Faculty Researchers (hide)

Aaron Steven White
Aaron Steven White
Aaron is an Assistant Professor in the Department of Linguistics at the University of Rochester, with a secondary appointment in the Department of Computer Science and an affiliation with the Goergen Institute for Data Science. He directs the FACTS.lab and co-leads the MegaAttitude Project and the Decompositional Semantic Initiative.



Postdoctoral Researchers (hide)

Julian Grove
Julian Grove
Julian is a post-doc in the FACTS.lab. He is interested in integrating Bayesian probabilistic models of inference with type-theoretic natural language semantics. He is also interested in characterizing dynamic semantic phenomena, such as presupposition, by relying on theories of effects, and determining how those characterizations should be combined with one another.



Graduate Researchers (hide)

Siddharth Vashishtha
Siddharth Vashishtha
Sid is a fourth-year PhD Student in Computer Science advised by Aaron White. His research work focuses on extracting event semantics from natural language text. His latest projects involve working on temporal reasoning in natural language inference systems and temporal relation extraction.
William Gantt
William Gantt
Will is a fourth-year PhD student in Computer Science advised by Aaron White. His research interests lie broadly in natural language understanding and information extraction, with a focus on document-level event understanding. Some of his recent projects along these lines include work on models for iterative template extraction, as well as resource development and modeling forevent structure. He has also worked on investigations of patterns in lexically-triggered belief and desire inferences across the English lexicon.
Hannah An
Hannah An
Hannah is a fourth-year PhD student in Computer Science co-advised by Aaron White and Len Schubert. Her research aims to enable computers to acquire lexical knowledge for better language understanding. Her current project involves collecting annotated data for verb phrase ellipsis and developing models for identifying and resolving the ellipses. She has also worked on investigating neg-raising inference triggers using a lexicon-scale dataset.
Benjamin Kane
Benjamin Kane
Ben is a fourth-year PhD student in Computer Science co-advised by Aaron White and Len Schubert. His current research involves creating natural language inference models predicting belief and desire inferences (including modeling annotator disagreement in natural language inference), and he is interested in future applications of these models in plan-based dialogue systems.
Stephanie N. Richter
Stephanie N. Richter
Stephanie is a second-year PhD student in Linguistics co-advised by Aaron White and Asia Pietraszko. Her current research is focused on statistical models of acceptability, prototypicality, and word sense.
Constanza Aceves Rodriguez
Constanza Aceves Rodriguez
Constanza is a second-year PhD student in Linguistics and Computer Science co-advised by Scott Grimm, Aaron White, and Nadine Grimm. Her current research focuses on cross-linguistic analysis of English and Spanish clause-embedding verbs.
Jack Valinsky
Jack Valinsky
Jack is a second-year MS student in Linguistics advised by Scott Grimm. His current research focuses on how lexical and syntactic features affect interpretability and acceptability of degraded environments.
Arsal Imtiaz
Arsal Imtiaz
Arsal is a second-year MS student in Computer Science. His current research focuses on building fully-featured web-based annotation tools for natural language processing.
Angela Cao
Angela Cao
Angela is a M.Sc. student in Linguistics at the University of Edinburgh. Her research interests include using language data to explore causal models of cognition.



Undergraduate Researchers (hide)

Alexander Martin
Alexander Martin
Alex is a third-year undergraduate student in Computer Science. His current research focuses on information extraction and summarization.
Steven Oufan Hai
Steven Oufan Hai
Steven is a third-year undergraduate student in computer science. His current research focuses on building a web-based annotation tool.
Pinxin Liu
Pinxin Liu
Pinxin is a second-year undergraduate student in Computer Science. His current research focuses on coreference resolution.
Jakob Dravk
Jakob Dravk
Jakob is a third-year undergraduate student in Linguistics. His research interests include referring expression generation and coreference.
Carina Giordano
Carina Giordano
Carina is a second-year undergraduate student in Linguistics. Her research interests include referring expression generation and coreference.
Rachel Hamelburg
Rachel Hamelburg
Rachel is currently a fourth-year undergraduate student in Linguistics, Spanish, and Comparative Literature at the University of Rochester. Her research interests include information extraction and natural language understanding.



Alumni (hide)

Chandrashekar Nair
Chandrashekar Nair
Chandrashekar is currently a software engineer at Everlaw. While in the FACTS.lab, his research focused on building fully-featured web-based annotation tools for natural language processing.
Zhendong Liu
Zhendong Liu
Zhendong is currently a first-year PhD student in Linguistics at the University of Southern California. While in the FACTS.lab, his research focused on the nature of clause-embedding in Mandarin.
Weiwei Gu
Weiwei Gu
Weiwei is currently a first-year PhD student in Computer Science at Arizona State University. While in the FACTS.lab, his research focused on document-level information extraction and question answering.
Ellise Moon
Ellise Moon
Ellise is currently a fourth-year PhD student in Linguistics and Philosophy at the University of Rochester. Their current research focuses on countability and count-mass coercion. While in the FACTS.lab, their research focused on the temporal interpretation of nonfinite clause-embedding structures.
Venkata Govindarajan
Venkata Govindarajan
Venkat is currently a fourth-year PhD student in Linguistics at the University of Texas, Austin. While in the FACTS.lab, his research focused on the expression of generalizations in text.