Carnegie Mellon University, Graduate School of Industrial Administration, Doctor of Philosophy., Wei, Wei. (2015). Learning Latent Event Representations: Structured Probabilistic inference on Spatial, Temporal and Textual Data. Institute for Software Research, CASOS Center, Graduate Student Thesis Proposal. Daimler, Eric. (2013). Machine detection of persisting pragmatic linguistic.
With these challenges in mind, this thesis focuses on developing novel neural architectures and training objectives that are highly expressive, allow for efficient optimization, and can scale to a large amount of data for generative modeling.
I am working on an AI startup. My research interests include deep learning and natural language understanding. In 2019, I obtained my PhD degree from the School of Computer Science, Carnegie Mellon University, advised by Ruslan Salakhutdinov and William W. Cohen.Prior to that, in 2015, I received my bachelor's degree from Tsinghua University, advised by Jie Tang.
In this dissertation, I identify key challenges of sensing at scale- the ability to track multiple users and activities in an environment at the same time. The need to build reliable novel approaches that detect multiple activities from the same sensor stream and identify the user performing those activities presents a unique technical challenge.
Carnegie Mellon’s Department of Electrical and Computer Engineering offers one undergraduate degree and two graduate degrees, the Masters of Science and Ph.D. Included as part of these degree programs is the ability to complete studies at various campuses throughout the world. Carnegie Mellon University ——— Search Search Search this site only. Electrical and Computer Engineering.
The Carnegie Mellon University School of Architecture is pleased to announce the guest speakers for the 2020 Fall Lecture Series. The Fall Lecture Series will focus attention on architecture and activism, and the role that architecture can have towards social equity and spatial justice.
Doctor of Philosophy (PhD) Program The Robotics doctoral program is committed to preparing students to be world-class researchers, creating knowledge and artifacts that can impact our society. Graduates of the program will take a leading role in the research and development of future generations of integrated robotics technologies and systems.
We participate in the Medical Scientist Training Program (MSTP) sponsored jointly by Carnegie Mellon and the University of Pittsburgh. The mission of the MSTP, funded partly by the National Institutes of Health, seeks to train talented students to become physician-scientists in an environment that integrates superlative medical education and customized graduate work in biomedical research.