Syracuse Sun

The College of Arts and Sciences’ Forensic and National Security Sciences Institute (FNSSI) is offering courses designed to equip students with the skills to analyze complex data using computational methods and algorithms. One such course, "Computational Forensics," taught by Filipe Augusto da Luz Lemos, focuses on coding, machine learning, and artificial intelligence (AI) in the field of digital forensics.

Brianna Cardillo, a graduate student in forensics, undertook a project titled “What to Read Next? Using Historical Reader Preferences to Promote Books from Marginalized Authors,” which aimed to develop a machine learning algorithm to promote works by underrepresented writers. Cardillo shared her motivation, stating, “I have read so many books from authors like Faridah Àbíké-Íyímídé that deserved more praise than they got.”

Cardillo's algorithm suggests books based on readers’ interests, taking into account factors such as genre, length, average ratings on Goodreads, and authors’ race. She hopes her work will encourage readers to actively choose and promote diverse stories, emphasizing the influence readers have on promoting underrepresented authors.

In response to the project, Lemos noted that Cardillo’s work exemplifies the course's goal of solving contemporary issues with computational methods. He highlighted the transferable skills developed by students, emphasizing their ability to identify problems suitable for machine learning solutions and design algorithms to automate tasks efficiently.

Cardillo expressed her desire to expand the algorithm to include authors from various marginalized communities, stating, “I would love to include authors of many different identities so that everyone can find books where they feel represented.”

Upon graduation, Cardillo aims to work as a forensic DNA analyst in a crime laboratory, where she believes her experience in problem-solving and creative thinking through projects like this will be beneficial. She emphasizes the importance of being able to adapt and find solutions quickly in a dynamic work environment.

Overall, Cardillo's project showcases how machine learning can be used not only for forensic purposes but also to address societal issues such as promoting diversity and visibility for underrepresented authors.