Teaches in: Cybersecurity
About Me
Ethan Brooks has spent the last eight years working on large language models, from early transformer variants to the latest Mixture-of-Experts systems. He got hooked on AI during grad school when he realized how much efficient model design could impact real applications. Now, he closely follows open-source LLM developments, like Tencent Hy3, to understand how architecture choices affect performance and cost.
In his teaching, Ethan focuses on demystifying complex topics. He uses case studies from his own projects to show how to train, evaluate, and deploy models. Students learn to think critically about trade-offs in AI systems and gain hands-on skills they can apply immediately.
Expertise
Experience
NeuralFlow Systems
Senior Machine Learning EngineerDataMind Labs
AI Research ScientistCloudForge Solutions
Software Engineer - AI TeamAchievements
- Published 4 papers on efficient MoE architectures at conferences including NeurIPS and ICML.
- Open-source MoE toolkit he maintains has over 8,000 GitHub stars and is used in research labs worldwide.
- Delivered a keynote talk at AI Expo 2024 on scaling language models for production.
- Holds AWS Certified Machine Learning Specialty and Google Cloud Professional ML Engineer certifications.
- Contributed to benchmarking frameworks for evaluating LLMs on OpenRouter, with analysis featured in tech blogs.
- Mentored over 50 junior engineers through a community AI bootcamp, focusing on practical LLM applications.
Teaching Impact
- 1 Course
- 4.70 Average Rating
