My name is Jennifer Ogden and I am one of the speakers for the talk entitled “Reducing the data complexity with filtering and clustering” along with Rachel Davis of Drake University and Rehan Raiyyani of University of California, San Diego. This talk is part of the mini symposium “Combining disciplines, techniques, faculty, and students to tackle protein folding” organized by Dr. Silvia Crivelli.
Ever since high school, I have always been interested in bioengineering, so when I heard about the internship at the Lawrence Berkeley National Laboratory to work on protein folding it sounded like the perfect opportunity to learn more about proteins and their functions as well as an opportunity to get more involved with computer sciences. Throughout my internship, my knowledge of computational sciences has improved vastly and I even got to work on Hopper, one of the fastest supercomputers in the world. The SIAM conference seems like the perfect opportunity to expand my knowledge and understanding of the many different applications of computer science and engineering. This conference will also allow my colleagues and I to display our advancement on the filtration and clustering systems of prediction protein structures and develop our professional careers. I feel very passionate about this subject since protein structure prediction can revolutionize the health industry and human life as we know it. We can potentially design and engineer proteins that can eliminate fatal diseases such as cancer and prolong human life expectancy.
Unfortunately, I do not have the financial resources to attend this conference on my own. Without your support I will have to withdraw my participation, which will prevent me from getting a unique educational experience that will connect me with students and researchers from all over the country and have an impact on my career. Read more about Jennifer’s WeFold internship here.