I lead research in scientific computing: the application of computers to solve scientific challenges of the 21st century. Scientific computing is inherently multidisciplinary, situated at the intersection of computer science, mathematics, and the natural sciences. My research agenda in scientific computing can be exemplified by three areas of interest that I will outline below.
My first area of interest revolves around simulations of physical processes via high performance computing. In my current position at UCLA, in my previous postdoctoral position at University of Chicago, and as a graduate student at Ohio State, I utilized supercomputers to model lasers, plasma, fluids, particle beams, and a variety of laboratory detectors.
My second area of interest is in the development and implementation of computational data analysis methods. My work in this area includes image analysis as well as statistical analysis of large datasets created from scientific experiments and computer simulations. As an example, a typical scientific experiment may produce millions of digital photographs and oscilloscope traces representing exploding plasmas, and each image may contain a small amount of distinct information of interest to the scientist.
My third area of interest is in computerized data acquisition, sensor development, and mechatronics for scientific laboratories. An example of my work in sensor development can be found in the linear-CCD-based proton spectrometer in Morrison, Feister, et al. 2018, New Journal of Physics.
My research agenda provides opportunities for students to be part of cutting-edge, interdisciplinary applications of scientific computing. My research is interwoven with many international collaborators and collaborations that I have built over the years. I am excited to bring my expertise to my colleagues and students, while developing my research into the future.
My conception of teaching is to motivate students to learn, give them access to knowledge, and work with them to apply their knowledge in real-world contexts. In contrast to being in the driver’s seat of my students’ education, I view myself as the spark that ignites their engines. To consider my teaching a success, I hope for students to be confident and capable of independently carrying themselves forward after course completion: knowing where to engage for further study on the topic, comfortable working and solving problems without a teacher involved, and confident enough in themselves to teach others.
Three principles that guide me as an educator are developing independent motivation and ability, integrating real-world context, and project-based learning.
First, I strive to inspire independence in students. Since I will not be able to help the students apply their knowledge once they leave my classroom, I must lead them to independence while they are in the classroom.
Second, I show students how knowledge fits into or is applied in the real world. For example, in teaching Computer Organization and Architecture at CSUCI, I discuss not just how computer systems can be organized, but also how the computer chips in their smartphones currently are organized. I also enabled students in that class to test their final project code on parallel computing clusters across the country.
Third, I use projects in my teaching wherever possible. For example, I am currently leading undergraduates at CSUCI to build computer imaging sensors, mechatronics, and data processors. I tie their projects into the real world: once complete, their projects will be installed in a scientific research laboratory.
Frequent assessment, reflection, and modification of my teaching process allows me to continually improve. I hope to continue to refine my approach throughout my career.
I am an Assistant Researcher at University of California Los Angeles, where I lead supercomputer simulations, analyze large digital datasets, and design electronic hardware for scientific study of laser-laboratory astrophysics. My research focuses on applying computer science to solve scientific problems. I also teach part-time at California State University Channel Islands. I was previously a Postdoctoral Scholar at the Flash Center for Computational Science at University of Chicago, and a Research Scientist at the Air Force Research Laboratory. I earned a Ph.D. at The Ohio State University and B.S. at University of Notre Dame.
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