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Students Present Research and Demo Drone Project at Iona Scholars Day 2019

Four students sit at the panel table as Slominsky moderates.

Ileana Palesi ’19 and Brandon Neilsen ’20 both had the opportunity to present their research during the “Thomas Paine and Multiple Revolutions: Digital Humanities, Protest Movements, and Research at the ITPS” , moderated by Dr. Nora Slonimsky, ITPS and History. Palesi (mentored by Dr. Smiljana Petrovic) discussed her work on “Machine Learning and Authorship Attribution” and Neilsen (mentored by Dr. Lubomir Ivanov) presented his research project titled “Stylistic Features and Authorship Attribution.” The interesting discussion that followed touched topics of anonymity and activism in history and modern times.  

Fran Baille with two students watching as the drone hovers nearby.

The Computer Science Club also showcased software they’ve developed which controls drones through voice command. Brandon Neilsen ’20 demonstrated how the human voice can control drones more efficiently and easier than other user interfaces in a presentation titled "Controlling Drones with Voice Command.".

Support from the Clare Boothe Luce (CBL) program was also on display through research work by  Kathryn Kenny '20 and Amanda Aebig ’19. Kenny (mentored by Dr. Jongwook Kim) presented "Rename Method Refactoring without Using Pretty-printers." Her research involves implementing a novel rename method refactoring tool that directly manipulates source code to produce refactored code without pretty-printing, as well as checking that all preconditions are satisfied.  Aebig (mentored by Dr. Lubomir Ivanov) presented “The Use of Sentiment Analysis in Authorship Attribution of Historical Texts,” which describes her work on extracting sentence-level sentiment values from texts using Stanford CoreNLP API. The sentiment vectors she extracted are used to train deep-learning LSTM networks to look for patterns of temporal change in sentiment throughout texts to attribute the authorship of unknown writings.  

Panelist responds to question.