Raymond Mooney
UT Austin CS · Professor, Professorship In Computer Sciences #3
Research focus: natural language learning · grounded language learning · statistical relational learning · information extraction
保护项目第 3 项：构建以 natural language learning 为基准的适配图，基于 grounded language、semantic parsing、information extraction、人机对话、explainable AI 等要素，引用一个可见的实验室主题、校友/就业模式、基准信号、招募/状态警告或当前项目领域，并提出一个具体的第一学期研究扩展。
Who this advisor fits / 什么情况下适合你
- You want ML tied to real data and deployable problems (signal: natural language learning · grounded language learning).
- Applicants should show real NLP/ML research: semantic parsing, grounded language, information extraction, human-robot dialog, multimodal reasoning, explainable AI or code/documentation generation, wit
- 你想把 ML 接到真实数据与落地问题（当前信号：natural language learning · grounded language learning）。
- 申请人应展示具有真实 NLP/ML 研究：semantic parsing、基于语言学的 grounded language、information extraction、人机对话、多模态推理、explainable AI 或代码/文档生成，并具备可发表的实验及清晰的错误分析。
What to watch for / 什么情况下要慎重
- You want pure theory ML with little domain data or cross-disciplinary collaboration.
- 你要的是纯理论 ML、几乎不碰领域数据或跨学科合作。
Public evidence as of 2026-06-10
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