Professor Dr. Hanne Kekkonen
Assistant Professor
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Biography
Hanne Kekkonen is an Assistant Professor at TU Delft, specializing in statistical inverse problems and uncertainty quantification. She has a strong academic background with significant positions, including Research Fellow at the University of Cambridge and the University of Warwick. Her research interests primarily focus on Bayesian non-parametric models. Throughout her career, Kekkonen has contributed to several notable publications in the field, including work on Crocheting Bour's Minimal Surfaces and Random Tree Besov Priors. She has also engaged in teaching various courses related to statistical learning and inverse problems. She completed her PhD at the University of Helsinki, focusing on mathematical methods applicable to statistical analysis. Kekkonen has demonstrated an ongoing commitment to academic excellence and innovation in her research, contributing to the understanding of complex mathematical concepts in practical applications.
Research Interests
Experience
Assistant Professor (tenured)
2020-02-01 — PresentTU Delft • Delft, Netherlands
Engaged in research and teaching in the field of statistical inverse problems.
Research Fellow
2017-09-01 — 2020-01-31University of Cambridge • Cambridge, UK
Conducted research in advanced statistical methods.
Research Fellow
2016-03-01 — 2017-08-31University of Warwick • Warwick, UK
Focused on statistical modeling and its applications.
PhD Student
2011-09-01 — 2016-02-01University of Helsinki • Helsinki, Finland
Researched mathematical aspects of statistical inference.
Requirements for Delft University of Technology
Master Program
Requirements
GPA Requirement
IELTS
TOEFL
GRE General
Prerequisites
Application Checklist
- Bachelor's degree certificate
- Academic transcript
- English language certificate
- Curriculum Vitae (CV)
- Motivation letter
- Two letters of recommendation
- Identity document (Passport)
- GRE General Test results (for international diplomas)
Specialization Notes
Requirements apply generally across engineering and science master programs. Specific tracks like Architecture require a digital portfolio.