Prof. Dr. Maik Kschischo
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Professor of Biomathematics
Research interests
- Machine Learning
- Statistical Analysis of Complex Data
- Mathematical Modelling
in Medicine and Biologe
Contact
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Prof. Dr. Maik Kschischo
Koblenz University of Applied Sciences
Fachbereich Mathematik und Technik
Biomathematik
Joseph-Rovan-Allee 2
53424 Remagen
++ 49 (0) 2642932330
kschischo@hs-koblenz.de
Prof. Dr. Maik Kschischo
kschisch@hs-koblenz.de
02642 932 330
Publications
Basic Research
We devise Machine Learning methods, analyse data and develope mathematical and statistical models for biological and medical applications.
In particular, we work on methods for
- time series data and learning of differential equation models (model errors, Neural ODEs)
- Data assimilation methods
- data driven control of dynamic systems
- methods for integrating multimodal and high dimensional biomedical data
- Cancer computational biology
Application related Research
Application areas:
- Cancer research (in particular chromosomal instability, drug resistance, tumour heterogeneity)
- Clinical decision support using AI methods
Activities as a Reviewer
Reviewer for reserach proposals at
- BBSRC
- DFG
- BMBF
- EU
Reviewer for several journals including
Cancer Research, Nature, Bioinformatics, PLOS Com-
putational Biology, BMC Bioinformatics, Microarrays,
European Physical Journal (EPJ) E, Bulletin of Math-
ematical Biology, Journal of Statistical Software, Brief-
ings in Bioinformatics, Physics Letters A, Physical Re-
view E, IEEE Transactions on Automatic Control
Received Awards, Prizes, Honors
Lion Bioscience Innovation price (2002)
Special Expertise
Basic Research
- Machine Learning (ML): Self-Supervised Learning, (Semi) Supervised Learning, Artificial Neural Network (ANN), Decision Tree, Bayesian Neural Networks, Model Based, Generative Models, Dimensionality Reduction, Feature Engineering/Feature Extraction
- Knowledge-Based Systems: Causality
- Robotics: Control Algorithms, Simulation Technology
Application related Research
AI Events
- 18.07.2023 - 20.07.2023: SafeAI and Data Governance in Clinical Decision Making
AI Research Projects
- FOR2800: Modelling the link between replication stress, chromosomal instability and aneuploidy
Duration: 03.01.2023 - 08.02.2026, Funding Organization: Deutsche Forschungsgemeinschaft (DFG)
- Data2Health: Data2Health: Trustworhy data analytics for health care,
Duration: 09.01.2022 - 10.03.2023, Funding Organization: Ministerium für Wissenschaft und Gesundheit Rheinland Pfalz - Sepski: Data-driven AI systems for individualized early detection and treatment optimization of sepsis in hospitals
Duration: 01.01.2022 - 01.03.2023, Funding Organization: Ministerium für Wissenschaft und Gesundheit, RlP - GTT: A global trigger tool for sentinel events in hospitals linked to COVID-19 infections
Duration: 03.01.2021 - 10.03.2022, Funding Organization: Ministerium für Wissenschaft und Gesundheit, RlP - SEEDS: Structural errors estimation in dynamic systems
Duration: 03.01.2017 - 01.03.2024, Funding Organization: Deutsche Forschungsgemeinschaft (DFG)