Heike Leutheuser

Heike Leutheuser

Postdoctoral research fellow

Machine Learning and Data Analytics Lab


Since April 2022, I am head of the Digital Health - Biosignals group of the Machine Learning and Data Analytics Lab, FAU, Germany. In September 2022, I joined the Medical Data Science group, Department of Computer Science, ETH Zurich, as a postdoctoral research fellow. The research stay at ETH Zurich ended in August 2023 and was funded by the PRIME program of the German Academic Exchange Service (DAAD). As a guest researcher at ETH Zurich, I continue my research in diabetes management. From July 2021 to August 2022, I coordinated the CRC 1483 EmpkinS integrated Research Training Group. From August 2017 to March 2022, I worked as the managing science director of the Central Institute of Medical Engineering (ZiMT) of the FAU.

I obtained my Ph.D. at FAU in computer science in 2019, working on wearable computing applications in eHealth. As a doctoral candidate, I did a three-month research visit at Stanford University, USA. The research stay was affiliated with the Mobilize Center and the Department of Orthopaedic Surgery.

Before, I received the Diplom (Dipl.-Phys. Univ.) degree in physics with an emphasis on medicine from FAU.


  • Time series analysis for longitudinal health data
  • Machine learning for wearable health monitoring
  • Biomedical signal processing
  • Event detection algorithms
  • Regression
  • Cross-validation methods
  • Recommendation systems
  • Supervised and unsupervised learning


  • Postdoctoral research fellow, 2022 - 2023

    ETH Zurich, Switzerland

  • PhD in Computer Science, 2019

    Friedrich-Alexander University Erlangen-Nuernberg (FAU), Germany

  • Diplom in Physics (Dipl.-Phys. equivalent MSc.), 2011

    Friedrich-Alexander University Erlangen-Nuernberg (FAU), Germany

  • Visiting Student Researcher, 2016

    Stanford University, US

Recent Publications

Quickly discover relevant content by filtering publications.
(2023). Usability and Perception of a Wearable-Integrated Digital Maternity Record App in Germany: User Study. JMIR Pediatr Parent.

(2023). Evaluating the Effectiveness of Mobile Health in Breast Cancer Care: A Systematic Review. Oncologist.


(2023). Fetal Re-Identification in Multiple Pregnancy Ultrasound Images Using Deep Learning. In Proc: 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

(2023). Prevalence and course of pregnancy symptoms using self-reported pregnancy app symptom tracker data. npj Digit. Med.


(2023). WebPPG: Feasibility and Usability of Self-Performed, Browser-Based Smartphone Photoplethysmography. In Proc: 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).