Case summary
At a glance
How can fresh academic perspectives drive real-world innovation? Through the TUM 1000+ program, Sciospec collaborated with a dynamic team of TU Munich students—Mohammad Omer, Monika Gupta, and Guillem Alvarez Bernal—to explore AI-driven optimizations in signal processing, test automation, and development workflows. Their insights not only helped refine key processes but also reinforced Sciospec’s commitment to advancing high-precision impedance-based technologies. Read about our key takeaways and how industry-academia collaboration fuels the next generation of innovation.
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PhD project sets out to deliver cutting edge innovation through close collaboration
Leipzig, February 1st 2025
We are excited to announce that Vincent Weiß started his industry PhD project at Sciospec Scientific Instruments on February 1st, in close collaboration with HTWK Leipzig! 🎉
His PhD research is supervised by Prof. Dr.-Ing. Gerold Bausch and his Electronic Engineering Lab (EEL) at HTWK Leipzig and Sebastian Wegner (Sciospec) with Prof. Dr. Olfa Kanoun (TU Chemnitz) supporting as an academic reviewer.
This project builds upon our successful CardioEPIX initiative, which we have been developing together with Uniklinik Dresden and University of Leipzig. With this platform, we have already achieved a major breakthrough—capturing high-resolution electrical signatures of cardiomyocytes, enabling precisely differentiated diagnostic data—a true innovation for cardiological research and diagnostics!
What makes CardioEPIX special?
The system is based on massively multi-channel electrical impedance spectroscopy (EIS) and enables:
✅ surpass conventional cardiac safety by adding sensitivity and specificity
✅ precisely differentiated identify subtypes of cardiovascular diseases
✅ enables first time ever early stage precision diagnostics
✅ open new possibilities for targetted drug development
What’s Next? Pushing toward clinical adaptation.
🔹 Developing real-time capable algorithms for high-channel signal analysis
🔹 Applying machine learning for pattern recognition & classification
🔹 Optimizing FPGA-based signal processing for maximum efficiency
🔗 Learn more about CardioEPIX here: www.sciospec.com/portfolio/cardioepix
#Sciospec #PhDResearch #HTWKLeipzig #EEL #Cardiology #MedicalTechnology #FPGA #AI #CardioEPIX #UniklinikDresden #UniLeipzig #TUChemnitz #Innovation
Let’s discuss opportunities for collaboration. Contact us!
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