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Teaching is more sophisticated than simply delivering knowledge. It is just as important, if not more, to inspire the interests from students and to help them master the skills of learning and creation. I believe that my role, as a science instructor and a mentor, is to advise the students in the process of transforming their dreams into goals and then to guide them along the paths that will make them reach these goals.
I have taught and designed courses in my areas of expertise, Applied Mathematics, Bioinformatics and Computational Biology that cover both undergraduate and graduate studies. Here is a list of my recent classes:
ECS15:
This is an introductory class on computers for non-CS major. It provides an introduction to computers, covering hardware, software, and networking. It includes an introduction to programming, using Python as an example of computer language. It does include a writing assignment on the use of computers in a field of interest to the student.
The class include traditional lectures and weekly computer labs to practice the skills covered in the lectures.
ECS129:
Tangible success of the many genome sequencing projects currently underway (from human to dog, mouse, rat, tomatoes,…) will come from the unraveling of the information contained in the corresponding sequences, and from constructing models that relate the genotype (i.e. the information coded in the genes) to the phenotype (the physical manifestation) of an organism. Our goal in this course is to provide an overview of the challenges faced by bioinformatics, a new branch of both computer science and biology whose aims are to collect, organize and analyze the data coming from these genomics projects. We will focus in particular on the importance of structural data.
ECS293A:
Research in computer science. This is an orientation class for new graduate students in computer science. It covers: study of important research topics in computer science, PhD level research methodologies (experimental, applied and theoretical), presenting research results for the computer science community. It also describes the study skills that are necessary to successfully find/solve significant research problems.
BL5229:
Data analysis and modeling in biological sciences. This class aims at providing students with concepts and general techniques that are essential for modeling, analyzing and visualizing data as well as for testing and validating models, with applications in the domain of biology.
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