Martha Arbayani Bin Zaidan - 南京大学

个人简介

Professional Title Sept 2020 Docent/Adjunct Professor in Atmospheric and Environmental Data Sciences, University of Helsinki, Finland Education Mar 2014 Ph.D. in Automatic Control and Systems Engineering, University of Sheffield, UK Nov 2009 MSc. (Eng.) in Control Systems, University of Sheffield, UK Mar 2007 B.Eng. in Electrical Engineering, Trisakti University, Indonesia Work Experience Feb 2021 - present Research Associate Professor, Joint International research Laboratory of Atmospheric and Earth System Sciences, Nanjing University, China Sept 2020 - present Visiting Researcher, Institute for Atmospheric and Earth System Research (INAR), University of Helsinki, Finland Aug 2017 - Aug 2020 Postdoctoral Researcher, Institute for Atmospheric and Earth System Research (INAR), University of Helsinki, Finland Aug 2015 - July 2017 Research Fellow, Aalto Science Institute and Centre of Excellence in Computational Nanoscience, Aalto University, Finland Feb 2015 - June 2015 Visiting Faculty, Department of Mechanical and Industrial Engineering, Sultan Qaboos University, Oman June 2014 - Feb 2015 Research Associate in Centre for Advanced Life Cycle Engineering, University of Maryland at College Park, USA Honors and Awards Aalto Science Fellowship, funded by Aalto Science Institute (AScI) and Centre of Excellence in Computational Nanoscience (COMP), Aalto University, Finland. Dorothy Hodgkin Postgraduate Award (DHPA) by Rolls-Royce plc and En- gineering & Physical Sciences Research Council (EPSRC) for pursuing research in the field of Prognostics Health Monitoring (PHM) of aerospace gas turbine engines in Rolls-Royce UTC, in Dept. of Automatic Control & Systems Engineering at the University of Sheffield, 2010-2014. First class with distinction in both MSc. (Eng.) and B.Eng. degrees. Best Graduate in Engineering 2007 by Trisakti University, Indonesia.

研究领域

Artificial intelligence and data sciences for systems monitoring (atmospheric and environmental sciences as well as engineering systems) Sensors calibrations and virtual sensors Complex systems modelling and control systems engineering

近期论文

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M.A. Zaidan, N.H. Motlagh, P.L. Fung, D. Lu, H. Timonen, J. Kuula, Jarkko V. Niemi, S. Tarkoma, T. Pet?j?, M. Kulmala, and T. Hussein. Intelligent calibration and virtual sensing for integrated low-cost air quality sensors. IEEE Sensors Journal, 20(22):13638–13652, 2020. M.A. Zaidan, O. Surakhi, P.L. Fung, and T. Hussein. Sensitivity analysis for predicting sub- micron aerosol concentrations based on meteorological parameters. Sensors, 20(10):2876, 2020. M.A. Zaidan, D. Wraith, B.E. Boor, and T. Hussein. Bayesian proxy modelling for esti- mating black carbon concentrations using white-box and black-box models. Applied Sciences, 9(22):4976, 2019. M.A. Zaidan, L. Dada, M.A. Alghamdi, H. Al-Jeelani, H. Lihavainen, A. Hyv?rinen, and T. Hussein. Mutual information input selector and probabilistic machine learning utilisation for air pollution proxies. Applied Sciences, 9(20):4475, 2019. M.A. Zaidan, V. Haapasilta, R. Relan, P. Paasonen, V.-M. Kerminen, H. Junninen, M. Kul- mala, and A. S. Foster. Exploring non-linear associations between atmospheric new-particle formation and ambient variables: a mutual information approach. Atmospheric Chemistry and Physics, 18(17):12699–12714, 2018. M.A. Zaidan, V. Haapasilta, R. Relan, H. Junninen, P.P. Aalto, M. Kulmala, L. Laurson, and A.S. Foster. Predicting atmospheric particle formation days by Bayesian classification of the time series features. Tellus B: Chemical and Physical Meteorology, 70(1):1–10, 2018. M.A. Zaidan, F.F. Canova, L. Laurson, and A.S. Foster. Mixture of Clustered Bayesian Neural Networks for modeling friction processes at the nanoscale. Journal of Chemical Theory and Computation, 13:3–8, 2017. M.A. Zaidan, A.R. Mills, R.F. Harrison, and P.J. Fleming. Gas turbine engine prognostics using Bayesian hierarchical models: a variational approach. Mechanical Systems and Signal Processing, 70–71:120–140, 2016. M.A. Zaidan, R. Relan, A.R. Mills, and R.F. Harrison. Prognostics of gas turbine engine: An integrated approach. Expert Systems with Applications, 42(22):8472–8483, 2015. M.A. Zaidan, R.F. Harrison, A.R. Mills, and P.J. Fleming. Bayesian hierarchical models for aerospace gas turbine engine prognostics. Expert Systems with Applications, 42(1):539–553, 2015.

学术兼职

Members in various scientific organizations, including: European Geosciences Union (EGU) member (2020 - present) Nordic Society for Aerosol Research (NOSA) member (2020 - present) Institution of Engineering and Technology (IET) member (2019 - present) Finnish Association of Aerosol Research (FAAR) member (2018 - present) Institute of Electrical and Electronics Engineers (IEEE) member (2014 - present) Institute of Electrical and Electronics Engineers (IEEE) student member (2010 - 2014) The Royal Aeronautical Society (RAeS) student member (2010 - 2014) Reviewers for various scientific journals, including: Advances in Engineering Software (Elsevier) Aerospace Science and Technology (Elsevier) Applied Energy (Elsevier) Applied Sciences (MDPI) Atmospheric Chemistry and Physics (Copernicus) Electronics (MDPI) Energies (MDPI) Expert Systems with Applications (Elsevier) IEEE Transactions on Automation Science and Engineering (IEEE) IEEE Transactions on Reliability (IEEE) INKOM Journal - Journal of Informatics, Control Systems, and Computers (Indonesian Institute of Sciences) International Journal of Advanced Manufacturing Technology (Springer) Mechanical Science and Technology (Springer) Mechanical Systems and Signal Processing (Elsevier) Microelectronics Reliability (Elsevier) Neurocomputing (Elsevier) Sensors (MDPI) Editorial Services Associate Editor for Journal of Communication in Science and Technology (KIPMI). Guest Editor for Special Issue on 'Data Fusion/Assimilation of Low-Cost Sensors for Air Pollution Exposure' in International Journal of Environmental Research and Public Health (MDPI). Editor for International Journal of Bio-Inspired Computation (Inderscience Publishers Ltd.)