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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
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Posts
Future News
Published:
What’s up?
Blog Post number 4
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 2
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 1
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
portfolio
Portfolio item number 1
Short description of portfolio item number 1
Portfolio item number 2
Short description of portfolio item number 2
publications
Paper Title Number 1
Published in Journal 1, 2009
This paper is about the number 1. The number 2 is left for future work.
Recommended citation: Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1). http://academicpages.github.io/files/paper1.pdf
Paper Title Number 2
Published in Journal 1, 2010
This paper is about the number 2. The number 3 is left for future work.
Recommended citation: Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2). http://academicpages.github.io/files/paper2.pdf
Paper Title Number 3
Published in Journal 1, 2015
This paper is about the number 3. The number 4 is left for future work.
Recommended citation: Your Name, You. (2015). "Paper Title Number 3." Journal 1. 1(3). http://academicpages.github.io/files/paper3.pdf
talks
Talk 1 on Relevant Topic in Your Field
Published:
This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Biosimulation I
Graduate course, BMES-672, 2018
Biomedical engineering is at the interface of mathematics, engineering, and biology / medicine. This course will be on the mathematical analysis of biomedical engineering systems. As the first course in the Biosimulation sequence, it will emphasize analytical methods and the development of models. This course will provide the foundations for the modeling and mathematical analysis of biomedical engineering systems, with an emphasis on differential equations and an introduction to probabilistic methods. In general, the focus will be on analytical techniques, setting the stage for BMES673, which introduces numerical methods and other advanced computational techniques for solving applied problems. Modeling and specific biological and biomedical applications will be introduced through examples and experience.
Biosimulation II
Graduate course, BMES-673, 2018
Biomedical engineering is at the interface of mathematics, engineering, and biology / medicine. This course is the second in the Biosimulation sequence on the mathematical analysis of biomedical engineering systems. It will emphasize numerical methods for simulation to analyze models and generate predictions. As a whole, this course will provide the foundations for computer modeling and mathematical analysis of biomedical engineering systems. The numerical methods that are presented in this course are not only useful for general problems throughout science and engineering, but also helpful for complex computational problems involved in biological and biomedical domains. By studying numerical methods students can become more informed users of the underlying numerical algorithms used in bioengineering environments, and be better prepared to evaluate and judge the accuracy of the model results. Much more complex and applicable models with simulations will be introduced in this course than BMES672, since we will have access to computer simulation.
Neural Networks
Graduate course, BMES-725, 2019
The emergence of big data, machine learning algorithms, and increased computing power has enabled significant breakthrough in neural networks and related applications. This class will discuss recent progress and findings in the exciting field of deep learning. While mathematical aspects will be covered, the primary goal is to provide students with the deep learning tools and technical aspects needed to solve the data science problems in biomedicine. Besides the construction by students of computer simulations of important deep neural networks, the class will also show how to develop deep learning applications in the Cloud. Selected applications in computational neuroscience, computational biology, medical imaging, and electronic medical records will be discussed.