FOUNDER · HAMILTONIAN RESEARCH · ABU DHABI
Building what
comes after
attention.
01 / THESIS
The transformer is an important architecture. It is not the final one.
Hamiltonian Research studies models that replace quadratic attention and token-by-token generation with state-space dynamics and parallel refinement. The aim is practical: stronger computational scaling, bounded inference state, and more control over the tradeoff between generation time and quality.
02 / CURRENT RESEARCH
DIMBA
Diffusion on a Mamba backbone.
A language model that refines a response in parallel instead of predicting it one token at a time.
DIMBA combines masked diffusion with a bidirectional Mamba-2 backbone. At each step, the model reads the incomplete sequence, predicts the missing tokens, commits the most confident ones, and repeats until the response is complete.
03 / RESEARCH LOG
Work in public,
including the failures.
I trained a language model that thinks the capital of Japan is Paris
The first DIMBA run, what failed, what worked, and what the results imply for the architecture.
READ ↗04 / ABOUT
Faris Allafi
I’m an independent researcher and the founder of Hamiltonian Research, based in Abu Dhabi. My work is focused on efficient sequence models, non-autoregressive generation, and the systems work required to test those ideas properly.
I build the research and implementation together. Current work spans model architecture, training, inference, and low-level performance, primarily in Python, PyTorch, and Rust.
05 / CONTACT
Connections
Research, systems, and difficult problems. Email is the most direct route.
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