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Centre for Artificial Intelligence in Public Health Research

Head:
Katharina Ladewig m.d.W.d.G.b.
Deputy:
Nils Körber, Christopher Irrgang

The "Centre for Artificial Intelligence in Public Health Research" (ZKI-PH) is responsible for the strategic support of advances in the field of public health research using the latest AI-based technologies at the RKI. At ZKI-PH, the topics of bioinformatics, computational epidemiology, modern data visualisation as well as big data and systems analysis are combined with the central methodological building blocks of machine learning, AI, decision making research as well as the development of realistic computer simulations in the field of public health research. To meet these challenges, the ZKI-PH develops models and simulations for the corresponding subject areas, promotes the utilisation/transfer of existing solutions into public health applications and prepares the results and underlying data for the public and political stakeholders. The aim of this interdepartmental cooperation in the field of Artificial Intelligence (AI) is to gain a comprehensive understanding of the spread and prevention of diseases in the population and to counter epidemics of the 21st century even more effectively.

Thumbnail for the video about the Centre for Artificial Intelligence in Public Health Research at the Robert Koch Institute. Source: RKI

Tasks

  • Strategic management of the expansion of AI research at the RKI
  • Developing, monitoring and strategically supporting new advances and their application in the field of public health research using the latest AI-based technologies
  • Steering and coordination of inter- and transdisciplinary research in the field of AI through development, acquisition and implementation of new research and development projects
  • Planning and further development of research cooperations within the RKI and with strategic partners in and outside Germany

The ZKI-PH is structured as follows:

Representation of the RKI in (inter)national panels

  • Working Group Health Care Research (Federal Institute for Drugs and Medical Devices (BfAM))

Projects and networks

Location

The ZKI-PH is based in Wildau near Berlin. In 2021, the Centre for Future Technologies (ZFZ) was built here. The ZKI-PH is located on the third floor of this ultra-modern building complex.

Route to ZKI-PH

Job vacancies at the ZKH-PH

Vacancies at the ZKI-PH are published on the careers website of the RKI and on www.interamt.de.

Further information

Date: 04.04.2024

Publications

  • Hartner AM, Li X, Echeverria-Londono S, Roth J, Abbas K, Auzenbergs M, de Villiers MJ, Ferrari MJ, Fraser K, Fu H, Hallett T, Hinsley W, Jit M, Karachaliou A, Moore SM, Nayagam S, Papadopoulos T, Perkins TA, Portnoy A, Tran MQ, Vynnycky E, Winter AK, Burrows H, Chen C, Clapham HE, Deshpande A, Hauryski S, Huber J, Jean K, Kim C, Kim J-H, Koh J, Lopman BA, Pitzer VE, Tam Y, Lambach P, Sim SY, Woodruff K, Ferguson NM, Trotter CL, Gaythorpe KAM (2024): Estimating the health effects of COVID-19-related immunisation disruptions in 112 countries during 2020–30: a modelling study.
    The Lancet Global Health 12 (4): e563-e571. more

  • Dai X, Yang Z, Xu M, Liu F, Hattab G, Hirche S (2024): Decentralized Event-Triggered Online Learning for Safe Consensus of Multi-Agent Systems with Gaussian Process Regression.
    arXiv:2402.03174 [eess.SY]: https://doi.org/10.48550/arXiv.2402.03174. more

show all

  • Yang Z, Dai X, Dubey A, Hirche S, Hattab G (2024): Whom to Trust? Elective Learning for Distributed Gaussian Process Regression.
    arXiv:2402.03014 [cs.LG]: https://doi.org/10.48550/arXiv.2402.03014. more

  • Yang Z, Songbo Dong, Armin Lederer, Xiaobing Dai, Siyu Chen, Stefan Sosnowski, Hattab G, Hirche S (2024): Cooperative Learning with Gaussian Processes for Euler-Lagrange Systems Tracking Control under Switching Topologies.
    arXiv:2402.03048 [cs.MA]: https://doi.org/10.48550/arXiv.2402.03048. more

  • Ilgen B, Pilic A, Harder T, Hattab G (2023): Pre-Training to Identify Immunization-Related Entities from Systematic Reviews.
    In 2023 7th International Conference on Natural Language Processing and Information Retrieval (NLPIR 2023), December 15-17, 2023, Seoul, Republic of Korea. https://doi.org/10.1145/3639233.3639355. Pages: 234-239. more

  • Kumar SS, Hartner AM, Chandran A, Gaythorpe KAM, Li X (2023): Evaluating effective measles vaccine coverage in the Malaysian population accounting for between-dose correlation and vaccine efficacy.
    BMC Public Health 23 (2351): doi: 10.1186/s12889-023-17082-9. more

  • Anžel A, Heider D, Hattab G (2023): Interactive polar diagrams for model comparison.
    Computer Methods and Programs in Biomedicine 242: 107843. doi: 10.1016/j.cmpb.2023.107843. more

  • Boender S, Schneider PH, Houareau C, Wehrli S, Purnat TD, Ishizumi A, Wilhelm E, Voegeli C, Wieler LH, Leuker C (2023): Establishing Infodemic Management in Germany: A Framework for Social Listening and Integrated Analysis to Report Infodemic Insights at the National Public Health Institute
    JMIR Infodemiology 2023; 3: e43646. doi: 10.2196/43646. more

  • Irrgang C, Tim Eckmanns, von Kleist M, Antão EM, Ladewig K, Wieler LH, Körber N (2023): Anwendungsbereiche von künstlicher Intelligenz im Kontext von One Health mit Fokus auf antimikrobielle Resistenzen.
    Bundesgesundheitsblatt 66: 652-659, doi: 10.1007/s00103-023-03707-2. more

  • Ezekannagha C, Welzel M, Heider D, Hattab G (2023): DNAsmart: Multiple attribute ranking tool for DNA data storage systems.
    Computational and Structural Biotechnology Journal 21: 1448-1460, doi: 10.1016/j.csbj.2023.02.016. more

  • Hattab G, Anžel A, Spänig S, Neumann N, Heider D (2023): A parametric approach for molecular encodings using multilevel atomic neighborhoods applied to peptide classification.
    NAR Genomics and Bioinformatics 5 (1): 10.1093/nargab/lqac103. more

  • Akhmedova S, Stanovov V, Kamiya Y (2022): A Hybrid Clustering Approach Based on Fuzzy Logic and Evolutionary Computation for Anomaly Detection.
    Algorithms 15 (10): 342; doi: 10.3390/a15100342. more