, Leane Hoey, Adrian Moore, Jinling Wang, Geraldine Horigan, Paul Carlin, Helene McNulty, Anne M Molloy and Mimi Zhang, Co-Clustering Multi-View Data Using the Latent Block Model, Computational Statistics & Data Analysis, 2024Journal Article, 2024
• Guangchen Wang, Michael Monaghan and Mimi Zhang, Parallelizing Adaptive Reliability Analysis through Penalizing the Learning Function, IEEE Transactions on Reliability, 2024Journal Article, 2024, TARA - Full Text

• 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, UK, 25 " 29 Sep, 2016, 2016Conference Paper, TARA - Full Text
• Mimi Zhang, Andrew Parnell, Dermot Brabazon and Alessio Benavoli, Bayesian Optimisation for Sequential Experimental Design with Applications in Additive Manufacturing, arXiv, 2021Review Article
• Mimi Zhang and Min Xie, Degradation modeling using stochastic filtering for systems under imperfect maintenance, Chemical Engineering Transactions, Prognostics and System Health Management Conference (PHM 2013), Milan, Italy, 8-11 Sep, 2013, 33, 2013, pp7 - 12Conference Paper
• Mimi Zhang, Zhisheng Ye and Min Xie, Optimal Burn-in Policy for Highly Reliable Products Using Inverse Gaussian Degradation Process, Proceedings of the 8th World Congress on Engineering Asset Management (WCEAM 2013) & the 3rd International Conference on Utility Management & Safety (ICUMAS), 8th World Congress on Engineering Asset Management (WCEAM 2013), Hong Kong, China, 30 Oct -1 Nov, 2013, 2013, pp1003 - 1011Conference Paper
• Zhisheng Ye, Mimi Zhang and Xun Xiao, An inspection-maintenance strategy for heterogeneous systems with measurable degradation, 2013 IEEE International Conference on Industrial Engineering and Engineering Management, 2013 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), Bangkok, Thailand, 10-13 Dec, 2013, 2013, pp1432 - 1437Conference Paper

My academic journey spans from a foundation in mathematical statistics during my undergraduate studies to a focus on optimization algorithms and their applications in my doctoral and postdoctoral research. This interdisciplinary background integrates mathematics, probability, statistics, and algorithms to address diverse challenges across sectors like manufacturing, materials science, and healthcare. Since becoming an independent researcher, my primary focus has been on cluster analysis, where I specialize in developing methodological, theoretical, and computational approaches for analyzing diverse data types, including multivariate, functional, and image data. In particular, functional data clustering aims to identify patterns across subjects, where each subject is represented by a continuous function. This technique has broad applications across various fields, such as grouping gene expression profiles in bioinformatics, economic time series in econometrics, and mechanical system vibrations in engineering. Complementing my work in cluster analysis, my research portfolio extends to Bayesian Optimization -- a methodology designed to find the maximum (or minimum) of an unknown function, which is typically expensive to evaluate. The goal is to iteratively select the next best point to evaluate in order to efficiently search for the optimal solution. My collaborations in Bayesian optimization with academic and industry partners have afforded me the opportunity to address real-world challenges, a pursuit that I find immensely rewarding and fulfilling.

• Title

  FLImagin3D: Fluorescent Lifetime Imaging Microscopy in Biomedical Applications
  Summary

  beneficiary of the 2021 MSCA Doctoral Networks FLImagin3D, working on fluorescence microscopy data analysis
  Funding Agency

  European Union
  Date From

  Jan/2023
  Date To

  Dec/2026
• Title

  I-Form, the SFI Research Centre for Advanced Manufacturing
  Summary

  funded investigator for I-Form Phase 1, working on AM process feedback and control
  Funding Agency

  Science Foundation Ireland
  Date From

  Nov/2017
  Date To

  Oct/2023
• Title

  AIM4HEALTH
  Summary

  co-PI of the North-South Research Programme 2021 AIM4HEALTH, developing machine learning techniques to address mental health inequalities in Ireland
  Funding Agency

  Higher Education Authority
  Date From

  Sep/2022
  Date To

  Feb/2024
• Title

  I-Form, the SFI Research Centre for Advanced Manufacturing
  Summary

  funded investigator for I-Form Phase 2, working on AM process feedback and control
  Funding Agency

  Science Foundation Ireland
  Date From

  Nov/2023
  Date To

  Oct/2029

Mechanical engineering, Artificial intelligence and machine learning, Theory of computation, Mathematical Sciences,

• Award of Excellence in Supervision of Research Students (Runner Up) 2024