Tapahtumat

Special Seminar: Suvi Wilhelmiina Hämäläinen "Problem-driven Approach to Theory: Highlights and Visions of Teaching and Research"

This talk is arranged at the Department of Computer Science and it's open to everyone free-of-charge. The talk will take place at 14:00 in lecture room AS4, TUAS building.
SpecialSeminar_AaltoEvent

Problem-driven Approach to Theory: Highlights and Visions of Teaching and Research

Suvi Wilhelmiina Hämäläinen

Abstract:

Both my teaching and research could be characterized as a problem-driven approach to theory. In teaching, I have developed and tested different kinds of problem-based learning techniques, in addition to more traditional exercises and use of practical problems in lectures. The problem-based approach has proved to be very successful both in theoretical and difficult courses as well as data science courses where students have heterogeneous background. In this talk, I will introduce some successful techniques and vision how they could be applied in Aalto. In my research, there is a similar tendency: my applied research has revealed open problems and challenges that have motivated my basic research on pattern discovery algorithms and statistical methods. In the talk, I will discuss how to integrate my research interests with teaching and how certain areas like educational data mining could benefit the education in Aalto as a whole.

Bio:

Wilhelmiina Hämäläinen (PhD, computer science) is a researcher of data mining, currently working as a research manager of UEF Bioinformatics center. In the past, she has worked in various teaching and research positions in the fields of computer science and bio-sciences in Finnish universities. Her research interests cover basic and applied research, including efficient algorithms for pattern discovery and computational statistics and applications of data mining to biological and educational data. In addition, she has been engaged in various expert tasks for developing computer science teaching and promoting statistically sound data mining in the scientific community.

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