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David Stutz is listed as Research scientist & engineer | 7+ YOE in AI/ML/CV, 12+ in software engineering | Evaluating, building and deploying safe generative AI at Google DeepMind, based in London, England, United Kingdom. AeroLeads shows a work email signal at rwth-aachen.de and a matched LinkedIn profile for David Stutz.
David Stutz previously worked as Senior Research Scientist at Google Deepmind and Research Scientist at Google Deepmind. David Stutz holds Doctor Of Philosophy (Ph.D.), Computer Science from Universität Des Saarlandes.
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I am an experienced research scientist and engineer at Google DeepMind interested in making generative AI useful and safe for everyone to use. Recently, I helped develop SynthID, Med-Gemini and contributed to safety evaluations in Bard (now Gemini).Webpage and blog: https://davidstutz.de/CV as PDF: https://davidstutz.de/cvGitHub: https://github.com/davidstutzGoogle Scholar: https://scholar.google.com/citations?user=TxEy3cwAAAAJ&hl=enTalks on YouTube: https://www.youtube.com/channel/UCfhh-OAwqkGbX_RN87Ht3ow
Listed skills include Bildverarbeitung, C++, Computer Vision, Computer Vision, and 24 others.
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London, London, GB
In short: Awarded 2 spot bonues, 3 peer bonuses, filed 1 patent, helped ship SynthID video, improved Bard/Gemini safety, evaluated Med-Gemini, published three papers, started and led various interdisciplinary, cross-team collaborations.- Drove research into video watermarking, focussing on robustness and decision-making; this has been deployed as part of.
London, London, GB
In short: Awarded 3 spot bonuses, 1 peer bonus, filed 3 patents within 1.5 years of starting, helped ship Google DeepMind's SynthID, published two papers, led a research collaboration with Google Health.Details:- Worked on image provenance and watermarking, with a focus on robust and adversarial evaluation and uncertainty-aware decision making; this has.
Saarbrücken, Saarland, DE
- Led original research on adversarial and corruption robustness, out-of-distribution detection and uncertainty estimation for deep neural networks; this work received the Qualcomm Innovation Fellowship Europe 2019 (40k€).- Established an interdisciplinary collaboration with IBM research on bit error robustness for energy-efficient deep learning.
London, London, GB
- Reviewed literature on conformal prediction and distribution-free uncertainty estimation and compiled as well as presented a technical survey for the team.- Developed and implemented a novel training method for conformal prediction called conformal training alongside baselines; 20k+ lines of reviewed code.- Contributed to understanding adversarial.
Stuttgart, Baden-Württemberg, DE
- Developed a novel learning-based algorithm for weakly-supervised 3D reconstruction of objects.- Implemented method alongside various learning-based and optimization-based baselines to conduct extenstive experiments; needed to implement several custom 3D deep learning layers in Torch and TensorFlow and develop appropriate visualization and evaluation.
Redmond, Washington, US
- Implemented a new feature for centralized deployment of office add-ins for organizations together with two other interns.- Responsible for backend and database access, obtaining and integrating data from various database systems within Microsoft.- Took part in Microsoft's ``One Week'' hackathon working on machine learning for understanding EEG brain.
Eschborn, Hessen, DE
- Conducted an extensive literature review on deep learning for object/pedestrian detection and tracking for advanced driver assistance systems and presentation to the team.- Implemented a benchmark for different deep learning architectures for pedestrian detection based on Caffe.- Integrated and evaluated on multiple public datasets as well as MOBIS'.
San Francisco, California, US
- Conducted an extensive literature review on deep learning for object/pedestrian detection and tracking for advanced driver assistance systems and presentation to the team.- Implemented a benchmark for different deep learning architectures for pedestrian detection based on Caffe.- Integrated and evaluated on multiple public datasets as well as MOBIS'.
Aachen, North Rhine-Westphalia, DE
- Conducted research on superpixel segmentation of images, resulting in the most comprehensive benchmark of superpixel algorithms at that time \cite{cviu2018}.- Re-implemented various superpixel algorithms in C++, optimizing runtime and extending them to utilize 3D information, i.e., RGB-D images.- Developed novel superpixel semgnetation metrics and.
- Developed and established an employee scheduling web applications with features including time tracking, billing, customer management as well as calendar functionalities.- Worked directly with customers to manage requirements and estimate costs for adapting the software to their needs; sold it to five companies with up to 30 eomployees.- Implemented.
Aachen, North Rhine-Westphalia, DE
- Gave weekly tutorials to groups of 30-50 students, presenting sample solutions for exercises and answering questions.- Graded final exams as well as weekly homework and gave feedback when students viewed their exam papers.- Helped with writing lecture notes and completed various trainings for teaching at university level.
Wachtberg, DE
- Wrote a visualization library based on d3.js/JavaScript to visualize web analytics data.-
Wachtberg, DE
- Implemented a Piwik plugin in PHP/SQL/JavaScript to import and export web analytics data.-
Wachtberg, DE
- Developed a web application using Kohana/PHP/JavaScript to create and manage complex SQL queries for web analytics data.-
Wachtberg, DE
- In an internship during high school, I developed 3D models for various applications using Blender and X3D and learned C++.-
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David Stutz works for Google DeepMind.
David Stutz is listed as Research scientist & engineer | 7+ YOE in AI/ML/CV, 12+ in software engineering | Evaluating, building and deploying safe generative AI at Google DeepMind.
AeroLeads has found 1 work email signal at @rwth-aachen.de for David Stutz at Google DeepMind.
David Stutz is based in London, England, United Kingdom while working with Google DeepMind.
David Stutz has worked for Google Deepmind, Max Planck Institute For Informatics, Deepmind, Max Planck Institute For Intelligent Systems, and Microsoft.
You can use AeroLeads to view verified contact signals for David Stutz at Google DeepMind, including work email, phone, and LinkedIn data when available.
David Stutz holds Doctor Of Philosophy (Ph.D.), Computer Science from Universität Des Saarlandes.
David Stutz is listed with skills including Bildverarbeitung, C++, Computer Vision, Computer Vision, Matlab, Machine Learning, Datamining, and Javascript.
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