Erik Goh is an M.S. student in CS at Georgia Tech, specializing in ML. He first-authored two pending publications with Dr. David Joyner and Dr. Ana Rusch, where he applied programmatic web scraping, LLMs, text embeddings, and unsupervised learning to uncover insights in large-scale learning. Prior to DILab, Erik also worked in ASDL’s Energy Infrastructure and Data Engineering group, modelling energy data and census information for resource planning. His industry background includes leading technical and creative innovation teams prototyping, pitching for funds, and building products; his latest one was funded by Microsoft, for a product that leverages GOFAI, ML, and LLM for revenue identification. He is currently also a research assistant in DILab, working on VERA.

Research Interest: Self-Reasoning, Meta-Learning, Cognitive Architectures, AI Education, Knowledge Representation, Transfer Learning.

LinkedIn: https://www.linkedin.com/in/ewg0000/