Burkhard Schaffrin joined OSU's Geodetic Science Program in 1989 as an expert in mathematical and statistical methods. His main interests are developing new estimation techniques for ever more complex observation models to enhance the retrieval of valuable information from the measurements in terms of accuracy, reliability, and computational efficiency. Such novel techniques include the use of wavelets for image de-blurring, the application of criterion matrices for geodetic network optimization, the employment of the Total Least-Squares approach to semivariogram fitting, and the formulation of simple criteria for the equivalence of rather complicated models. Most recently, he has succeeded in determining Tykhonov’s regularization parameter in an ill-posed problem directly from the data by exploiting the analogy to a variance component ratio. Its performance in the case of combining GRACE satellite data with a hydrological model in the Amazon basin turned out rather convincing. Burkhard Schaffrin has been a fellow of the Intl. Assoc. of Geodesy (IAG) for more than 15 years. He has won several further awards, published over 150 papers, roughly half of them in peer-reviewed outlets, and is currently on the editorial boards of two geodetic journals. He is also the co-author of two textbooks and the sole author of two monographs.