Research
Independent engineering in intelligent systems.
I investigate emerging technologies across robotics, heterogeneous compute, FPGA design, and machine learning. Each research effort is built from first principles, combining rigorous engineering with practical experimentation to understand how intelligent systems behave in real environments.
Historically, our experiments have lived in reStructuredText files for internal use, with an emphasis on reproducibility. The Research section serves a different purpose: to communicate what we've learned, not to provide step-by-step instructions. If you're interested in deeper technical details, feel free to reach out, we're happy to answer questions and, when possible, share the artifacts behind our experiments.
Robotics
Our robotics research focuses on developing control systems that operate reliably under real-world constraints. Work in this area explores sensor fusion, motion planning, and adaptive behaviors that allow robots to respond to dynamic environments with precision and consistency.
Field Programmable Gate Arrays
FPGA research examines how reconfigurable logic can be used to implement efficient compute architectures and specialized processing pipelines. Work in this area explores soft-core processors, custom accelerators, and hardware-level parallelism to evaluate how flexible digital designs can improve performance, reduce latency, and support unconventional computational models.
Coming: Sep 14, 2026
Heterogeneous Compute
Heterogeneous compute research investigates how diverse processing units can be combined to execute workloads more efficiently. Work in this area evaluates performance trade-offs across CPUs, GPUs, iGPUs, NPUs, FPGAs, and specialized accelerators, examining how tasks can be partitioned, scheduled, and optimized to take advantage of each architecture's strengths under real-world constraints.
Machine Learning Models
Machine learning research explores how models can be trained, evaluated, and deployed to solve complex computational and perception tasks. Work in this area examines data representation, optimization strategies, and generalization behavior, focusing on how different model architectures perform under real-world constraints and how learned systems can be adapted for reliable, efficient operation.
Precision Engineering
High-reliability embedded systems, FPGA design, and robotics platforms built with uncompromising attention to detail.
Verified Performance
Benchmarked, stress‑tested, and validated across real‑world robotics and compute workloads.
Robotics & Control
Physical systems, precise motion, and intelligent actuation.