Peng Chen Email & Phone Number | I am interested in developing a set of algorithms to compute confidence regions on the optima of various flexible and distribution-free statistical models. It applies to many fields, such as hyperparameter tunning in machine learning, drug cost reduction in the pharmaceutical industry, and hypothesis testing in evolutionary biology. In general, it provides a measure of uncertainty for the optima of functions learned from data. My other specialties include classic experimental design, optimal design theory, statistical process optimization, time series analysis, statistical process control, and Bayesian statistics. I am familiar with traditional machine learning methods as well as deep learning, including convolutional neural networks and recurrent neural networks. I can implement these learning methods effectively using Keras or Tensorflow in either R or Python.

Peng Chen

I am interested in developing a set of algorithms to compute confidence regions on the optima of va...
State College, Pennsylvania, United States

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Peng Chen’s Location State College, Pennsylvania, United States

Peng Chen’s Current Industry Penn State University

Peng Chen’s Prior Industry University Of Missouri Columbia | East China University Of Science And Technology

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Research Assistant at Penn State Engineering Statistics and Machine Learning Lab

2016-08-01T00:00:00.000Z - Present

Teaching Assistant

2014-01-01T00:00:00.000Z - 2015-05-01T00:00:00.000Z

President of Electrical Engineering Students Community

2009-09-01T00:00:00.000Z - 2012-08-01T00:00:00.000Z

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Peng Chen is a I am interested in developing a set of algorithms to compute confidence regions on the optima of various flexible and distribution-free statistical models. It applies to many fields, such as hyperparameter tunning in machine learning, drug cost reduction in the pharmaceutical industry, and hypothesis testing in evolutionary biology. In general, it provides a measure of uncertainty for the optima of functions learned from data. My other specialties include classic experimental design, optimal design theory, statistical process optimization, time series analysis, statistical process control, and Bayesian statistics. I am familiar with traditional machine learning methods as well as deep learning, including convolutional neural networks and recurrent neural networks. I can implement these learning methods effectively using Keras or Tensorflow in either R or Python.

Peng Chen has prior
experience in the following industries:
University Of Missouri Columbia | East China University Of Science And Technology

Peng Chen has the following professional experience:
Penn State University | University Of Missouri Columbia | East China University Of Science And Technology