Dr.-Ing. Simon Claus Stock
- Wissenschaftlicher Mitarbeiter
- Gruppe: Prof. Stork
- Raum: 228
CS 30.10 - Tel.: +49 721 608-41316
- simon stock ∂ kit edu
Engesserstr. 5
76131 Karlsruhe
Dr.-Ing. Simon Stock
Lebenslauf
Dr.-Ing. Simon Stock wurde im Mai 1991 in Aalen, Deutschland, geboren. Er begann seine akademische Laufbahn am Karlsruher Institut für Technologie (KIT), wo er sowohl seinen Bachelor- als auch seinen Masterabschluss in Elektro- und Informationstechnik erlangte.
Seine Bachelorarbeit fertigte er interdisziplinär am Institut für Anthropomatik und Robotik (H2T) an der Fakultät für Informatik an. Während seiner Masterarbeit entwickelte er bei der Carl Zeiss Meditec Inc. in Kalifornien innovative Ansätze zur automatisierten Erfassung von 3D-Bildern im menschlichen Auge.
Seit November 2017 ist Dr. Stock als wissenschaftlicher Mitarbeiter am Institut für Informationstechnik (ITIV) tätig. Während seiner Promotion war er Stipendiat der Karlsruhe School of Optics and Photonics (KSOP). 2020 wurde er mit dem Fakultätslehrpreis für die Initiierung und Durchführung des Labors für Angewandte Machine Learning Ansätze (LAMA) ausgezeichnet.
Im Januar 2022 schloss er seine Promotion mit der Arbeit "An Objectivation of Visual Perception using Virtual Reality, Brain-Computer Interfaces and Deep Learning" ab.
Neben seiner Arbeit als Post-Doc und wissenschaftlicher Mitarbeiter ist er im Wissenschaftstransfer tätig. Er ist Mitgründer des Start-ups und Transferprojekts Metis Neurotec (www.MetisNeurotec.com).
Lehre
Betreuung des Labors für angewandte Machine Learning Algorithmen (LAMA)
Forschungsinteressen
- Softwareentwicklung in der Medizintechnik
- Maschinelles Lernen
- Brain-Computer-Interfaces (BCI) und Elektroenzephalographie (EEG)
- Computer Vision
- Ophthalmologie
- Virtuelle und Augmented Reality (VR und AR)
Kollaborationen
Dr. Stock hat mit renommierten Institutionen und Unternehmen zusammengearbeitet, darunter:
- Massachusetts Institute of Technology (MIT), Cambridge, MA, USA
- David J Apple Laboratory - Heidelberg University Hospital, Heidelberg, Deutschland
- Carl Zeiss Meditec, Inc., Dublin, CA, USA
- Apic.ai, Karlsruhe, Deutschland
Weitere Informationen:
Betreute abgeschlossene studentische Arbeiten
- MA: "Simulation Progressiver Augenkrankheiten mittels virtueller Realität"
- MA: "Objekterkennung mittels Transfer Learning durch Convolutional Neural Networks (CNN): Eine Fallstudie zur automatisierten Mahlzeitenerkennung" (Collaborative MA by two Master-students)
- BA: "Design and Prototyping of a Virtual Reality Head Mounted Display with Adaptable Vergence and Accommodation"
- BA: "Instance Segmentation of Objects Close to the User for Improved Perception in Augmented Reality Using Transfer Learning"
- BA: "Gaze Estimation using Convolutional Autoencoders"
- MA: "DeepBees: Using Multi-Task Learning for Joint Detection, Pose Estimation and Classification of Pollen Bearing Bees"
- BA: "Prototyping and Implementation of a Smart Foot Bracelet for Navigation and Guidance Using Haptic Feedback"
- BA: "Integration of pupil tracking in an ophthalmologic virtual reality application for improved immersion and pupil movement analysis"
- BA: "Signal processing in Ophthalmology: How the Retina defines what we are seeing"
- MA: "Highly Parallelized Rendering of the Retinal Image through a Computer Simulated Human Eye"
- BA: "Rapid Prototyping and Evaluation of a Connected Distributed Load Measurement System"
- MA: "Real Time Monitoring System for Laser Marking of Polymeric Materials"
- BA: "Implementierung einer intuitiven Multimediaoberfläche für ein ophthalmologisches VR-Gerät"
- MA: "Examining the Human Neuro-visual System using Electroencephalography: A Deep Learning Approach towards Objective Perimetry"
- MA: "An Electroencephalography based System for Objective Refraction and Visual Acuity Assessment using Convolutional Neural Networks"
- MA: "Ein Ansatz für Maschinelles Lernen in der Produktion: Ein Software-Framework zur Ausführung von künstlichen Neuronalen Netzen in C++"
- MA: "Adaptive Gesture Control for Automotive Applications with Few-Shot-Learning"
- MA: "Correction of choroidal and retinal thickness maps using widefield optical coherence tomography"
- Seminar: "Artifact detection in electroencephalography signals for human brain computer interfaces"
- MA: "A rapid prototyping approach to EEG electrodes for use in machine learning supported brain computer interfaces"
- BA: "Exploring visual stimulation for brain-computer interfaces: A comparison of stimulus designs for ssvep-based applications"
- BA: "Measurement of astigmatism using a SSVEP-based brain-computer-interface"
- BA: "Comparison of convolutional neural network and canonical correlation analysis in ssvep-based brain-computer interfaces"
- BA: "Visual re-identification of bumblebees returning from foraging trips"
- BA: "Closed-loop user-experience in a brain-computer interface for neuro-visual experiments"
- MA: "A cross-platform approach to brain-computer interfaces for monitoring and device control using augmented reality"
- BA: "Development of a low-cost open-source electroencephalograph focused on scientific research"
- MA: "Development of an automatic laser diode lifetime testing setup"
- BA: "Key classification in music recordings using deep convolutional neural networks"
- BA: "Detection and classification of higher cognitive functions with SSVEP using a brain-computer interface"
- BA: "Artifact detection in an EEG-based BCI for the assessment of neuro-visual function"
- BA: "Using brain computer interface for the recognition and classification of various mental states using neural networks"
- MA: "Smart Home Raum-Sensor zur Personenverhaltenserkennung"
- Seminar: "On steady-state visual evoked potential detection in short response time for human brain computer interfaces"
- Seminar: "Quality assessment and noise estimation of EEG data"
- BA: "Development of a firmware for an ophthalmologic VR-device towards the treatment of presbyopia by vergence and accommodation training"
- MA: "Improving user experience and user interface by designing an optimized model for convoaid app"
- MA: "EEG-based objective ADHD diagnosis using convolutional neural networks"
- BA: "Investigating cognitive enhancement through binual beats utilizing brain-computer interfaces"
Titel | Typ | Datum |
---|---|---|
METIS NEUROTEC - Mit KI gegen Demenz | Bachelor-/ Masterarbeit | ab 08 / 2024 |
Publikationen
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Development of dialogue and voice-call robot system for personalized dementia prevention and care
Kumagai, K.; Stock, S.; Miyake, N. P.; Otake-Matsuura, M.; Stork, W.
2024. Gerontechnology, 23 (2), 1 – 5. doi:10.4017/gt.2024.23.s.862.5.sp
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Towards EEG-based objective ADHD diagnosis support using convolutional neural networks
Stock, S.; Hausberg, J.; Armengol-Urpi, A.; Kaufmann, T.; Schinle, M.; Gerdes, M.; Stork, W.
2023. 2023 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), Eindhoven, Netherlands, 29-31 August 2023, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/CIBCB56990.2023.10264876 -
Model-Driven Dementia Prevention and Intervention Platform
Schinle, M.; Dietrich, M.; Stock, S.; Gerdes, M.; Stork, W.
2023. Caring is Sharing. Ed.: M. Hägglund, 937–941, IOS Press. doi:10.3233/SHTI230313 -
End-to-End Deep Learning for Stress Recognition Using Remote Photoplethysmography
Zhou, K.; Schinle, M.; Weimar, S.; Gerdes, M.; Stock, S.; Stork, W.
2023. 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 1435–1442, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/BIBM55620.2022.9995577
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Navigating challenges in digital dementia intervention: A Look at BCI potential
Stock, S.; Schinle, M.
2023, Juni 21. 2nd International Forum on Neural Engineering & Brain Technologies (2023), Berlin, Deutschland, 20.–21. Juni 2023
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An Objectivation of Visual Perception using Virtual Reality, Brain-Computer Interfaces and Deep Learning. Dissertation
Stock, S.
2022, Februar 1. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000142511/v3
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Digital Health Apps in the Context of Dementia: Questionnaire Study to Assess the Likelihood of Use Among Physicians
Schinle, M.; Erler, C.; Kaliciak, M.; Milde, C.; Stock, S.; Gerdes, M.; Stork, W.
2022. JMIR Formative Research, 6 (6), Art.-Nr.: e35961. doi:10.2196/35961
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Development of a self-learning automotive comfort function: an adaptive gesture control with few-shot-learning
Stang, M.; Stock, S.; Müller, S.; Sax, E.; Stork, W.
2022. 2022 International Conference on Connected Vehicle and Expo (ICCVE), 1–8, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICCVE52871.2022.9742989
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METIS - A Holistic Medical Treatment Platform for Dementia Risk Factor Interventions
Stock, S. C.
2022, Dezember 2. Japanese-German-Polish Workshop on AI Applications for Dementia - Machine Learning, Robotics and Health Neuroscience Approaches for Aging Societies (2022), Tokio, Japan, 2. Dezember 2022 -
AI for Health - From University to the Real World
Stock, S.
2022, Oktober 28. 3rd Japanese-German-French AI symposium “AI for Planetary Challenges in the Anthropocene” (2022), Tokio, Japan, 27.–28. Oktober 2022
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Evaluation of Innovative SSVEP Stimulation Patterns for Neuro-Ophthalmology
Stock, S.; Gerdes, M.; Schinle, M.; Veloso de Oliveira, J.; Hauptmann, L.; Martini, L.; Stork, W.
2021. Investigative Ophthalmology & Visual Science, 62 (8), 2391–2391
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A Decision Process Model for De-Identification Methods on the Example of Psychometric Data
Schinle, M.; Erler, C.; Leenstra, S.; Stock, S.; Gerdes, M.; Stork, W.
2021. 2021 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME), 1–6, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICECCME52200.2021.9591139 -
MMAI - Mobile Moods AI; Electroencephalography Artifact Detection; Towards Objective Assessment of Mental States
Stock, S.; Mazura, F.; De La Torre, F. G.; Gerdes, M.; Schinle, M.; Stork, W.
2021. 2021 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME), 01–06, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICECCME52200.2021.9590972
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QUA³CK - A Machine Learning Development Process
Stock, S. C.; Becker, J.; Grimm, D.; Hotfilter, T.; Molinar, G.; Stang, M.; Stork, W.
2020. Proceedings of Artificial Intelligence for Science, Industry and Society — PoS(AISIS2019), 026, Scuola Internazionale Superiore di Studi Avanzati (SISSA). doi:10.22323/1.372.0026 -
Bumblebee Re-Identification Dataset
Tausch, F.; Stock, S.; Fricke, J.; Klein, O.
2020. IEEE Winter Conference on Applications of Computer Vision Workshops, WACVW 2020, Snowmass Village, CO, 1 March 2020 through 5 March 2020. Proceedings, 35–37, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/WACVW50321.2020.9096909 -
Deepbees - Building and scaling convolutional neuronal nets for fast and large-scale visual monitoring of bee hives
Marstaller, J.; Tausch, F.; Stock, S.
2020. 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), 271–278, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICCVW.2019.00036 -
A system approach for closed-loop assessment of neuro-visual function based on convolutional neural network analysis of EEG signals
Stock, S. C.; Armengol-Urpi, A.; Kovács, B.; Maier, H.; Gerdes, M.; Stork, W.; Sarma, S. E.
2020. Online SPIE Photonics Europe, 6-10 April 2020. Neurophotonics. Vol.: 11360, 1136008/ 19 S., Society of Photo-optical Instrumentation Engineers (SPIE). doi:10.1117/12.2554417 -
Highly parallelized rendering of the retinal image through a computer-simulated human eye for the design of virtual reality head-mounted displays
Vu, C. T.; Stock, S. C.; Fan, L. T.; Stork, W.
2020. Online SPIE Photonics Europe, 6 - 10 April 2020 - Optics, Photonics and Digital Technologies for Imaging Applications. Vol.: VI. Ed.: P. Schelkens, 1135316 / 21 S., Society of Photo-optical Instrumentation Engineers (SPIE). doi:10.1117/12.2555872 -
FEEDI - A Smart Wearable Foot-Band for Navigation and Guidance Using Haptic Feedback
Stock, S.; Bertemes, A.; Stang, M.; Böhme, M.; Grimm, D.; Stork, W.
2020. Human Interaction, Emerging Technologies and Future Applications II : Proceedings of the 2nd International Conference on Human Interaction and Emerging Technologies: Future Applications (IHIET – AI 2020), April 23-25, 2020, Lausanne, Switzerland. Ed.: T. Ahram, 349–355, Springer. doi:10.1007/978-3-030-44267-5_52
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Suitability of Virtual Reality for Vision Simulation – A Case Study using Glaucomatous Visual Fields
Stock, S. C.; Erler, C.; Stork, W.; Labuz, G.; Son, H. S.; Khoramnia, R.; Auffarth, G. U.
2019. Investigative ophthalmology & visual science, 60 (9), Abstract 2441 -
Automatic pupil detection using off-axis iris images for alignment guidance in fundus cameras
Dave, P.; Wei, A.; Nolan, D.; Stock, S.; Guo, J.; Covita, A.; Chen, M.; Straub, J.; Durbin, M.; Manivannan, N.
2019. Investigative ophthalmology & visual science, 60 (11), PB040
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DeepBees-Building and Scaling Convolutional Neuronal Nets For Fast and Large-Scale Visual Monitoring of Bee Hives [in press]
Marstaller, J.; Tausch, F.; Stock, S.
2019. ICCV - International Conference on Computer Vision 2019, Oct. 27 - Nov. 2, 2019, Seoul, Korea
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The QUA³CK Machine Learning Development Process and the Laboratory for Applied Machine Learning Approaches (LAMA)
Becker, J.; Grimm, D.; Hotfilter, T.; Meier, C.; Molinar, G.; Stang, M.; Stock, S.; Stork, W.
2019, Oktober 22. Symposium Artificial Intelligence for Science, Industry and Society (AISIS 2019), Mexiko-Stadt, Mexiko, 20. Oktober–25. Dezember 2019
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Suitability of Virtual Reality for Vision Simulation – A Case Study using Glaucomatous Visual Fields
Stock, S. C.; Erler, C.; Stork, W.; Labuz, G.; Son, H. S.; Khoramnia, R.; Auffarth, G. U.
2019. ARVO Annual Meeting (2019), Vancouver, Kanada, 26.–27. April 2019
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Realistic Simulation of Progressive Vision Diseases in Virtual Reality
Stock, S.; Erler, C.; Stork, W.
2018. Proceedings of the 24th ACM Symposium on Virtual Reality Software and Technology, 117:1–117:2, Association for Computing Machinery (ACM). doi:10.1145/3281505.3283395
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Automatic Detection of the Optic Nerve Head in Line Scanning Ophthalmoscope Images in CIRRUS™ HD-OCT
Fard, A.; Bagherinia, H.; Stock, S.; Straub, J.
2017. Investigative ophthalmology & visual science, 58 (8), Abstract 4010 -
The Benefits of Real Time Pupil Tracking on the Quality of the B-Scan
Stock, S.; Kubach, S.; Sha, P.; Straub, J.; Stork, W.
2017. Investigative ophthalmology & visual science, 58 (8), Abstrract 660
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3D Visualization of Retinal Vasculature Using Virtual Reality and 3D Printing
Straub, J.; Jaward, S.; Stock, S.; Leahy, C.; Burns, C.; Sousa, F.
2017. ARVO imaging in the Eye Conference, 2017 Baltimore, May 06, 2017
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The Benefits of Real Time Pupil Tracking on the Quality of the B-Scan
Stock, S.; Kubach, S.; Sha, P.; Straub, J.; Stork, W.
2017. ARVO 2017 in Baltimore, USA -
Automatic Detection of the Optic Nerve Head in Line Scanning Ophthalmoscope Images in CIRRUS™ HD-OCT
Fard, A.; Bagherinia, H.; Stock, S.; Straub, J.
2017. ARVO 2017 in Baltimore, USA -
Algorithm Parameter Optimization with Evolutionary Algorithms
Stock, S.; Kubach, S.; Straub, J.
2017. ARVO imaging in the Eye Conference, 2017 Baltimore, May 06, 2017