Hauschild, Anne-Christin, Jun.-Prof. Dr.

Junior Professor for Medical Informatics

2016 Dr. rer. nat, Saarland University, Saarbrücken, Germany
2016 – 2018 Post-Doctoral Researcher Princess Margaret Cancer Centre
2016 – 2018 Post-Doctoral Researcher Krembil Research Institute
2018 – 2019 Visiting Research Fellow Ontario Cancer Research Institute
2018 – 2019 Post-Doctoral Research Fellow Center for Addiction and Mental Health
2019 – 2021 Head of Medical Informatics Division University of Marburg
Since 2021 Junior Professor, Institut of Medical Informatics, University of Göttingen

Major Research Interests

• Integration of machine learning in clinical decision support systems for analysis of clinical, imaging and omics datasets for disease stratification and prediction.
• Longitudinal modelling for disease progression and treatment optimization using multi- omics and medical imaging data.
• Systems medicine algorithms and network analysis approaches for biomarker detection in medicine, drug target identification and a systematic way to uncover molecular mech- anisms and pathways.
• Development of novel privacy preserving learning algorithms to improve medical re- search and foster advances health care applications.

Homepage Department/Research Group
in preparation

Selected Recent Publications

Park Y, Hauschild AC, Heider D (2021) Transfer Learning Compensates Limited Data, Batch-Effects, And Technical Heterogeneity In Single-Cell Sequencing. bioRxiv

Park Y, Heider D, Hauschild AC, (2021) Integrative Analysis of Next-Generation Sequencing for Next-Generation Cancer Research toward Artificial Intelligence. Cancers * ISSUE COVER

Hauschild AC, Eick L, Wienbeck J, Heider D (2021) Fostering Reproducibility, Reusability, and Technology Transfer in Health Informatics. iScience

Spänig S, Mohsen S, Hattab G, Hauschild AC, Heider D (2021) A large-scale comparative study on peptide encodings for biomedical classification. NAR genomics and bioinformatics. 3 (2), lqab039

Marshe V, Maciukiewicz M, Hauschild AC, Islam F, Qin L, Tiwari A, Sibille E, Blumberger D, Karp J, Flint A, Turecki G, Lam R, Milev R, Frey B, Rotzinger S, Foster J, Kennedy S, Kennedy J, Mulsant B, Reynolds C, Lenze E and Mueller D (2021) Genome-wide analysis suggests the importance of vascular processes and neuroinflammation in late-life antidepressant response. Nature Translational Psychiatry