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Bipasha Roy, M.Sc., scientist at IMMS

”Beyond technical challenges, IMMS stands out for its open and collaborative culture. Thanks to my colleagues, working at IMMS is very convenient with high team spirit and active knowledge sharing. At IMMS, I continue to grow — professionally, by exploring cutting-edge AI applications, and personally, through teamwork and shared motivation.“

”I started my journey in IMMS in 2022, and since 2023 as a researcher in the System Design department. I started as a student assistant and continued with my Master’s thesis in the Microelectronics department, where I worked with chip image data to identify different regions on the chip and recreation of the GDSII layout. The work during my thesis not only gave me a deeper understanding of AI application in industrial scenarios but also helped me to gain valuable insights into the structure and creation of microchips. Gaining hands-on professional experience motivated me to continue working in applied research.

As a researcher in the System Design team, my focus is on the application of Artificial Intelligence in industrial environments. I find great fulfillment working in the intersection of academic research and real-world implementation where innovative ideas become practical solutions. Our team collaborates closely with both industrial and scientific partners, this constantly introduces new challenges and encourages creative thinking.

My initial work at IMMS gave me the opportunity to work on signal processing and find AI-based solutions on embedded systems for anomaly detection — supporting machine health estimation and fault diagnosis in running machinery. My research involved analysing different models on vibration data, to predict and localise defects in bearing systems. My focus and work at IMMS continues to expand towards direction on data-driven optimisation for injection molding machines, where I develop AI techniques to enhance process efficiency.

At IMMS I not only develop AI models, I also contribute to work in other industrial applications where intelligent solutions are implemented. This has allowed me to expand my technical skills, while deepen my understanding of how smart systems can transform manufacturing processes.

Beyond technical challenges, IMMS stands out for its open and collaborative culture. Thanks to my colleagues, working at IMMS is very convenient with high team spirit and active knowledge sharing.  At IMMS, I continue to grow — professionally, by exploring cutting-edge AI applications, and personally, through teamwork and shared motivation. I look forward to the journey ahead, filled with new ideas, evolving technologies, and the inspiring people I work with every day.“


Related content

Close-up of a milling machine to which an approximately 2 x 2 cm small wireless circuit board with sensors and an illuminated LED is held.

Project

HoLoDEC

IMMS researches ultra-low-power architectures (ULP) and circuit concepts as well as energy-efficient edge-AI systems with overall system energy modeling

Project

ProQuaOpt

IMMS is developing an AI-based control system for resource-efficient online optimisation of injection moulding


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Lead application

Adaptive edge AI systems for industrial application

We are researching solutions for adaptive edge AI systems to make AI possible on low-consumption embedded systems in industry and to network them in real time.

Service for R&D

Development of embedded systems

We develop embedded systems for you as complete solutions consisting of sensors and actuators, signal processing and communications technology as well as open-loop and closed-loop controls.

Core topic

Embedded AI

The numerous existing AI algorithms and methods for high-performance computing are unsuitable for embedded systems. We are researching to optimise AI algorithms and methods so that they can be used on embedded systems.

Research field

Smart distributed measurement and test systems

Integrated sensor ICs are the heart of sensor and measurement systems like wireless sensors, stationary or handheld devices. We are researching solutions for ever more powerful sensors with more intrinsic intelligence and task allocation in the network.

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