Summary
Sky Wang is a research scientist at Abridge with 11 years of experience building human-centered NLP and ML systems that bridge language technology and real-world users. His work spans post-training alignment, model steering, mechanistic interpretability, and text-as-data methods, informed by a PhD from Columbia and NSF Graduate Research Fellowship–supported research. Sky has interned and collaborated with top labs including Google, Microsoft, Amazon, and Microsoft Research, tackling accessibility, toxicity, reasoning, and language grounding across applied and theoretical settings. He brings a rare blend of computational social science and machine-learning rigor, with award-winning EMNLP papers and extensive peer-review service across leading conferences. Notably, his approach emphasizes controllability and user modeling—designing algorithmic tools that make models more responsive to people’s needs rather than solely more capable. Based in New York, he combines academic depth with practical industry impact, from agentic evaluation to post-training alignment work at Abridge.
10 years of coding experience
4 years of employment as a software developer
Bachelor of Science in Engineering - BSE Computer Science, Bachelor of Science in Engineering - BSE Computer Science at University of Michigan
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Columbia University