Dr. Avijit Ghosh

Dr. Avijit Ghosh is a Lead Technical AI Policy Researcher at Hugging Face, a central platform for open AI models, datasets, and research tools used by industry, government, and academic developers worldwide. He is also a Research Affiliate at the University of Connecticut. His work sits at the intersection of AI research and policy, with a central focus on how we measure and benchmark AI systems, and whether those measurements can actually be trusted. He founded and leads the EvalEval Coalition, a multi-stakeholder initiative bringing methodological rigor and accountability to AI evaluation. His broader research spans algorithmic bias, agent autonomy, AI for science, and third-party flaw disclosure, with coverage in The New York Times, Forbes, The Guardian, ProPublica, Wired, and MIT Technology Review. He represents Hugging Face in technical engagements with legislators and regulators in the United States, United Kingdom, European Union, and Singapore on open-source AI governance and evaluation standards. His work has helped shape AI regulation in New York City and prompted Facebook to remove its biased ad targeting algorithm.