Teaching
Courses @ Drexel University
BMES-725 Neural Networks (Spring, 2018-present)
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 Google Cloud Platform. Selected applications in computational neuroscience, computational biology, medical imaging, and electronic medical records will be discussed.
BMES-672 Biosimulation I (Starting in Fall of 2010, and annually thereafter)
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.
BMES-673 Biosimulation II (Starting in Winter of 2010, and annually thereafter)
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.
Courses @ Univerity of Texas
- Biomedical Signal Processing (HI 5321)
- Introduction to Computational Biomedicine (HI 5320)
- Data Mining in Bioinformatics (HI 6323)
- Advanced Topic in Computational Biomedicine (HI 6322)
- Methods in Computational Biomedicine (HI 5370)