Michael Glass is a research staff member at IBM with a PhD in Computer Science from the University of Texas at Austin and roughly eight years of professional research experience building LLM-based solutions for natural language understanding and code generation. His work spans pre-training transformer architectures, question answering, information extraction, and knowledge base completion, with notable open-source contributions in TableQA, HotpotQA, KILT tasks, and table augmentation. He combines deep academic training—rooted in a long UT Austin affiliation—with practical systems work dating back to early software development and internships in industry. Based in Bayonne, NJ, he maintains a public research footprint on Google Scholar and GitHub, signaling a commitment to reproducible, community-facing research. An interesting through-line in his career is the steady pivot from classical research assistant roles into leading applied LLM efforts that bridge QA benchmarks and production-ready tooling.
8 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at The University of Texas at Austin
Code to create pre-training data for a span selection pre-training task inspired by reading comprehension and an effort to avoid encoding general knowledge in the transformer network itself.
Contributions:4 commits, 4 pushes, 1 comment in 1 year 7 months
nlpeffortknowledgespancomprehension
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