Lösel Philipp

Dr. Philipp Lösel

Phone: +49 6221 54 14537
Room: 1/411
philipp.loesel <_at_> uni-heidelberg.de

Postdoc

Office address/Post address

Engineering Mathematics and Computing Lab (EMCL)
Interdisciplinary Center for Scientific Computing (IWR)
Im Neuenheimer Feld 205
69120 Heidelberg (Germany)

Short Biography

Studies in Mathematics and Political Science at Heidelberg University (2008-2013).
From 2013 to 2015, I was a lecturer in Mathematics at the Institute of Pharmacy and Molecular Biotechnology (IPMB) at Heidelberg University.
From November 2014 to September 2019, I was a research associate at the Engineering Mathematics and Computing Lab (EMCL) at Heidelberg University.
From October 2019 to September 2021, I was a research associate in the research group Data Mining and Uncertainty Quantification (DMQ) at the Heidelberg Institute for Theoretical Studies (HITS).
Since October 2021, I've been working as a research associate and since April 2022 as a Postdoc at the Engineering Mathematics and Computing Lab (EMCL) at Heidelberg University and as a guest researcher at the Heidelberg Institute for Theoretical Studies (HITS).

Research Interests

Biomedical Image Analysis & Segmentation
Artificial Intelligence & Deep Learning
High Performance Computing
Hardware-Aware Computing
Uncertainty Quantification
Computational Geometry

Projects

Previous Projects

Teaching

Teaching assistant for Numerical Methods for Ordinary Differential Equations (summer term 2020)
Teaching assistant for Introduction to Numerics (winter term 2019/2020)
Lecturer in Mathematics for Molecular Biotechnology (Lecture Notes) (winter term 2013/14, summer term 2014, winter term 2014/15)
Lecturer in Mathematical and Statistical Methods for Pharmacy (Lecture Notes) (winter term 2013/14)

Publications

Monchanin, C., Drujont, E., Le Roux, G., Lösel, P., Barron, A., Devaud, J.-M., Elger, A., & Lihoreau, M. Environmental exposure to metallic pollution impairs honey bee brain development and cognition. Preprint at Authorea (2023).
Lösel, P.D., Monchanin, C., Lebrun, R. , Jayme, A., Relle, J., Devaud, J.-M., Heuveline, V., & Lihoreau, M. Natural variability in bee brain size and symmetry revealed by micro-CT imaging and deep learning. Preprint at bioRxiv (2022).
Lösel, P.D. GPU-basierte Verfahren zur Segmentierung biomedizinischer Bilddaten. Dissertation (2022).
Nessel, R., Löffler, T., Rinn, J., Lösel, P., Voss, S., Heuveline, V., Vollmer, M., Görich, J., Ludwig, Y.M., Al-Hileh, L., & Kallinowski, F. Primary and Recurrent Repair of Incisional Hernia Based on Biomechanical Considerations to Avoid Mesh-Related Complications. Front. Surg. 8, 764470 (2021).
Kallinowski, F., Ludwig, Y., Gutjahr, D., Gerhard, C., Schulte-Hörmann, H., Krimmel, L., Lesch, C., Uhr, K., Lösel, P., Voß, S., Heuveline, V., Vollmer, M., Görich, J. & Nessel, R. Biomechanical Influences on Mesh-Related Complications in Incisional Hernia Repair. Front. Surg. 8, 763957 (2021).
Jayme, A., Lösel, P.D., Fischer, J. & Heuveline, V. Comparison of Machine Learning Methods for Predicting Employee Absences. Preprint Series of the Engineering Mathematics and Computing Lab 2 (2021).
Kallinowski, F., Ludwig, Y., Löffler, T., Vollmer, M., Lösel, P.D., Voß, S., Görich, J., Heuveline, V. & Nessel, R. Biomechanics applied to incisional hernia repair – Considering the critical and the gained resistance towards impacts related to pressure. Clin Biomech 82, 105253 (2021).
Lösel, P.D., van de Kamp, T., Jayme, A., Ershov, A., Faragó, T., Pichler, O., Tan Jerome, N., Aadepu, N., Bremer, S., Chilingaryan, S.A., Heethoff, M., Kopmann, A., Odar, J., Schmelzle, S., Zuber, M., Wittbrodt, J., Baumbach, T. & Heuveline, V. Introducing Biomedisa as an open-source online platform for biomedical image segmentation. Nat. Commun. 11, 5577 (2020).
Haupt, S., Fard-Rutherford, N., Lösel, P.D., Grenacher, L., Mehrabi, A. & Heuveline, V. Mathematical Clustering Based on Cross-Sections in Medicine: Application to the Pancreatic Neck. Preprint Series of the Engineering Mathematics and Computing Lab 1 (2020).
van de Kamp, T., Schwermann, A.H., dos Santos Rolo, T., Lösel, P.D., Engler, T., Etter, W., Faragó, T., Göttlicher, J., Heuveline, V., Kopmann, A., Mähler, B., Mörs, T., Odar, J., Rust, J., Tan Jerome, N., Vogelgesang, M., Baumbach, T. & Krogmann, L. Parasitoid biology preserved in mineralized fossils. Nat. Commun. 9, 3325 (2018).
Mexner, W., Bonn, M., Kopmann, A., Mauch, V., Ressmann, D., Chilingaryan, S.A., Jerome, N.T., van de Kamp, T., Heuveline, V., Lösel, P., Schmelzle, S. & Heethoff, M. OpenGL® API-based analysis of large datasets in a cloud environment. In Design and Use of Virtualization Technology in Cloud Computing (eds Das, P.K. et al.) 161-181 (IGI Global, Hershey, 2018).
Gawlok, S., Gerstner, P., Haupt, S., Heuveline, V., Kratzke, J., Lösel, P., Mang, K., Schmidtobreick, M., Schoch, N., Schween, N., Schwegler, J., Song, C. & Wlotzka, M. HiFlow3 – Technical Report on Release 2.0. Preprint Series of the Engineering Mathematics and Computing Lab 6 (2017).
Schmelzle, S., Heethoff, M., Heuveline, V., Lösel, P., Becker, J., Beckmann, F., Schluenzen, F., Hammel, J.U., Kopmann, A., Mexner, W., Vogelgesang, M., Tan Jerome, N., Betz, O., Beutel, R., Wipfler, B., Blanke, A., Harzsch, S., Hörnig, M., Baumbach, T. & van de Kamp, T. The NOVA project: maximizing beam time efficiency through synergistic analyses of SRμCT data. Proc. SPIE 10391, 103910P (2017).
Lösel, P. & Heuveline, V. A GPU based diffusion method for whole-heart and great vessel segmentation. In Reconstruction, Segmentation, and Analysis of Medical Images (eds Zuluaga, M. et al.) 121–128 (Springer, Cham, 2017).
Lösel, P. & Heuveline, V. Enhancing a diffusion algorithm for 4D image segmentation using local information. Proc. SPIE 9784, 97842L (2016).

Invited Talks

Large-scale analysis of the bee brain using micro-CT imaging and the online segmentation platform Biomedisa
HITS Scientific Seminar Series, AIN, HITS, Heidelberg, Germany, December 5, 2022, on invitation by Dr. Kai Polsterer.
Large-scale analysis of the honey bee brain using micro-CT imaging and the online segmentation platform Biomedisa
BMIT user workshop on X-ray micro-CT data processing, Canadian Light Source (CLS), Saskatoon, Canada, online, October 6, 2022, on invitation by Dr. Sergey Gasilov.
Large-scale analysis of the honey bee brain using micro-CT imaging and deep learning
Stockholm University Brain Imaging Centre (SUBIC), Stockholm, Sweden, online, October 7, 2021, on invitation by Dr. Tunhe Zhou.
Fast synchrotron X-ray imaging and semi-automated analysis of extant and fossil insects
BASF, Ludwigshafen, Germany, April 19, 2018, on invitation by Dr. Paul Birnbrich.
The NOVA project: maximizing beam time efficiency through synergistic analyses of SRμCT data
Helmholtz-Zentrum Geesthacht GEMS Outstation: Materials Research and High Resolution Imaging, DESY Photon Science Users' Meeting, Hamburg, Germany, January 25, 2018, on invitation by Dr. Christina Krywka.
Biomedisa: The Biomedical Image Segmentation App
Scientific Seminar Series, Imaging Group, IPS, KIT, Karlsruhe, Germany, May 9, 2017, on invitation by Dr. Thomas van de Kamp.
Biomedisa: The Biomedical Image Segmentation App
9. Graduiertenforum der DZG Fachgruppe Morphologie, Karlsruhe, Germany, October 14, 2016, on invitation by Dr. Thomas van de Kamp.

Conference and Seminar Talks

Large-scale analysis of the honey bee brain using micro-CT imaging and deep learning
HeKKSaGOn University Consortium, the 8th German – Japanese University Presidents’ Conference, Tohoku University, Japan, online, September 10, 2021.
Biomedisa: 30 million-year-old fossils come back to life
HeKKSaGOn University Consortium, the 7th German – Japanese University Presidents’ Conference, Heidelberg, Germany, September 12-13, 2019.
Biomedisa: fast and accurate segmentation of fossil insects from synchrotron X-ray microtomography images
13th World Congress in Computational Mechanics, New York City, USA, July 22-27, 2018.
Biomedisa: 30 million-year-old fossils come back to life
HITS Lab Meeting, Heidelberg, Germany, January 8, 2018.
Biomedisa: The Biomedical Image Segmentation App
3rd International Conference on Tomography of Materials and Structures, Lund, Sweden, June 29, 2017.
Biomedisa: The Biomedical Image Segmentation App
HITS Scientific Seminar Series, Heidelberg, Germany, February 13, 2017.
Biomedisa: The Biomedical Image Segmentation App
12. Modellierungstag Rhein-Neckar, HGS MathComp, Heidelberg, Germany, December 8, 2016.
The NOVA Project and the Biomedical Image Segmentation App
DZG Workshop on Engineering tools in morphology, Kiel, Germany, September 13, 2016.

Scientific Posters

HEDI: 3D surface imaging of the unstable anterior abdominal wall before incisional hernia repair
Informatics for Life - Yearly Meeting, Medical Hospital, Heidelberg, Germany, November 19, 2022.
Large-scale analysis of the bee brain using micro-CT imaging and deep learning
Young Researchers @ HITS, Heidelberg Institute for Theoretical Studies, Germany, September 21, 2022.
Biomedisa: The Biomedical Image Segmentation App
110. Jahrestagung der Deutschen Zoologischen Gesellschaft, Bielefeld, Germany, September 13, 2017.
A GPU based diffusion method for whole-heart and great vessel segmentation
19th International Conference on Medical Image Computing and Computer Assisted Intervention, Athens, Greece, October 17, 2016.
Enhancing a diffusion algorithm for 4D image segmentation using local information
SPIE Medical Imaging, San Diego, USA, Februray 27, 2016.