Email:	jmielens@utexas.edu
CV:	[pdf]
LinkedIn:	linkedin.com/in/mielens
Github:	github.com/jmielens

About

My academic research focuses on techniques for effectively using low-resource languages in Natural Language Processing, with particular interests in parsing morphologically-rich languages and unsupervised or semi-supervised parsing methods. My dissertation research focuses on the properties of imperfect data like quickly collected corpora or partial annotations, and the consequences for low-data scenarios.

I was previously part of the UW-Madison Laryngeal Physiology Laboratory, where I focused on the quantification and analysis of dysphagia.

Publications

Computational Linguistics

Parse Imputation for Dependency Annotations

Parsing Low-Resource Languages Using Gibbs Sampling for PCFGs with Latent Annotations

Real-World Semi-Supervised Learning of POS-Taggers for Low-Resource Languages

Dysphagia

Evaluating the Tongue-Hold Maneuver Using High-Resolution Manometry and Electromyography

Detection of Chronic Laryngitis due to Laryngopharyngeal Reflux Using Color and Texture Analysis of Laryngoscopic Images

ANN Classification of Pharyngeal High-Resolution Manometry with Impedance Data

Application of Classification Models to Pharyngeal High-Resolution Manometry

High-Resolution Manometry of Pharyngeal Swallow Pressure Events Associated with Effortful Swallow and the Mendelsohn Maneuver

Automated Analysis of Pharyngeal Pressure data Obtained with High-Resolution Manometry

Pharyngeal swallow adaptations to Bolus Volume Measured with High-Resolution Manometry

Groups

UT-Austin Computational Linguistics Lab
UW-Madison Laryngeal Physiology Laboratory