Projects

My ongoing funded projects include:

• Learning science concepts through metaphor comprehension, production, and conversation: Behavioral, neural and artificial intelligence measures (NSF BCS 2140897; funded since 2022), in which we are using language models to help students generate metaphors and improve their science knowledge.

My past funded projects include:

• Extended Methods and Software Development for Health NLP (NIH NIGMS R01GM114355; funded 2016-2025), in which we are designing machine learning algorithms that leverage large collections of text to improve information extraction tasks such as mapping text to ontologies and discovering links between health events.
• Temporal Relation Discovery for Clinical Text (NIH NLM R01LM010090; funded 2010-2023), in which we were designing machine learning algorithms to extract timelines from clinical text and integrate those with structured data from the electronic medical record.
• Using Natural Language Processing to Determine Predictors of Healthy Diet and Physical Activity Behavior Change in Ovarian Cancer Survivors (NIH NCI R21CA256680; funded 2021-2022), in which we were designing machine-learning algorithms to analyze conversations in behavioral interventions, with the goal of improving patient outcomes by improving how patients are coached.
• A Data Science Platform and Mechanisms for Its Sustainability (NSF SMA RIDIR 1831551; funded 2018-2022), in which we were designing information extraction algorithms to make it easier to search 50 years of environmental policy documents.
• Global Reading and Assembly for Semantic, Probabilistic World Models (DARPA W911NF-18-1-0014; funded 2017-2022), in which we were designing machine learning algorithms to infer from text the times and locations over which a causal relation is valid, with the goal of modeling complex interactions in domains like food security.
• Voice Assistant for Data Entry and Recording (VADER; USAF SBIR FA8649-21-P-0834; funded 2021-2022), in which we were designing speech-to-text algorithms to assist aircraft maintainers in logging their activities.
• Automated Domain Adaptation for Clinical Natural Language Processing (NIH NLM R01LM012918; funded 2018-2021), in which we were designing algorithms that can improve machine learning models trained in one medical institution with data from another institution without any need for sharing of patient data.