Teaching

Courses (LUT University)

1. BM40A1601 · Foundations of Artificial Intelligence and Machine Learning. Blended teaching, Lappeenranta and Lahti campuses. Fall 2024 and Fall 2025 (TA for two consecutive editions; the 2025 edition ran 1 September to 12 December). Introduction to AI and ML for engineering students: classical learning algorithms, neural networks, evaluation, and a hands-on project.
2. BM40A0202 · Foundations of Computer Science. Blended teaching, Lappeenranta. 7 January 2026 to 17 April 2026. Core CS foundations for engineering students: algorithms, data structures, computational thinking, programming practice.

AMC-Lahti Summer School

The summer school Application of AI / ML techniques in Atmospheric Science is a one-week intensive co-organised by the Atmospheric Modelling Centre in Lahti. It pairs introductory lectures on atmospheric topics (atmospheric chemistry, aerosol dynamics, Earth-system models, numerical weather prediction) with a computational track covering data science and machine learning, then sends mixed-discipline groups into a hands-on project.

1. Hands-on training. About half of the course is project work. Each group trains an end-to-end neural network (LSTM, RNN, Transformer) on a curated atmospheric dataset.
2. Practical infrastructure. Students get up to speed with GPU workflows on Google Colab or local machines, and use CUDA-enabled deep-learning frameworks (PyTorch).
3. Advanced topics. For motivated students, the programme covers data visualisation, analysis, and model optimisation.
4. Final presentations. Each group presents its outcome and discusses the trade-offs of the approach used.

The 2025 edition ran 11–15 August 2025 at the University of Helsinki, Lahti campus, with 25 participants (13 anonymous feedback responses). The 2024 edition had 21 participants (11 feedback responses). The next edition is scheduled for August 2027.

Resources

AMC-Lahti education LUT Computational Engineering CVPRL lab UH Multi-Scale Modelling summer school