Naomi Feldman

Naomi Feldman is a Professor at the University of Maryland with dual affiliations in the Department of Linguistics and the University of Maryland Institute for Advanced Computer Studies (UMIACS). She is also affiliated with the Department of Computer Science, the Program in Neuroscience and Cognitive Science, and the Computational Linguistics and Information Processing (CLIP) Lab.

Her research focuses on computational psycholinguistics, applying methods from statistics, machine learning, and automatic speech recognition to model cognitive processes underlying speech perception, phonetic learning, and language acquisition. Key areas include understanding how humans learn language structure in complex environments and developing computational strategies to assist language learners and clinicians.

• Research combines infant phonetic learning with neural network modeling
• Investigates cross-linguistic speech recognition and selective attention mechanisms
• Explores language discrimination, developmental language disorders, and computational models of aphasia

Her recent publications (2022-2025) cover topics such as reward-based language learning, rhythm analysis in speech, self-supervised speech representations, and argument role sensitivity in language models. These works have received recognition like the Computational Modeling Prize in Perception & Action and Best Paper Award Honorable Mention.

Naomi actively advises students across three graduate programs: Linguistics, Neuroscience and Cognitive Science (NACS), and Computer Science. Her research team includes postdocs, PhD candidates, and undergraduate collaborators. She has received grants including an NIH Pilot Grant to assist children with specific language impairment.

She is a core member of the university's interdisciplinary Language Science community and participates in projects crossing multiple departments. Her lab maintains open-source code repositories for research reproducibility.