Faculty

CSE2 313
althoffcs.washington.edu
Data Science, Data Mining, Social Network Analysis, Natural Language Processing
CSE328
Adjunct, Linguistics

Computational linguistics (especially grammar engineering and NLP), syntax and study of variation.

EEB-418
bilmescs.washington.edu
Adjunct, Electrical & Computer Engineering

Machine learning, speech/language/bioinformatics/music, submodularity & discrete optimization

aylinuw.edu
Adjunct, Information School
Artificial intelligence, AI ethics, algorithmic bias, computational social science, computer vision, data science, machine learning, natural language processing
CSE 578
yejincs.washington.edu
Natural language processing
CSE 470
hannanehcs.washington.edu
Natural Language Processing, Artificial Intelligence, Machine Learning
pangweics.washington.edu
Techniques and theory for building reliable and interactive machine learning systems
ranjaycs.washington.edu
Development of new representations, models, and training paradigms for machine learning and computer vision, drawing on insights from human-computer interaction, social, and behavioral sciences
msaveskiuw.edu
Adjunct, Information School
Computational social science, social networks, causal inference, data mining
nasmithcs.washington.edu
Natural language processing
CSE 566
yuliatscs.washington.edu
Natural language processing
lucylwuw.edu
Adjunct, Information School
Health informatics, natural language processing, data science
swangcs.washington.edu
Computational biology — learning in the open-world setting, biomedical natural language processing, network biology

Postdocs

goosehecs.washington.edu

Tianxing He works with Yulia Tsvetkov on natural language generation. He works towards a better understanding of how the current large language models work. Related, he is interested in monitoring and detecting different behaviors of language models under different scenarios, and approaches to fix undesirable behaviors.

niloofarcs.washington.edu

Fatemehsadat Mireshghallah works with Allen School professors Yejin Choi and Yulia Tsvetkov. Her research interests are Trustworthy Machine Learning and Natural Language Processing. She is a recipient of the National Center for Women & IT (NCWIT) Collegiate award in 2020, a finalist of the Qualcomm Innovation Fellowship in 2021 and a recipient of the 2022 Rising star in Adversarial ML award. She received her Ph.D. from the CSE department of UC San Diego in 2023.

Collaborators

338
royschcs.washington.edu