Teaching

Teaching is an enjoyable and inspiring part of my work, especially knowing I contribute to preparing the next generation of technologists. I teach subjects ranging from the mathematical foundations of deep neural networks to applied deep learning and state-of-the-art AI applications. Sharing knowledge and experiences in these areas is rewarding, as it helps students grasp both theory and practical use. Students interested in research are also encouraged to participate in the Students' Scientific Association Conference (TDK).

Year	Submission	Supervised student	Thesis title
2025	BSc Thesis	Gergő Kerényi	Parking Garage Traffic Control System
2023	MSc Thesis, TDK 2nd prize	Muhammad Luqman Hakim	Personality Recognition Based on Visual and Movement Features on the Face

Each semester, we build on this foundation through collaborative projects that often continue within our research group, sometimes even leading to scientific publications. This ongoing connection between teaching and research creates a motivating environment for students to deepen their skills and contribute meaningfully to the field.

Academic Year/Semester	Course Code	Course Name
2019/20/1	IPM-18sztKVMNG IPM-18AUTADLEG	Mathematical basis of deep neural networks L. Applied Deep Learning Pr.
2020/21/1	IPM-18sztKVMNG IPM-18AUTADLEG	Mathematical basis of deep neural Networks L. Applied Deep Learning Pr.
2020/21/2	IPM-18sztKVMNG IPM-19fmiAMLEG	Mathematical basis of deep neural networks L. Advanced Machine Learning Pr.
2021/22/1	IPM-18sztKVMNG IPM-18sztKVMNAG	Mathematical basis of deep neural networks L. State-of-the-art applications of deep neural networks Pr.
2021/22/2	IPM-18sztKVMNG IPM-18sztKVMNAG	Mathematical basis of deep neural networks L. State-of-the-art applications of deep neural networks Pr.
2022/23/1	IPM-22fmiAMLEG	Advanced Deep Network Development L.+Pr.
2022/23/2	IPM-22fmiAMLEG	Advanced Deep Network Development L.+Pr.
2024/25/2	IPM-22AUTDNDEG IPM-22fmiAMLEG	Deep Network Development L.+Pr. Advanced Deep Network Development L.+Pr.