Klaus Telkmann

Beruflicher Werdegang

Seit 2020
Wissenschaftlicher Mitarbeiter, Institut für Public Health und Pflegeforschung, Universität Bremen

2018 bis 2019
Postdoctoral Researcher, Department of Statistics, University of California Irvine, USA

Akademischer Werdegang

2012 bis 2018
Promotion Statistik, Universität Konstanz

2006 bis 2012
Diplom Mathematik, Universität Bremen

Projekte

Equal-Life: Die Bedeutung der Lebensumwelt von Kindern für deren Entwicklung und psychische Gesundheit
Forschungsteam: Prof. Dr. Gabriele Bolte (Projektleitung); Jenny Ahrens; Dr. Stefanie Dreger; Dr. Helene Gudi-Mindermann; Dr. rer. pol.  Dipl.-Ing. Natalie Riedel; Jana Roczen; Maddie White

INGER – Integration von Geschlecht in die Forschung zu umweltbezogener Gesundheit: Aufbau einer fundierten Evidenzbasis für geschlechtersensible Prävention und umweltbezogenen Gesundheitsschutz
Forschungsteam: Prof. Dr. Gabriele Bolte (Projektleitung); Dr. Lisa Dandolo; Christina Hartig

WHO-CC

Publikationen

Zeitschriftenbeiträge referiert

Dandolo L, Telkmann K, Hartig C, Horstmann S, Pedron S, Schwettmann L, Selsam P, Schneider A, Bolte G, on behalf of the INGER Study Group. Do multiple sex/gender-dimensions play a role in the association of green space and self-rated health? Model-based recursive partitioning results from the KORA INGER study. Int J Environ Res Public Health 2023, 20(7): 5241, doi:10.3390/ijerph20075241

Mena E, Stahlmann K, Telkmann K, Bolte G. Intersectionality-informed sex/gender-sensitivity in Public Health Monitoring and Reporting (PHMR): A case study assessing stratification on an “Intersectional Gender-Score”. Int J Environ Res Public Health 2023, 20, 2220, doi:10.3390/ijerph20032220

Dandolo L, Hartig C, Telkmann K, Horstmann S, Schwettmann  L, Selsam  P, Schneider A, Bolte G, on behalf of the INGER Study Group. Decision tree analyses to explore the relevance of multiple sex/gender dimensions for the exposure to green spaces: results from the KORA INGER study. Int J Environ Res Public Health 2022, 19(12): 7476, doi:10.3390/ijerph19127476, 18.06.2022

Shrestha R, Telkmann K, Schüz B, Koju P, Shrestha R, Karmacharya A, Bolte G. Measuring environmental justice in real time: A pilot study using digital participatory method in the Global South-Nepal. International Journal of Environmental Research and Public Health 2022, 19 (8), 4752, doi:10.3390/ijerph19084752, 14.04.2022

Czwikla G, Boen F, Cook D, de Jong J, Harris T, Hilz L, Iliffe S, Lechner L, Morris R, Müllmann S, Peels D, Pischke C, Schüz B, Stevens M, Telkmann K, van Lenthe F, Vanderlinden J, Bolte G. Equity-specific effects of interventions to promote physical activity among middle-aged and older adults: results from applying a novel equity-specific re-analysis strategy. International Journal of Behavioral Nutrition and Physical Activity 2021, 18 (65), 17.05.2021, Link (Stand: 18.05.2021)

Beran J, Telkmann K. On inference for modes under long memory. Scandinavian Journal of Statistics 2021, 48(2), 429-455, doi:10.1111/sjos.12476, Link

Beran J, Sabzikar F, Surgailis D, Telkmann K. On the empirical process of tempered moving averages. Statistics & Probability Letters 2020, 167, 108902, doi:10.1016/j.spl.2020.108902

Beran J, Telkmann K. On nonparametric ridge estimation for multivariate long-memory processes. Lithuanian Mathematical Journal 2020, 60(3), 291-314, doi:10.1007/s10986-020-09480-y, Link

Zhu J, Hancock A M, Qi L, Telkmann K, Shahbaba B, Chen Z, Frostig R D. Spatiotemporal dynamics of pial collateral blood flow following permanent middle cerebral artery occlusion in a rat model of sensory-based protection: a Doppler optical coherence tomography study. Neurophotonics 2019, 6(4), doi:10.1117/1.NPh.6.4.045012

Beran J, Telkmann K. On nonparametric density estimation for multivariate linear long-memory processes. Communications in Statistics - Theory and Methods 2018, 47(22), 5460-5473, doi:10.1080/03610926.2017.1395048

Beran J, Liu H, Telkmann K. On two sample inference for eigenspaces in functional data analysis with dependent errors. Journal of Statistical Planning and Inference 2016, 174, 20-37, doi:10.1016/j.jspi.2016.02.001

Vorträge / Poster

Telkmann K, Gudi-Mindermann H, Bogers R, Ahrens J, Tönnies J, van Kamp I, Vrijkotte T, Bolte G. Identification of exposome clusters relevant for children’s mental health: Results of the ABCD cohort study. Gemeinsame Jahrestagung der GMDS, DGSMP, DGEPI, DGMS und DGPH, Dresden, 11.09.2024

Telkmann K, Dandolo L, Hartig C, Horstmann S, Schneider A, Bolte G. Model-based recursive partitioning to integrate sex/gender into environmental health research, 17. Jahrestagung der Deutschen Gesellschaft für Epidemiologie, Greifswald, Deutschland, 26.09.2022

Dandolo L, Telkmann K, für die INGER-Studiengruppe. Statistische Analysenmethoden bei komplexen Daten zu Geschlechterdimensionen, Online-Konferenz des Projektes INGER – Integration von Geschlecht in die Forschung zu umweltbezogener Gesundheit, Bremen, Deutschland, 29.11.2021

Shrestha R, Telkmann K, Bolte G, Shrestha R, Koju P, Karmacharya B. Digital Participatory Method for Environmental Justice Research: Lessons Learned from Adapting and Piloting DASEIN concept in the context of the Global South-Nepal, Extended Abstract and Presentation at: 11th International Summer School and Conference “Applied Geoinformatics for Society and Environment”. Nov 24-26, 2021, Dhulikhel (online), Nepal

Telkmann K, für die INGER-Studiengruppe. Bedeutung von Grünflächen für die subjektive Gesundheit: Einfluss von Geschlecht. Analyse der KORA-Daten, Online-Konferenz des Projektes INGER – Integration von Geschlecht in die Forschung zu umweltbezogener Gesundheit, Bremen, Deutschland, 29.11.2021

Telkmann K, Dandolo L. Recursive partitioning for effect heterogeneity in dose-response relationships, 63rd ISI World Statistics Congress, online, Den Haag, Niederlande, 15.07.2021

Telkmann K, 2019: Two sample testing for multivariate functional data, Joint Statistical Meetings, Denver, CO, 30.07.2019

Telkmann K, 2019: Multivariate functional data analysis for local field potentials, Statistical Methods in Imaging, Irvine, CA, 02.06.2019

Telkmann K, 2018: Nonparametric ridge estimation for multivariate linear long-memory processes, Stochastic Processes and their Applications, Göteborg, Schweden, 13.06.2018

Telkmann K, 2017: On multivariate kernel density estimation under long memory, European Meeting of Statisticians, Helsinki, Finnland, 24.07.2017

Telkmann K, 2016: On estimating open and closed line segments in noisy data, Joint Statistical Meetings, Chicago, IL, 02.08.2016