Ali Bolcakan is a Postdoctoral Research Fellow in Multilingual Digital Humanities in the Department of Comparative Literature at the University of Michigan. Ali’s research focuses on how ideas and texts transform as they move across languages and cultures over long periods of time. His interest began during his dissertation, when he noticed specific patterns in 19th-century translations in Armenian, Greek, and Turkish. He observed that translators would sometimes make significant alterations to the source material—for example, changing a character’s profession to make them more palatable for a different audience. He also found that these changes could be repeated across different languages, suggesting that humanistic data underwent major transformation during transmission, at times using intermediary languages with cascading effects.
These observations led to his postdoctoral project, “Translation Forensics,” which seeks to uncover how cultural works propagate, particularly in contexts with non-Roman scripts and low-resource languages. This work has revealed that a major obstacle is inadequate text recognition for these materials, making even basic textual analysis nearly impossible. This hands-on experience will directly inform his work as a MIDAS postdoctoral affiliate, where he will collaborate with AI scientists to develop innovative AI-enabled workflows for cross-linguistic humanities research.
As a MIDAS postdoctoral affiliate, Ali will have the opportunity to work on creating scalable technologies that directly address these challenges. The project will focus on enhancing text recognition for non-Roman and mixed-script documents, contribute to natural language processing efforts for historical languages, and develop and refine a computational framework to track how textual elements shift between languages. Rather than optimizing for conventional translation accuracy, this approach will train AI to preserve culturally distinct concepts and nuances that existing models typically flatten, to empower scholars to conduct new forms of inquiry using humanistic data.