Peer-reviewed work, conference proceedings, and technical reports from the AoE collective. All research is tethered to our three core domains — Energy, Medical Systems, and Foundations.
A non-invasive "aerosol fingerprinting" framework for algae-based hydrogen reactors that uses low-cost sensor arrays and Edge-AI to analyze reactor headspace emissions in real time. The system correlates bioaerosol shifts with physiological stress states in Chlamydomonas reinhardtii cultures — providing 3–4 hour early warnings ahead of traditional optical detection. A two-stage ML pipeline (unsupervised anomaly detection + supervised stress classification) achieved 94.6% classification accuracy with sub-10-minute inference on edge hardware, directly closing the control loop for stable green hydrogen production.
Both works here are outputs of the BIOLOOP initiative — AoE's flagship project building closed-loop biological systems for green hydrogen production. Research spans real-time bioaerosol monitoring, AI-driven anomaly detection, computational intelligence, and electrochemical pathway modeling in algae-based reactors.