Martha Arbayani Zaidan, PhD
Affiliations: | 2017- | Helsinki University |
Area:
Machine Learning, Control Systems Engineering, Prognostics Health MonitoringWebsite:
https://sites.google.com/site/marthaarbayanizaidan/Google:
"https://scholar.google.fi/citations?user=kAZnkMoAAAAJ&hl=en&oi=sra"Parents
Sign in to add mentor| Peter J. Fleming | grad student | 2010-2014 | The University of Sheffield |
| Robert F. Harrison | grad student | 2010-2014 | The University of Sheffield |
| Markku Kulmala | post-doc | 2017- | Helsingin Yliopisto / University of Helsinki (Chemistry Tree) |
| Adam S. Foster | post-doc | 2015-2017 | Aalto University |
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Publications
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| Fung PL, Savadkoohi M, Zaidan MA, et al. (2024) Constructing transferable and interpretable machine learning models for black carbon concentrations. Environment International. 184: 108449 |
| Fung PL, Sillanpää S, Niemi JV, et al. (2022) Improving the current air quality index with new particulate indicators using a robust statistical approach. The Science of the Total Environment. 157099 |
| Alghamdi MA, Al-Hunaiti A, Arar S, et al. (2019) A Predictive Model for Steady State Ozone Concentration at an Urban-Coastal Site. International Journal of Environmental Research and Public Health. 16 |
| Zaidan MA, Wraith D, Boor BE, et al. (2019) Bayesian Proxy Modelling for Estimating Black Carbon Concentrations using White-Box and Black-Box Models Applied Sciences. 9: 4976 |
| Zaidan MA, Haapasilta V, Relan R, et al. (2018) Predicting atmospheric particle formation days by Bayesian classification of the time series features Tellus B: Chemical and Physical Meteorology. 70: 1-10 |
| Zaidan MA, Canova FF, Laurson L, et al. (2016) Mixture of Clustered Bayesian Neural Networks for Modeling Friction Processes at the Nanoscale. Journal of Chemical Theory and Computation |
| Zaidan MA, Mills AR, Harrison RF, et al. (2016) Gas turbine engine prognostics using Bayesian hierarchical models: A variational approach Mechanical Systems and Signal Processing. 70: 120-140 |
| Zaidan MA, Relan R, Mills AR, et al. (2015) Prognostics of gas turbine engine: An integrated approach Expert Systems With Applications. 42: 8472-8483 |
| Zaidan MA, Harrison RF, Mills AR, et al. (2015) Bayesian Hierarchical Models for aerospace gas turbine engine prognostics Expert Systems With Applications. 42: 539-553 |