Lilianne Mujica-Parodi

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About me

Lilianne R. Mujica-Parodi is Director of the Laboratory for Computational Neurodiagnostics, and Associate Professor in Stony Brook University's Department of Biomedical Engineering. She holds joint faculty appointments in the Departments of Neurobiology and Behavior (Program in Neuroscience), Neurology, and Psychiatry at Stony Brook University. She additionally holds external appointments as Associate Neuroscientist/Lecturer in Radiology at the A.A. Martinos Center for Biomedical Imaging (Massachusetts General Hospital, Harvard Medical School), as well as Research Affiliate at the McGovern Institute for Brain Research (Massachusetts Institute of Technology). Dr. Mujica-Parodi received her undergraduate and graduate degrees from Georgetown University and Columbia University, respectively, studying mathematical logic and foundations of physics. After her Ph.D. (Niles G. Whiting Fellow), she completed a three-year NIH Training Fellowship in Schizophrenia Research at the New York State Psychiatric Institute. Dr. Mujica-Parodi was subsequently promoted to Assistant Professor of Clinical Neuroscience at Columbia University's College of Physicians and Surgeons, where she performed research for two years until being recruited by Stony Brook University. She is the recipient of the National Alliance for Research in Schizophrenia and Affective Disorder‘s Young Investigator Award (Essel Investigator), the National Science Foundation’s Career Award, and the White House’s Presidential Early Career Award in Science and Engineering. Dr. Mujica-Parodi‘s research interests focus on the application of control systems engineering and complex systems analysis to neuroimaging (fMRI, MEG, EEG, NIRS, ECOG), with neurodiagnostic applications to neurological and psychiatric disorders. In her Physiology and Disease course for SchoolNova, Dr. Mujica-Parodi introduces students to complex systems analysis, using a hands-on approach in which students approach dynamic interrelationships between variables on a purely intuitive and visual basis, and in a manner that requires no prior experience. STELLA software by isee (http://www.iseesystems.com/softwares/Education/StellaSoftware.aspx) meets the challenge of teaching young people to 'think systems' far before they have the mathematical skills to describe them quantitatively. Specifically designed for K-12, STELLA uses easy-to-manipulate graphics (stocks, flows, connectors, and converters) in order to graphically represent relationships and run simulations. 'Thinking systems' is one of the areas that should be started at a young age because it informs innovative thinking about other subjects. Many of the most interesting features of the world are systems, maintained by negative feedback loops, and the societal implications for breakdown of these systems can be catastrophic. Systems-based phenomena are, for example, as varied as species collapse caused by predator-prey-food imbalance following deforestation, global warming, and the 2008 U.S. housing market collapse. Unfortunately, as the world has become more complex, science curricula have failed to capture and teach the dynamics of these phenomena, most likely because their description requires differential equations, and but also because teachers themselves are typically not trained in mathematical modeling. Young people have become increasingly accustomed to computer-based learning, and schools are largely recognizing this by integrating computers more and more into the classroom. Teaching students to think in a systems-based way not only prepares them to approach the direction towards which science is moving, but also teaches them to think more holistically and analytically about the wider world around them.