Text Mining of Publications
A diagram describing the identified clustersIn this project at the Aerospace Systems Design Laboratory under the supervision of Prof. Dimitri Mavris and Dr. Olivia Pinon Fischer, I employed sophisticated topic modeling and text mining techniques to dissect and categorize the lab’s extensive portfolio of academic publications. By meticulously processing and analyzing a vast dataset, I was able to identify and characterize the various research collectives and their thematic clusters within the lab. Leveraging advanced algorithms and machine learning tools, I extracted pivotal patterns and discerned trends that illuminated the lab’s research trajectory and thematic development. This analytical deep dive not only showcased my proficiency in data analysis with Python and R, but also emphasized my capabilities in data visualization and the intricate fields of text mining and topic modeling. Derived insights were presented to lab administration.
Efe Yarbasi is an Assistant Research Scientist in the Engineering Systems Group at the University of Michigan Transportation Research Institute (UMTRI). His research covers the safety of automated and driver-assistance systems and the electrification of transportation. He serves as principal investigator and co-principal investigator on projects sponsored by NHTSA, Toyota Motor North America, and the National Cooperative Highway Research Program. He co-leads the Low Altitude Airspace Working Group at M-Air.
He holds a PhD in Aerospace Engineering from Georgia Tech. There he worked in the Aerospace Systems Design Laboratory under Prof. Dimitri Mavris and developed methods to find and reduce the uncertainties that matter most in complex, multi-disciplinary designs. He is a member of AIAA and IEEE.
Students: I enjoy working with students. If you are interested in my research, please send me an email.