Christopher Gundler, Ph.D.

Christopher Gundler, Ph.D.

I lead the group Applied Artificial Intelligence in Healthcare at the University Medical Center Hamburg‑Eppendorf. We use symbolic and sub-symbolic artifical intelligence to combine health data that is spread across many institutions, and turn it into clinical evidence.

Institute for Applied Medical Informatics, UKE Hamburg

European Health Data Spaceindividual dataabout this patientcohort dataabout many peopleno record linkageone patientintegrate withmachine learningCarehospital recordsPatientswearables, appsCareother patients’ recordsResearchcohort studiesPayersclaims dataRegistriese.g. cancer registriesPublic statisticsregional data: income, environmentEuropean Health Data Spacecohort dataabout many peopleno record linkageone patientintegrate withmachine learningCareother patients’ recordsResearchcohort studiesPayersclaims dataCarehospital recordsPatientswearables, appsRegistriese.g. cancer registriesPublic statisticsregional data: income, environment

Our heterogeneous healthcare system. Inside the ring: individual data about one patient. Outside: cohort data about many people, which cannot be linked to the patient directly. Machine learning (blue) is how the two come together. Select a source for details.

About

Portrait of Christopher Gundler

Since 2022 I have led the Applied AI group at UKE’s Institute for Applied Medical Informatics. We are up to twelve data scientists and students.

Across all the projects, I am interested in sustainably bringing artificial intelligence into practise. This means ensuring that AI solutions are not only effective but also robust, interpretable, aligned with clinical needs, and have a regulatory framework. Accordingly, I am a certified "Person of Regulatory Compliance" accroding to the medical device regulation.

I studied in Osnabrück and Auckland. Before going to academia, I was a software developer and head of Artifical Intelligence at mindQ GmbH & Co. KG, where I worked on interpretable methods for sensor data. I received my PhD from the University of Hamburg in early 2026.

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Research

Unifying a heterogeneous healthcare system.

A disease is more than its symptoms. Understanding it also means looking at causes that are not biological, such as income or environment.

Some of the data for this describes the individual patient, such as hospital records or their own recordings. Much more of it describes cohorts: claims data, registries, cohort studies and regional statistics. These were collected for different purposes and under different rules, and they can rarely be linked to a single patient. My goal is to integrate those kinds with machine learning and turn them into clinical evidence.

Career

My career between start-up scene and academia

Work

  1. 2022–today
    Group lead, Applied Artificial Intelligence in HealthcareUniversity Medical Center Hamburg-Eppendorf
    • Scientific lead of a team of up to twelve data scientists and students
  2. 2022
    Research associateUniversity Medical Center Hamburg-Eppendorf
    • Implementing AI solutions for healthcare applications
  3. 2021–2022
    Head of Artificial IntelligencemindQ GmbH & Co. KG
    • Designed AI methods for new use cases; interpretable, verifiable processing of sensor data
  4. 2018–2021
    Software developerUniversity Medical Center Hamburg-Eppendorf
    • Software solutions for clinical and research customers

Education

  1. 2023–2026
    PhDUniversity of Hamburg
  2. 2018–2021
    Master of ScienceOsnabrück University
  3. 2017
    Semester abroadAuckland University of Technology, New Zealand
  4. 2015–2018
    Bachelor of ScienceOsnabrück University

Publications

My 35 publications. Please find the full record on my ORCID.

202610 publications

  1. Harmonizing regional cancer registry data to facilitate Germany-wide epidemiological analyses

    Germer S, Sauerberg M, Johanns O, Rudolph C, Gundler C, Meisegeier S, …, Kusche H

    International Journal of Medical Informatics

  2. Semantic Retrieval of Projects Funded by the Innovation Committee

    Gundler C, Beernink M, Blaß M, Wiederhold AJ

    Studies in Health Technology and Informatics, book chapter

  3. Symbolar: Hyperdimensional computing from teaching to deployment

    Gundler C

    SoftwareX

  4. From Prototype to Clinical Workflow: Co-Developing a Wearable Hypomimia System for Parkinson’s Disease

    Wiederhold AJ, Haidar L, Pötter-Nerger M, Gundler C

    Sensors

  5. Enhancing stratification for survival analyses across standardized data sources

    Shubov M, Beernink M, Carus J, Wiederhold AJ, Gundler C

    BMC Medical Informatics and Decision Making

  6. Learning Deep Temporal Representations of Socioeconomic Deprivation

    Beernink M, Gundler C

    Studies in Health Technology and Informatics, book chapter

  7. Retrospective Hypomimia Rating via Mobile App: A Usability Study

    Wiederhold AJ, Haidar L, Gundler C

    Studies in Health Technology and Informatics, book chapter

  8. Supporting Risk Assessment Through a Visual, Browser-Based Tool

    Gundler C, Ückert F

    Studies in Health Technology and Informatics, book chapter

  9. Pre-operative three-dimensional face scans for predicting difficult facemask ventilation: a prospective development study

    Wünsch VA, Bommes H, Germer S, Piltan M, Breitfeld P, Latus S, Krause L, Zöllner C, Gundler C, Petzoldt M

    Anaesthesia

  10. Prospective development and validation of an objective classification for difficult facemask ventilation: the MASCAN score

    Wünsch VA, Bommes H, Piltan M, Germer S, Gundler C, Dohrmann T, …, Petzoldt M

    Anaesthesia

202510 publications

  1. Assessing the Generalizability of Foundation Models for the Recognition of Motor Examinations in Parkinson’s Disease

    Gundler C, Wiederhold AJ, Pötter-Nerger M

    Sensors

  2. Leveraging machine-learning techniques to detect recurrences in cancer registry data: A multi-registry validation study using German lung cancer data

    Kusche H, Gundler C, Johanns O, Sauerberg M, Wicker T, Heinrichs V, …, Nennecke A

    European Journal of Cancer

  3. Digitalizing Medical Forms Through Visual Question Answering: Are We There Yet?

    Gundler C, Wiederhold AJ, Pötter-Nerger M

    Studies in Health Technology and Informatics, book chapter

  4. Opportunities and Limitations of Wrist-Worn Devices for Dyskinesia Detection in Parkinson’s Disease

    Wiederhold AJ, Zhu QR, Spiegel S, Dadkhah A, Pötter-Nerger M, Langebrake C, Ückert F, Gundler C

    Sensors

  5. Humane Endpoint Estimation in Laboratory Rodents Using Bayesian Time Series Forecasts

    Blaß M, Grohmann C, Frenzel T, Gundler C

    Studies in Health Technology and Informatics, book chapter

  6. Monitoring Hypomimia in Parkinson’s Disease Using an E-Textile

    Wiederhold AJ, Gundler C

    Studies in Health Technology and Informatics, book chapter

  7. Privacy Protection in Data Synthesis: Effects on Survival Analysis Performance

    Beernink M, Gundler C

    Studies in Health Technology and Informatics, book chapter

  8. Latent spaces of generative models for forensic age estimation

    Chernysheva A, Gundler C, Wiederhold AJ, Well EJV, Heinemann A, Ondruschka B

    Rechtsmedizin

  9. A systematic review of challenges and proposed solutions in modeling multimodal data

    Farhadizadeh M, Weymann M, Blass M, Kraus J, Gundler C, Walter S, Hempen N, Binder H, Binder N

    ArXiv

  10. Improving Interoperability and Generalizability through Technology in Parkinson’s Disease

    Gundler CL, Ückert F

    Book

20246 publications

  1. Unlocking the Potential of Secondary Data for Public Health Research: Retrospective Study With a Novel Clinical Platform

    Gundler C, Gottfried K, Wiederhold AJ, Ataian M, Wurlitzer M, Gewehr JE, Ückert F

    Interactive Journal of Medical Research

  2. Digitalizing Handwritten Digits of Patients with Parkinson’s Disease Utilizing Consumer Hardware and Open-Source Software

    Gundler C, Wiederhold AJ, Pötter-Nerger M

    Studies in Health Technology and Informatics, book chapter

  3. An LLM-Based Visualization and Analysis Aid for a Secondary Use Clinical Data Platform

    Spiegel S, Wendt T, Gundler C, Ückert F, Riemann LT

    Studies in Health Technology and Informatics, book chapter

  4. Continuous, Learned Imputation of Missing Values in Parkinson’s Disease

    Gundler C, Pötter-Nerger M

    Studies in Health Technology and Informatics, book chapter

  5. Learning debiased graph representations from the OMOP common data model for synthetic data generation

    Schulz NA, Carus J, Wiederhold AJ, Johanns O, Peters F, Rath N, Rausch K, Holleczek B, Katalinic A, Gundler C

    BMC medical research methodology

  6. Improving Eye-Tracking Data Quality: A Framework for Reproducible Evaluation of Detection Algorithms

    Gundler C, Temmen M, Gulberti A, Pötter-Nerger M, Ückert F

    Sensors

20237 publications

  1. Patient-individual 3D-printing of drugs within a machine-learning-assisted closed-loop medication management – Design and first results of a feasibility study

    Langebrake C, Gottfried K, Dadkhah A, Eggert J, Gutowski T, Rosch M, …, Gundler C, …, Baehr M

    Clinical eHealth

  2. Introduction of MONOCLE – a software to reduce the workload and optimize the processes of the molecular tumor board at the University Hospital Hamburg-Eppendorf

    Schmitz AK, Lauk K, Heß KA, Voß HP, Fulla O, Schönbeck N, Ückert F, Gundler C, Riemann LT

    GMS German Medical Science — an Interdisciplinary Journal, abstract

  3. A Unified Data Architecture for Assessing Motor Symptoms in Parkinson’s Disease

    Gundler C, Zhu QR, Trübe L, Dadkhah A, Gutowski T, Rosch M, Langebrake C, Nürnberg S, Baehr M, Ückert F

    German Medical Data Sciences 2023 – Science. Close to People, book chapter

  4. Understanding Human-Computer Interactions in Restricted Clinical Environments

    Kraus K, Trübe L, Gundler C

    German Medical Data Sciences 2023 – Science. Close to People, book chapter

  5. Mapping the Oncological Basis Dataset to the Standardized Vocabularies of a Common Data Model: A Feasibility Study

    Carus J, Trübe L, Szczepanski P, Nürnberg S, Hees H, Bartels S, Nennecke A, Ückert F

    Cancers

  6. Development of an immediate release excipient composition for 3D printing via direct powder extrusion in a hospital

    Rosch M, Gutowski T, Baehr M, Eggert J, Gottfried K, Gundler C, Nürnberg S, Langebrake C, Dadkhah A

    International Journal of Pharmaceutics

  7. Semi-Automated Mapping of German Study Data Concepts to an English Common Data Model

    Chechulina A, Carus J, Breitfeld P, Gundler C, Hees H, Twerenbold R, Blankenberg S, Ückert F, Nürnberg S

    Applied Sciences-Basel

20211 publication

  1. Authentic Fear Responses in Virtual Reality: A Mobile EEG Study on Affective, Behavioral and Electrophysiological Correlates of Fear

    Kisker J, Lange L, Flinkenflügel K, Kaup M, Labersweiler N, Tetenborg F, …, Gundler C, …, Schöne B

    Frontiers in Virtual Reality

20171 publication

  1. Visual Analytics of Gaze Data with Standard Multimedia Player

    Schöning J, Gundler C, Heidemann G, König P, Krumnack U

    Journal of Eye Movement Research

List last updated October 2026.

Contact

For collaborations, talks or questions about our work:

christopher@gundler.de