I joined the University of Arizona School of Information in August 2016, after three years as an assistant professor in Computer and Information Science at the University of Alabama at Birmingham. I previously worked as a postdoctoral researcher at Stanford University's Natural Language Processing group, Johns Hopkins University's Human Language Technology Center of Excellence, KULeuven's Language Intelligence and Information Retrieval group in Belgium, and the University of Colorado's Center for Language and Education Research.
My research interests include natural language processing and machine learning theory and applications, including modeling the language of time and timelines, normalizing text to medical and geospatial ontologies, and information extraction models for clinical applications. There is a large community at the University of Arizona pursuing similar natural language processing research. Visit us at: http://nlp.arizona.edu/.
My ongoing funded projects include:
- Temporal Relation Discovery for Clinical Text (NIH NLM R01LM010090), in which we are designing machine learning algorithms to extract timelines from clinical text and integrate those with structured data from the electronic medical record.
- Extended Methods and Software Development for Health NLP (NIH NIGMS R01GM114355), 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.
- Automated Domain Adaptation for Clinical Natural Language Processing (NIH NLM R01LM012918), in which we are 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.
- Global Reading and Assembly for Semantic, Probabilistic World Models (DARPA W911NF-18-1-0014), in which we are 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.
- A Data Science Platform and Mechanisms for Its Sustainability (NSF SMA RIDIR 1831551), in which we are designing information extraction algorithms to make it easier to search environmental impact statements.
- Using Natural Language Processing to Determine Predictors of Healthy Diet and Physical Activity Behavior Change in Ovarian Cancer Survivors (NIH NCI R21CA256680), in which we are designing machine-learning algorithms to analyze conversations in behavioral interventions, with the goal of improving patient outcomes by improving how patients are coached.
Prospective students
I am not currently looking for any additional PhD students.
If you are already a student at the University of Arizona, I accept some undergraduate and graduate students for semester-long directed research projects. I prefer students who have taken ISTA 457/INFO 557 (Neural Networks) and/or ISTA 439/INFO 539 (Statistical Natural Language Processing). I also occasionally have pure linguistics or pure programming projects that do not require these courses. If you are interested in discussing research possibilities with me, please email me your experience and interests.