معرفی
Ainsley Miller is a Teaching Fellow in the Department of Mathematics and Statistics at the University of Strathclyde, Faculty of Science. She has held this position since August 2019 and currently serves as the Year 2 Co-ordinator and MSc Project Co-ordinator. She is deeply involved in both undergraduate and postgraduate teaching and supervision.
Her educational background is rooted at Strathclyde, where she earned her BSc (Hons) in Mathematics, Statistics, and Economics and completed her interdisciplinary PhD involving Electronic and Electrical Engineering and the National Physical Laboratory.
Ainsley's research centers on pedagogical innovation, particularly student mental health and the transition from school to university. She is a qualified mental health first aider and leads a Mental Health Support Service within her department. Her technical research spans photogrammetry, metrology, and refractive index reconstruction, reflecting her interdisciplinary training.
Her recent publications show a dual focus: educational research on anxiety in learning statistical programming and authentic assessment, alongside applied mathematical work in optical metrology. These works demonstrate strong engagement with both teaching innovation and engineering applications.
- Faculty of Science Teaching Excellence Award - Teaching Innovation (2022)
- Nominee, Strathclyde Teaching Excellence Awards (2021)
- Faculty of Science Teaching Excellence Award - Team Award (2021)
- Best Student who Tutors (2019)
- Finalist, STEM for Britain (2018)
- Best presentation by an early stage researcher (2017)
Ainsley actively supervises undergraduate and MSc dissertations and is a co-investigator on externally funded educational projects such as 'Re-engaging Students in Learning Development through Subject Specific Resources' and 'Supporting students during their transition to university.' She regularly contributes to teaching development events as an invited speaker.
She is involved in multiple teaching modules including Probability and Statistical Inference, Inference and Regression Modelling, Medical Statistics, and Statistical Machine Learning, both on-campus and online. Her leadership in curriculum design and student support highlights her integral role in the academic community.
