news category icon

neurocat wins 1st place award at TechAD 2022

Post Date: 29. April 2022

Neurocat won 1st place in Software and Compute Category at the 2022 edition of the Tech.AD EUROPE AWARD. The Tech.AD Europe Award exclusively honours extraordinary projects in the automotive industry and celebrates exceptional solutions & innovations.

“The winners have set a new standard for innovation and creative technology within the autonomous driving industry,” said Sarah Farley, Director of the Tech.AD Europe 2022. “This award is a testament to the skill, ingenuity, and vision of the creators. Being able to present the future in real time is an absolute privilege.”

Among all applications, the best 9 projects were nominated by an international jury of experts:

  • Dr. Helge Neuner, Head of Self Driving System Development, Volkswagen
  • Dr. Jürgen Dickmann, Head of Radar and Radar-based environment understanding, Daimler
  • Dr. Andree Hohm, Head of Lighthouse Program Automated Driving, Continental
  • Dr. Wende Zhang, Technical Fellow/ Sensing Systems, General Motors

You may also find this interesting

neurocat CEO Florens Greßner in IHK Berlin Magazine

neurocat CEO Florens Greßner in IHK Berlin Magazine

Feb 14, 2022

Our CEO Florens Greßner featured in IHK Berlin magazine’s February 2022 edition talking about his inspiration for #neurocat, love for abstract #mathematics and advice for #young #entrepreneurs 📰 Check out the magazine below (#35, only in German) 👇🏻...

neurocat Honoured With Vision Award 2021

neurocat Honoured With Vision Award 2021

Nov 23, 2021

Neurocat was awarded with the VisionAward 2021 at MedienTage Munich. VisionAwards have been given to young and established companies and entrepreneurs who set new trends with a new business idea. The jury for the award consisted of interdisciplinary experts and...

dSPACE Acquires Interests in Berlin Start-Up neurocat

dSPACE Acquires Interests in Berlin Start-Up neurocat

Nov 3, 2021

dSPACE, an internationally leading provider of simulation and validation solutions for the development of networked, self-driving, and electric vehicles, has acquired interests in neurocat. Support from a renowned industry leader will give us the necessary support in...

Wasserstein Verification Paper Published

Wasserstein Verification Paper Published

Oct 15, 2021

We are proud to present our joint work with the University of Göttingen. Formal verification of neural networks is a challenging topic! In the past, verification methods were mainly focused on Lp-norms for measuring imperceptibility. Using Lp-norms for measuring the...

Neurocat accepted onto NVIDIA AI Inception program

Neurocat accepted onto NVIDIA AI Inception program

Nov 16, 2020

Neurocat has been accepted into the NVIDIA AI Inception program! Being recognized by one of the giants in AI space showcases the potential of our software offering aidkit and neurocat's work in the domain of AI robustness, explainability and functionality. Want to try...

Papercat Thursday 12/11/2020

Papercat Thursday 12/11/2020

Nov 12, 2020

Proud to present the research paper contributed by colleagues at neurocat GmbH & Volkswagen AG. Risk Assessment for ML models is of paramount importance to understand the failure modes and improve the models before deployment. Our paper defines the standardized...

1E9 Interview Tarek R. Besold

1E9 Interview Tarek R. Besold

Nov 11, 2020

Making AI models robust against adversarial attacks, unboxing the black-box models to make their decision-making process more explainable, and also working with standardization agencies to bring quality in AI to the forefront. It's all in a day's work for us. Read the...

Most Promising German AI Startups

Most Promising German AI Startups

Mar 4, 2020

Neurocat was voted one of the 247 most promising German AI startups by the initiative for applied artificial intelligence. We are pleased to be part of the AI Startup Landscape 2020 and working hard to shape the future of AI quality. The Startup Landscape and a...

Decision Boundary

Decision Boundary

Feb 6, 2020

State-of-the-art neural networks are vulnerable to adversarial examples. This major problem for the safe deployment of ML models arises when minor input modifications push a data point across the decision boundary of the model. The existence of adversarial examples is...

5
4

Start Your Own Newsworthy Project!