Zaid Yusuf

ML Research
Engineer

Scientific ML · Protein AI · AI Systems

Open to research and applied ML roles

I work on machine learning systems from mathematical foundations through production—especially where scientific modeling, biological data, and reliable engineering meet.

01 / Selected work

Research meets implementation.

01

Protein AI Active exploration

ProtDiffusion

A PyTorch implementation exploring diffusion-based protein structure prediction.

02

Scientific ML In progress

AlphaFold implementation notes

A focused implementation study of the representations and geometric reasoning behind structure prediction.

03

Biological foundation models Open source

scGPT-mini

An implementation study of scGPT for single-cell transcriptomics.

View all work

02 / Technical writing

Notes from the work.

Writing is where I make the machinery explicit: geometry, models, systems, and the decisions hidden inside an implementation.

A working intuition for diffusion on SO(3)

Why rotations make a useful case study for respecting geometry in generative models.

MHA, MQA, and GQA: the cache is part of the architecture

A compact comparison of attention variants through the lens of inference-time memory.

All writing

03 / About

I care about understanding a model well enough to change it with intent.

I’m drawn to problems where assumptions matter: geometric representations, biological structure, inference trade-offs, and the engineering required to make ML systems useful outside a notebook.

More about my approach

04 / Contact

Open to thoughtful conversations and technically difficult work.

yusufteppei11@gmail.com