Summary
Justin Zeng is an AI engineer and researcher with 12 years of experience, currently advancing multimodal and agentic ML workflows as a Graduate Research Assistant at Columbia Engineering. He builds production-ready LLM orchestration and RAG systems that translate complex, high-stakes research—ranging from EEG time-series prediction to clinical audit automation—into measurable enterprise impact. His background spans university research and industry engineering at AWS, TD Bank, and AI startups, where he delivered multilingual fraud detection, optimized distributed systems, and benchmarked agent frameworks across hundreds of edge cases. Justin combines signal processing and NLP expertise (LoRA, PyTorch, LangGraph) with a practical focus on Responsible AI and stakeholder-aligned deployment. He thrives in cross-functional teams solving non-obvious problems and, outside work, pursues skiing, travel, and culinary adventures—reflecting a taste for high-altitude challenges and diverse perspectives.
12 years of coding experience
2 years of employment as a software developer
Bachelor of Science in Informatics Magna Cum Laude Informatics, Bachelor of Science in Informatics Magna Cum Laude Informatics at University of Washington
Bachelor of Science - BS Informatics, Bachelor of Science - BS Informatics at University of Washington Information School
Master of Science - MS Data Science, Master of Science - MS Data Science at Columbia Engineering
Newport High School