Ewelina Kurtys
Strategic advisor on frontier technologies
Dr. Ewelina Kurtys works at the interface of advanced research and real-world technological deployment, focusing on how emerging scientific breakthroughs can be translated into operational systems. H
With a background spanning neuroscience-driven technologies and advanced R&D ecosystems, she is actively involved in the commercialization and strategic development of frontier technologies. Her expertise includes deep-tech commercialization, technical strategy, innovation assessment, product vulnerability analysis, and the design of implementation pathways that move technologies from experimental validation to real-world use.
At FinalSpark, she contributes to the advancement and adoption of biological computing systems based on living neural networks, helping bridge the gap between laboratory-scale research and global research infrastructure. Her work involves close collaboration with engineers, scientists, and technical decision-makers to evaluate how novel computational paradigms — including wetware-based systems — can be integrated into practical research and development workflows.
She regularly engages with research institutions, industry partners, and innovation teams to explore how emerging technologies can be rigorously assessed, strategically deployed, and scaled responsibly.
Her work reflects a broader commitment to enabling the practical implementation of next-generation technologies that redefine how computation, intelligence, and biological systems interact.
Upcoming conference sessions featuring Ewelina Kurtys
Biocomputers: When Living Neurons Become Hardware
In this session, Ewelina Kurtys introduces a radically different approach to computing: building processors from living neurons.
You’ll see how biological neural networks can function as computing systems, why they could be orders of magnitude more energy efficient than traditional hardware, and how researchers and engineers can begin exploring this emerging field today.
Key Takeaways
- How computers can be built using networks of living neurons
- Why biological computing could dramatically reduce the energy cost of AI
- How researchers and engineers can remotely experiment with this emerging technology
Who Is This For?
Developers curious about the future of computing Engineers interested in AI infrastructure and hardware Anyone fascinated by emerging technologies and research If you enjoy exploring new technological frontiers, this session will give you a glimpse of what might come next.
Level
All levels
No prior knowledge of neuroscience or biology is required.
What This Session Covers
- The concept of biological computing
- How FinalSpark grows and connects living neurons to form computing systems
- Why biological processors could be vastly more energy efficient than silicon
- How the FinalSpark neuroplatform allows remote experimentation with biocomputing
What It’s Not
- Not a programming tutorial
- Not a neuroscience deep dive
- Not a commercial product pitch
Format
Slides Conceptual overview of the technology and research.
Full Description
AI systems are becoming increasingly powerful — and increasingly energy-hungry. As demand for computing continues to grow, researchers are exploring radically different approaches to building computers.
One of the most unusual directions comes from biological computing. Instead of silicon processors, researchers are experimenting with networks of living neurons as computing substrates.
At FinalSpark, scientists are growing neurons in controlled environments and connecting them into biological neural networks capable of performing computational tasks. These living systems could potentially be millions of times more energy efficient than traditional hardware.
In this session, Ewelina Kurtys introduces the emerging field of biocomputing, explains how living neurons can function as computing systems, and shows how researchers and organizations can remotely access the FinalSpark neuroplatform to explore this technology.
The goal is not to replace today’s computers tomorrow, but to explore a radically different path for the future of computing.
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Content featuring Ewelina Kurtys
State of the Art of Biological Computing
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