Nate Chambers
Professor, Department of Computer Science
Co-Director, Center for High Performance Computing
(Publishes as Nathanael Chambers)
Recent Developments
New paper on Event Reasoning at ACL-25
Winner of the 2020 Faculty Award for Excellence in Research at USNA
Best Paper Award: WNUT Wkshp
Finalist for ACL19 Test-of-Time Award (10 year)
Teaching
| Spring 2026: | SI420, Artificial Intelligence |
| SI448, Capstone Seminar | |
| Fall 2025: | SI425, Natural Language Processing |
| Spring 2025: | SD212, Data Science 2 |
| Fall 2024: | SI425, Natural Language Processing |
| Spring 2023: | SI425, Natural Language Processing |
| Fall 2022: | SD211, Intro to Data Science |
| Spring 2022: | SI268, Programming for Everyone |
| Fall 2021: | SI425, Natural Language Processing |
| IT350, Web & Internet Programming | |
| Spring 2021: | SI286, Programming for Everyone |
| Fall 2020: | SI425, Natural Language Processing |
| Spring 2020: | SI286, Programming for Everyone |
| Fall 2019: | IC210, Intro to Computing |
| Spring 2019: | IC211, Object-Oriented Programming |
| (previous semesters 2011-2018) | |
Research Interests
I research natural language processing (NLP) and learning about the world from text with minimal supervision. I apply modern NLP and machine learning techniques to learn how events and people interact. Most recently this involves researching Large Language Models for event understanding, reasoning, and inference. I am also interested in information extraction to help people better understand large amounts of text.
Student Collaboration
I am always open to advising undergraduate research. Come talk to me if you're interested. Topics ranging from social media like Twitter to intelligent systems that read the news are ripe for study.
Education
Ph.D., Computer Science, Stanford University, 2011
M.S., Computer Science, University of Rochester, 2003
B.S., Computer Science, University of Rochester, 2002
Selected Publications (view all 62 with downloads)
Causal Graph based Event Reasoning using Semantic Relation Experts | ACL 2025 |
CaT-Bench: Benchmarking Language Model Understanding of Causal and Temporal Dependencies in Plans | EMNLP 2024 |
Using Commonsense Knowledge to Answer Why-Questions | EMNLP 2022 |
TellMeWhy: A Dataset for Answering Why-Questions in Narratives | ACL 2021 |
Character-Based Models for Adversarial Phone Number Extraction: Preventing Human Sex Trafficking | WNUT 2019 |
Event Representations with Tensor-based Compositions | AAAI 2018 |
A Corpus and Cloze Evaluation for Deeper Understanding of Commonsense Stories | NAACL 2016 |
Identifying Political Sentiment between Nation States with Social Media | EMNLP 2015 |
Dense Event Ordering with a Multi-Pass Architecture | TACL 2014 |
Template-Based Information Extraction without the Templates | ACL 2011 |
A Multi-Pass Sieve for Coreference Resolution | EMNLP 2010 |
Unsupervised Learning of Narrative Schemas and their Participants | ACL 2009 |
Data
Nation-Nation Sentiment Data and Visualization
Narrative Cloze Evaluation (Gigaword Corpus NYT labeled)