Zach Rodiere

Machine Learning Engineer, Georgia Tech MS ECE

I'm currently building BehavLabs, a startup focused on continuous authentication and behavioral understanding: inferring mood and intent from human-computer behavioral signals.

My ML background is in neural time-series modeling. My thesis work focused on seizure onset zone localization from intracranial EEG (SEEG), using transformer architectures, contrastive representation learning, and cross-patient generalization.

I grew up in a small town in France, trained as an electrical and computer engineer, and completed my M.S. in Electrical and Computer Engineering at Georgia Tech.

Selected Work

Two-Stage Spatio-Temporal SEEG Modeling

Neural decoding framework for seizure onset zone localization, using transformer-based sequence modeling and contrastive pre-training for cross-patient generalization.

CLM6 Market-Making Engine

Market-making research platform built on reconstructed CME Globex WTI Crude Oil Level-3 order-book data, with FIFO queue modeling, latency-aware paper trading, and strategy evaluation under realistic microstructure conditions.

Distributed CUDA Ray Tracer

GPU ray tracer with coordinator/worker execution, CUDA rendering kernels, UDP-based task distribution, and interactive SFML visualization.

Markdown to HTML Newsletter Generator

Production newsletter pipeline converting structured Markdown into styled, email-ready HTML for HKN Beta Mu chapter communications.