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B115 ( Jon Lilletuns vei 3, Grimstad )

Michael obtained a first-class BEng degree in Computer Systems Engineering from Bangor University (Wales) in 2018. He was awarded the Data Lab scholarship (Scotland's Innovation Centre for AI), and in 2020 he received an MSc degree with distinction in Artificial Intelligence from the University of Aberdeen (Scotland). 

During the summer of 2017, he worked as a control systems intern for Zeeko Ltd at National Facility for Ultra-Precision surfaces (UK), where he was involved in developing an automated system for optics manufactury. Since 2020 he is involved with the Ultra-Precision Surfaces research group based at the University of Huddersfield (England), where he is responsible for the process automation, prototyping, and software implementation for the Swing Arm Profilometer project. 

His current research focuses on the application of machine learning for ultra-precision process control and optimization. He is particularly interested in AI and ML applied to the engineering and manufacturing sectors as well as concepts such as Industry 4.0, cyber-physical systems, automation, and digitalisation.

Scientific publications

  • Walker, David; Ahuir-Torres, Juan I.; Akar, Yasemin; Bingham, Paul A.; Chen, Xun; Darowski, Michal; Fähnle, Oliver; Gambron, Philippe; Jackson, Frankie F.; Li, Hongyu; Mason, Luke; Mishra, Rakesh; Shahjalal, Abdullah; Yu, Guoyu (2023). Bridging the Divide Between Iterative Optical Polishing and Automation. Nanomanufacturing and Metrology. ISSN: 2520-811X. doi:10.1007/s41871-023-00197-3.
  • Darowski, Michal; Aftab, Muhammad Faisal; Li, Hongyu; Walker, David; Yu, Guoyu; An, Chenghui; Omlin, Christian Walter Peter (2023). Towards Data-Driven Material Removal Rate Estimation in Bonnet Polishing. International Conference on Control, Mechatronics and Automation. ISSN: 2837-5114. s 473 - 479. doi:10.1109/ICCMA59762.2023.10375024.

Last changed: 3.06.2022 13:06