Adrian Derstroff
Room 606 (Einsteinstr. 62, 48149 Münster)
Tel: 0251 83-33752
Publications
- Evers, Marina, Derstroff, Adrian, Leistikow, Simon, Schneider, Tom, Mallepree, Larissa, Stampke, Jan, Leisgang, Moritz, Sprafke, Sebastian, Schuhl, Melina, Krefft, Niklas, Droese, Felix, and Linsen, Lars. . “Visual analytics of soccer player performance using objective ratings.” Information Visualization, № 1–15 doi: 10.1177/14738716231220539.
- Derstroff, Adrian, Leistikow, Simon, Nahardani, Ali, Gruen, Katja, Franz, Marcus, Hoerr, Verena, and Linsen, Lars. . “Interactive visual formula composition of multidimensional data classifiers.” Information Visualization doi: 10.1177/14738716241270288.
- Borrelli, Gabriel, Hagemann, Lars, Steinkühler, Jannik, Derstroff, Adrian, Evers, Marina, Huesmann, Karim, Leistikow, Simon, Rave, Hennes, Gol, Reyhaneh Sabbagh, and Linsen, Lars. . “2022 IEEE Scientific Visualization Contest Winner: Multifield Analysis of Vorticity-Driven Lateral Spread in Wildfire Ensembles.” IEEE Computer Graphics and Applications, № 44 (1): 40–49. doi: 10.1109/MCG.2023.3310298.
- Derstroff, A, Leistikow, S, Nahardani, A, Ebrahimi, M, Hoerr, V, and Linsen, L. . “Explorative Visual Analysis of Spatio-temporal Regions to Detect Hemodynamic Biomarker Candidates.” contributed to the EuroVis 2022, Rom
- Borrelli, G., Hagemann, L., Steinkühler, J., Derstroff, A., Evers, M., Huesmann, K., Leistikow, S., Rave, H., Gol, R.S., and Linsen, L. . “How Wildfires Spread and Why: Visual Multi-field Analysis of Vorticity-driven Lateral Spread Ensembles.” in Proceedings of IEEE VIS 2022 - Winner of the SciVis Contest 2022, edited by -. New York City: Wiley-IEEE Press.
- Evers, M, Leistikow, S, Derstroff, A, Gerrits, T, Huesmann, K, Hollenbeck, J, Seljami, J, and Linsen, L. . “Visual Analysis of Spatio-temporal Features in Multi-field Earth's Mantle Convection Simulations.” in Proceedings of IEEE VIS 2021, edited by -. New York City: Wiley-IEEE Press.
- Hamid, S, Derstroff, A, Klemm, S, Ngo, Q.Q., Jiang, X, and Linsen, L. . “Visual ensemble analysis to study the influence of hyper-parameters on training deep neural networks.” in Machine Learning Methods in Visualisation for Big Data, edited by Daniel and Nabney Archambault and Jaakko Ian and Peltonen. Eindhoven: Eurographics Association. doi: 10.2312/mlvis.20191160.