I'm a PhD student in Computer Science at the University of Rochester, working in the Formal and Computational Semantics lab (FACTS.lab) advised by Aaron White.
My work bridges formal semantics and NLP: I explore how theories of meaning can enhance machine reasoning, and how computational methods can help us refine those theories.
At Grammarly, I worked on the core product, implementing and shipping suggestions for improving grammar, style, clarity, and tone of the text. I also led a subteam of computational linguists, handling project planning, task prioritization, and technical supervision.
Master's project: Toward Logical Form Induction: Encoding and Decoding Types.
Fulbright Graduate Student Program grantee.
Thesis: Automatic error correction in Ukrainian text with the help of machine learning models.
Thesis: Automatic detection and correction of spelling errors in Ukrainian text based on the noisy channel model.
We introduce a novel task, event-keyed summarization (EKS), the goal of which is to produce a contextualized summary anchored to a specific event given a document and an extracted event structure.
I present two silver datasets for coreference resolution in Ukrainian, adapted from existing English data by manual translation and machine translation in combination with automatic alignment and annotation projection.
We have built a large-scale corpus for grammatical error correction and fluency in Ukrainian. UA-GEC includes texts from a diverse pool of contributors, annotated by professional proofreaders for errors relating to fluency, grammar, punctuation, and spelling.
We have built a large-scale corpus for grammatical error correction and fluency in Ukrainian. UA-GEC includes texts from a diverse pool of contributors, annotated by professional proofreaders for errors relating to fluency, grammar, punctuation, and spelling.