About
- since 2020: Coordination of Life Science & Medicine projects in Transfer & Service at ScaDS.AI [1]
- since 2019: Research Associate at ScaDS.AI [2] (Center for Scalable Data Analytics and Artificial Intelligence) Dresden/Leipzig
- 2008 - 2019: Software Developer and Research Associate at Loeser/Meierhofer Medizintechnik GmbH
- 2003 - 2008: Research Associate at Biodata Mining Group, University of Bielefeld
- Graduation: Dr.-Ing., University of Bielefeld, 2009
- Diploma in Computer Science, University of Bielefeld, 2003
Contact
- +49 341 97 39306
- christian.martin [at] informatik.uni-leipzig.de
- ScaDS.AI [3] (Center for Scalable Data Analytics and Artificial Intelligence) Dresden/Leipzig
- Humboldtstrasse 25, 3.OG
- 04105 Leipzig
Research Interests
- Machine Learning
- Statistical Learning
- Life Science & Medicine
- Personalized Medicine
- Biomedical Data Analysis
- Deep Learning
- Image Processing
- Radiomics
Projects
- GRAMMY (ERA PerMed): InteGRAtive analysis of tuMor, Microenvironment, immunitY and patient expectation for personalized response prediction in Gastric Cancer
- MIRACLE (ERA PerMed): A Machine learning approach to Identify patients with Resected non-small-cell lung cAnCer with high risk of reLapsE
- SaxoCell [4]
- SaxoCell Omics [5]
- SaxoCell Systems [6]
- Radiomics
- Classification of cancer types
- Rupture risk prediction of aneurysms
- Image Prediction
Tools
- Predict rupture risk of intracranial aneurysm: Webtool [7]
Talks
- Personalized Medicine and Cancer Research at ScaDS.AI. Innovationsworkshop Künstliche Intelligenz in der Krebsforschung und -behandlung, 2022-07
Supervision of Thesis/Students
- Running Thesis
- Marlene Mertens (MA): Klassifikation von Cervix-Karzinomen in MRT-Bildern
- Mohammad Issa (MA): Automatische Detektion und Segmentierung von Fahrspuren im Automotive Bereich (Kooperation mit ASAP ENGINEERING GmbH)
- Jonathan Huthmann (MA): Vorhersage der Kontrastmittelanreicherung in 3D-Mamma MRT-Aufnahmen durch Einsatz von Deep Learning
- Finished Thesis
- 2022, Lucas Lange (MA): Privacy-Preserving Detection of COVID-19 in X-Ray Images (joint supervision with Maja Schneider)
- 2021, Stefan Berger (MA): Feature Selection Methods to Predict Wafer Thickness in Chip Manufacturing (cooperation with Global Foundries)
- 2021, Georg Walther (BA): Automatische Aneurysma-Detektion und Rupturvorhersage
- Students (WHK)
- 2020-2022, Marlene Mertens: Klassifikation on Tumor-Subtypen und Survival Analysis bei Magenkrebs (Projekt GRAMMY)
- 2020-2022, Georg Walther: Machine Learning for Rupture Risk Prediction of Intracranial Aneurysms
- 2021, Leo Seeger: Segmentierung von Mamma-MRT-Bildern mit Unsupervised Deep Learning
- 2021, Emre Arkan: Erprobung von Treatment Response Assessment Maps (TRAMs) auf MRT-Bildern von Hirntumoren
- 2020, Jan Beckert und Emre Arkan: Entwicklung eines Covid-19-Demonstrators zur Klassifikation von Röntgenbildern
- Besondere Lernleistung (BeLL)
- 2021/2022, John Petersen: Klassifizierung von Magnetresonanztomographie-Bildern mit konvolutionalen neuronalen Netzen [pdf] [8]
Publications
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