Jen Wei
Jen Wei is an independent AI research engineer with a PhD in applied mathematics and a love for building things from scratch — especially when she probably shouldn’t. She’s reverse-engineered transformer architectures, implemented modern techniques like mixture-of-experts and Multi-head latent attention, and still enjoys writing clean PyTorch code at 2am for fun (and maybe for revenge). Jen currently works in the GenAI space and shares her work openly on Hugging Face. Her favorite research topics include efficient LLM architecture, post-training techniques, and the existential crises of overparameterized models.
Session
Want to understand how transformers actually work without wading through 10,000 lines of framework code or drowning in tensor shapes? This talk walks you through building a transformer model from scratch — no pre-trained shortcuts, no black-box abstractions — just clean PyTorch code and good old-fashioned curiosity. You'll walk away with a clearer mental model of how attention, encoders, decoders, and masking really work.