Christoph Dinh - Team Lead Physical AI And Computing at ZEISS Group

Christoph Dinh

Team Lead Physical AI And Computing at ZEISS Group

Landau in der Pfalz, Rhineland-Palatinate, Germany

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Summary

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Senior

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Christoph Dinh is a multidisciplinary technology leader with 13 years of experience at the nexus of medical robotics, neurotechnology, and AI, currently heading Physical AI and Computing at ZEISS. He leads teams spanning exploratory research to system-level concept development, shaping future clinical and industrial technology roadmaps with a focus on embodied AI, multimodal sensing, and computation-physical integration. His career blends deep academic training (Dr.-Ing., postdoc work at Harvard Medical School) with hands-on engineering—from real-time neural source localization and MR sequence development to software architecture for AI platforms. An active open-source contributor, he has improved real-time data acquisition and processing in the widely used MNE-Python project, reflecting a sustained interest in bridging neuroscience tooling and production systems. Colleagues know him for translating complex biomedical research into practical, deployable systems and for spotting nascent technology fields before they mainstream.

13 years of coding experience

12 years of employment as a software developer

Dr.-Ing. Biomedical Engineering, Dr.-Ing. Biomedical Engineering at Technische Universität Ilmenau

Postdoc Biomedical Engineering, Postdoc Biomedical Engineering at Harvard Medical School

Biomedical Engineering, Biomedical Engineering at The MGH/HST Martinos Center for Biomedical Imaging - Harvard Medical School

German, English, French

Stackoverflow

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Github Skills (12)

stream-processing10

megaparsec10

real-time-data10

realtime10

python10

data-processing10

el9

data-acquisition9

ceph9

ec9

numpy8

Programming languages (5)

C#TypeScriptC++MATLABPython

Github contributions (5)

mne-tools/mne-python

Nov 2012 - Aug 2014

MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python

Role in this project:

Back-end Developer

Contributions:14 commits in 1 year 9 months

Contributions summary:Christoph's primary contributions involve implementing and modifying core functionalities of the MNE-Python library. The user worked on real-time data processing capabilities within the `mne/fiff/realtime.py` module and related data handling. Key contributions include setting up client aliases, reading measurement information, and reading raw buffer data, demonstrating a focus on data acquisition and processing aspects of the library.

visualizationneuroimagingneurosciencepythonstatistics

chdinh/mne-cpp

Jan 2015 - Dec 2022

Applications for MEG and EEG Data Acquisition, Analysis & Visualization

Contributions:56 PRs, 913 pushes, 43 branches in 8 years

data-acquisitiondata-analysispythonvisual-analyticsanalysis

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