Tom Silver
Princeton CS · Assistant Professor of Electrical and Computer Engineering; Core Faculty, Robotics
Research focus: robot planning and learning · task and motion planning · program synthesis · foundation models
保护对象 0 的手动申请准备审计：一个强拟合的元生成应结合规划与学习，理想情况下应在机器人领域 cs 中实现符号结构、基础模型的能力、样本效率或可部署的具身任务。
Who this advisor fits / 什么情况下适合你
- A strong fit artifact should combine planning and learning, ideally in robotics: symbolic structure, foundation-model affordances, sample efficiency, or deployable embodied tasks.
- 一个强有力的适配模型应结合规划与学习，理想地以机器人领域cs的形式实现：符号结构、基础模型的能力、样本效率或可部署的具身任务。
What to watch for / 什么情况下要慎重
- You need strong placement evidence, but public signals for this PI are still thin.
- 你需要强证据的毕业去向分布，而这位 PI 目前公开信号仍较薄。
Public evidence as of 2026-06-10
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