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​Shira Broschat



Shira Broschat is a professor in the School of Electrical Engineering and Computer Science at Washington State University and an adjunct professor in the Paul G. Allen School for Global Animal Health and the Department of Veterinary Microbiology and Pathology. She is also the diversity and curriculum coordinator in the School of EECS as well as the coordinator for the Eastern Washington Affiliate of the National Center for Women & Information Technology’s (NCWIT) Aspirations in Computing award program.

Her research was initially in the area of wave propagation and scattering from randomly rough surfaces, which can be considered a branch of applied physics. Her focus was on the development of theoretical models for rough surface scattering, which led to equations that had to be solved using numerical methods. On the basis of this research she was made a Fellow of the Institute of Physics, the Institute of Electrical and Electronics Engineers (IEEE), and the Acoustical Society of America. In the early 2000s she was looking for new challenges and became interested in microbiology. Fortuitously, she was approached by a research team in need of someone to provide computational analysis of biofilm data. Since that time, she has been drawn further into the microbiology arena. Her current research collaborations are all with microbiologists, and she has found the variety of research projects to provide constant intellectual challenge and stimulation as well as the opportunity to learn. Each problem she has tackled has employed a novel approach ranging from developing supervised machine learning algorithms to clustering hundreds of thousands of bacterial proteins to developing a pattern matching algorithm. For example, her research team developed two machine learning algorithms for predicting apicoplast-targeted proteins and apicoplast-targeted transmembrane proteins for Apicomplexan pathogens such as Plasmodium and Babesia. In another project, with Dr. Kelly Brayton, they devised a heuristic approach for the identification of type IV secretion system (T4SS) effector proteins in Anaplasma marginale. She also has a long-standing interest in antimicrobial resistance and in developing software tools to analyze genomic (big) data. One of her goals is to provide intuitive and easy-to-use software that will assist microbiologists and other life scientists with their research. For more information, go to bcb.eecs.wsu.edu.