Welcome
At the Yang Research Group at Johns Hopkins University, we build AI copilots that help people make complex decisions. We combine scientific theory, domain knowledge, and physical constraints to help these systems reason through engineering problems, run simulations, and use tools. We study how copilots can learn from people’s choices and feedback, adapt to their goals and values, and help them judge when to trust a recommendation. We also design adaptive mixture-of-experts systems that match computing effort to the task to reduce response times, energy use, and deployment costs. Transportation and public health are our main application areas, where we test how these copilots can strengthen human judgment in practice.
News
Paper published in Transportation Research Part C
Hopkins engineers put large language model agents behind the wheel to study how AI agents reason in driving scenarios.
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NCHRP project awarded on generative AI for transportation planning
Prof. Hao Frank Yang will lead a Johns Hopkins research project developing a primer for using generative AI models in transportation planning.
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Paper accepted to NeurIPS 2025
We are excited to announce that our papers have been accepted to NeurIPS 2025. Congratulations to the authors!
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Paper published in IEEE TPAMI
A research team led by Prof. Hao Frank Yang developed an EMOS framework to improve autonomous driving safety and efficiency.
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Paper published in Nature Communications
Our paper on SafeTraffic Copilot has been published in Nature Communications and featured by the JHU Hub. Congratulations to the authors!
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