CRCD: Machine Learning: A Multidisciplinary Computer Engineering Graduate Program

wunsch, Donald Dunyak, James P.Feldkamp, Lee A.德克萨斯理工大学crcd：机器学习：一个多学科的计算机工程研究生项目CISE联合研究课程开发提案请求资金在计算机工程硕士和博士项目中开发机器学习轨道。机器学习将是跨学科的，将包括高级本科/研究生水平的三门新课程：高级神经网络（CS），动态规划（数学）和自适应批评设计（EE）。新课程将包括通过远程学习与领先的工业研究人员进行互动。除了新课程，还有四个实验室轮转：计算智能实验室（EE）、工业应用实验室（EE）、应用概率实验室（数学）和软件工程实验室（CS）。在实验室轮转课程中，学生将被组织成团队，并被引导进行与工业直接相关的实际研究问题。作为一个顶点的经验，学生将参加一个学期的实习在国家实验室或工业设施。PI将同时开发一本关于适应性批评设计的教科书。这个项目有可能产生重大影响。它可以作为其他机构设计新的跨学科学位课程的典范。

EIA 9980296Wunsch, Donald Dunyak, James P.Feldkamp, Lee A.Texas Tech UniversityCRCD: Machine Learning: A Multi-disciplinary Computer Engineering Graduate ProgramThis CISE Combined Research-Curriculum Development proposal requests funds to develop a machine learning track in Computer Engineering M.S. and Ph.D. programs. The machine learning track will be interdisciplinary and will include three new courses at the senior undergraduate/graduate level: Advanced Neural Networks (CS), Dynamic Programming (Math), and Adaptive Critic Designs (EE). The new courses will include interaction with leading industrial researchers through distance learning. In addition to the new courses, there will be four laboratory rotations: Computational Intelligence Laboratory (EE), Industrial Applications Laboratory (EE), Applied Probability Laboratory (Math), and Software Engineering Laboratory (CS). For the laboratory rotation courses, the students will be organized in teams and directed towards real research problems with direct industrial relevance. As a capstone experience, students will participate in a one-semester internship at a national laboratory or industrial facility. The PI's will concurrently be developing a textbook on Adaptive Critic Designs. This project has the potential to have a significant impact. It could serve as a model for the design of new interdisciplinary degree programs at other institutions.