Mathematical Foundations · Est. 2025
Foundations for signals and intelligence
We work on the structure inside the data, not on top of it. Two areas, one mathematical foundation.
"Sparsity isn't just a property of data. It's a design principle for intelligence."
The SparseTech Research Team
What We Do
Two areas, one foundation
Most real-world signals contain a lot of structure under the noise. We apply that idea in two places: the radio frequencies that carry information, and the neural networks that interpret it.
Deterministic signal processing
Efficient algorithms for next-generation wireless infrastructure such as 6G beamforming, massive MIMO, real-time spectrum analysis, and industrial sensing, with reproducible behavior we can test and verify.
- 6G beamforming & massive MIMO
- Real-time spectrum analysis
- Industrial sensing & biosignals
Principled AI frameworks
Frameworks for building intelligent systems on mathematical foundations: edge LLM deployment, principled compression, compositional reasoning, and deterministic inference.
- Edge LLM & on-device inference
- Principled model compression
- Compositional reasoning
Shared foundation
The same
mathematics
in both areas.
In signals
Most frequency bins are noise. Sparse methods identify and process only the components that carry information.
In models
Most parameters are redundant. Sparse methods discover and preserve the weights that matter.
Same math
Compressed sensing, sparse linear algebra, and deterministic optimization underlie both.
Selected Research
Published work
Our team's publications are listed on the Research page alongside curated foundational readings from arXiv.
Visit ResearchFrom the Blog
Recent writing
Technical Insights
AI Models Don't Need to Be Smaller. They Need to Be Selective
Scaling adds capacity. It doesn't guarantee structure. What we found when we started carving.
Technical Insights
Why Learning From One Model Is Like Studying With One Teacher
Why learning from a single source creates limits, and why combining perspectives produces smarter, more reliable systems.
Technical Insights
Why Prompting Feels Like Guesswork
The real problem isn't how you ask. It's how the model listens.
Get in touch
Research collaborations, licensing inquiries, or just to say hello.