Skip to main content
Our research experts

Damir Shakirov, Dipl.-Ing.

Senior Data Scientist and Business Consultant

Progress is called progress because it is supposed to improve our lives.

Damir Shakirov in dark red shirt smiling at the camera.

When I started working at the Bosch Center for Artificial Intelligence in 2018, AI and manufacturing weren’t things people usually put under the same umbrella. Now, almost 7 years later, things could not be more different, and I am proud to have played a role in this success story. I began my professional career at Bosch as a student in 2013 with a clear objective: to reduce the scrap rate through a better understanding and hence control of manufacturing processes. This objective remained the same while the technologies we used changed during the years. As a senior data scientist, I have had the opportunity to witness and contribute to the impact of AI-technologies. The latest emerging trend of generative AI-technologies has opened a vast range of possibilities and brings us even closer to our objective. More specifically, we aim to create a virtual expert whose knowledge closely matches that of our real experts.

Please tell us what fascinates you most about research.
Research always starts with an idea and believe that it actually could work. When I see my idea develop first into a working prototype and eventually into an application, that is an incredible feeling. Here at Bosch Research, I get the opportunity to work on those ideas. Given that we as a company are present in so many different domains, almost any idea is one that can potentially change the world.

What makes research at Bosch so special?
This transition from idea, to prototype, to an application in a real product, which I can experience in my daily life and tell friends and family about, is very unique. As a global company, we also have a global partner structure. I collaborate with colleagues from Pittsburgh and academical researchers from Carnegie Mellon University in my ongoing project.

What research topics are you currently working on at Bosch?
Currently we are working on the application of Generative AI models in manufacturing. Our vision is to be able to use those models just the way we use large language models like ChatGPT today. Our manufacturing experts will be able to use them for configuring manufacturing lines or querying for unexpected behavior such as the sudden occurrence of scrapped products.

What are the biggest scientific challenges in your field of research?
Today’s biggest challenge with generative AI algorithms lies in the generation of trustworthy and reliable results. The models that exist today excel at producing results, but those results must be verified before using them. It is easy to identify if something is physically impossible and exclude those suggestions from the possibility space. It is much harder to identify all undesirable consequences of those suggestions within a given context.

How do the results of your research become part of solutions “Invented for life”?
Our ultimate goal is to reduce scrap rates to zero. We want to minimize the environmental and hence economical footprint of our operations. Not wasting valuable resources helps to save more than just carbon dioxide emissions.

Curriculum vitae

2024
Senior Data Scientist and Business Consultant for Applied AI in manufacturing at Bosch Research

2021 – 2023
Project Manager for AI Supported Accelerated OEM Release of Dresden Plant

2021
Moderator of the AI DAY 2021

2018 – 2021
AI-Consultant for AI in manufacturing at Bosch Center for Artificial Intelligence

2014 – 2017
Research Engineer with focus on computational engineering

2007 – 2014
Studies of Mechanical Engineering at Karlsruhe Institute for Technology in Germany

Damir Shakirov stands with his arms crossed in front of a pond.

Selected publications

Icon book

Juerges & Shakirov (2024)

Method and Apparatus for Reconstructing the Position of Cells in a Three-Dimensional Tissue
  • Shakirov Damir, Juerges Christopher
  • DE102022212416A1; US2024170095A1
Icon book

Shakirov & Pfrommer (2023)

Method for comparing at least two production lines
  • Pfrommer Timo, Shakirov Damir, Iakovlev Anton, Levin Jonathan, Bansal Mehul, Werner Matthias
  • DE102022200737A1
Icon book

Steimer et al. (2021)

Method for dynamically setting regulator boundary values for welding controller and welding controller
  • Steimer Andreas, Zhou Baifan, Shakirov Damir, Bleier Fabian, Haeufgloeckner Juergen, McConnell Sean, Slavnic Sinisa, Pychynski Tim
  • CN113492253A; DE102020204521A1; DE102020204521B4; EP3892412A1; EP3892412B1; ES2940253T3
Icon book

McConnell et al. (2021)

Method for optimizing welding parameters of welding controller, method for providing trained machine learning algorithm, and welding controller
  • Haeufgloeckner Juergen, Steimer Andreas, Zhou Baifan, Shakirov Damir, Bleier Babian, Dieterle Martin, McConnell Sean, Slavnic Sinisa, Pychynski Tim
  • CN113492254A; DE102020204522A1; EP3915712A1; EP3915712B1

Get in touch with me

Damir Shakirov, Dipl.-Ing.
Senior Data Scientist and Business Consultant

Share this on: