Flagship Projects

Four projects, with code and open questions

GPU inference, robotics, EEG and energy optimization: explore the implementations, available evidence and next validation steps.

Hardware/GPU × LLM

FlashKernel

CUDA and Triton kernels for attention, activation fusion and cache operations. Explore the implementation, correctness boundaries and GPU validation requirements.

CUDA C++ Triton Nsight Compute PyTorch
LLM × Robotics × GPU

RoboLLM

A MuJoCo prototype tested on fixed-goal reaching and one-second holds, with collision checks, complete traces and reproducible controller comparisons.

MuJoCo Scripted control SAC PyTorch
BCI × LLM × GPU

NeuroLLM

An EEG transformer prototype for masked reconstruction and motor-imagery classification, with data separation and evaluation as the current priorities.

PyTorch NumPy/SciPy Transformers EEG
Quantum AI × Energy

QuantumGrid

Synthetic unit-commitment experiments using QUBO, QAOA, VQE and classical solvers. Explore the formulation and requirements for a fair comparison.

PennyLane QAOA/VQE OR-Tools QUBO