Cevat Ustun

Cevat Ustun has extensive experience in the field of data science and neuroscience. Cevat worked as a Senior Data Scientist at Beyond Limits, where they successfully applied analytical techniques to handle sparse datasets and reduce the dimensionality of problems. Cevat also utilized optimization techniques to address various problems. Prior to that, Cevat worked as an independent Data Scientist, where they honed their skills in data analysis. Cevat served as a Staff Research Associate at the University of California, Los Angeles, where they performed experiments and constructed neural network models to understand object recognition in the visual area of the primate brain. Cevat also used clustering algorithms and decision theory to predict cognitive uncertainty in decision-making tasks. As an Independent Scholar, Cevat published an innovative neural network model of a primate brain region involved in visually guided reaches, providing profound insights into the nature of information processing in the brain. Cevat also worked as a Post-doctoral Scholar and Senior Scientist at Caltech, where they co-wrote and obtained funding for a research proposal on understanding the primate brain during visually guided reaching. Additionally, they developed statistical models to infer intended arm movements from neural activities for the purpose of driving robotic limbs.

Cevat Ustun pursued their education in the field of physics, starting with a Bachelor of Science degree from Istanbul Technical University. Cevat attended the university from 1990 to 1995. Later, they went on to obtain a Ph.D. in Physics from the University of Maryland, where they studied from 1997 to 2005.