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Hal Daumé III is a Perotto Professor in Computer Science at the University of Maryland, College Park; he also spends time at Microsoft Research, New York City. He holds joint appointments in UMIACS and Language Science. He was previously an assistant professor in the School of Computing at the University of Utah. His primary research interest is in developing new learning algorithms for prototypical problems that arise in the context of natural language processing and artificial intelligence, with a focus on interactive learning and building systems that minimize social harms. He has received several awards, including best paper at ACL 2018, NAACL 2016, CEAS 2011 and ECML 2009, as well as best demo at NeurIPS 2015. He has been program chair for NAACL 2013 (and chair of its executive board), and ICML 2020; he was an inaugural diversity and inclusion co-chair at NeurIPS 2018. He earned his PhD at the University of Southern California with a thesis on structured prediction for language (his advisor was Daniel Marcu). When not sciencing, he spends most of his time working on the six limbs of yoga, cooking vegan food, and enjoying the outdoors (climbing, backpacking, skiing, etc.).

(You may cut the last one or two sentences for a more formal bio.)

Contact Information:

Hal Daumé III
Computer Science
University of Maryland
Iribe Center #4150
College Park, MD 20742

(o) 301-405-1073
(email) me _AT_ hal3 _DOT_ name
(skype) haldaume3
(twitter) @haldaume3

Representative Publications:

Help, Anna! Visual Navigation with Natural Multimodal Assistance via Retrospective Curiosity-Encouraging Imitation Learning
Khanh Nguyen and Hal Daumé III
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019
[Abstract] [BibTeX] [Code/Data]

Reinforcement Learning with Convex Constraints
Sobhan Miryoosefi, Kianté Brantley, Hal Daumé III, Miroslav Dudík and Robert Schapire
NeurIPS, 2019
[Abstract] [BibTeX]

Improving fairness in machine learning systems: What do industry practitioners need?
Kenneth Holstein, Jennifer Wortman Vaughan, Hal Daumé III, Miroslav Dudík and Hanna Wallach
CHI, 2019
[Abstract] [BibTeX]

Learning to Ask Good Questions: Ranking Clarification Questions using Neural Expected Value of Perfect Information
Sudha Rao and Hal Daumé III
Conference of the Association for Computational Linguistics (ACL), 2018
🏆 Best Paper Award
[Abstract] [BibTeX]

Datasheets for Datasets
Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé III and Kate Crawford
arxiv, 2018
[Abstract] [BibTeX]

Interpretese vs. Translationese: The Uniqueness of Human Strategies in Simultaneous Interpretation
He He, Jordan Boyd-Graber and Hal Daumé III
Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2016
[Abstract] [BibTeX]

Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback
Khanh Nguyen, Hal Daumé III and Jordan Boyd-Graber
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2017
[Abstract] [BibTeX]

Learning to search better than your teacher
Kai-Wei Chang, Akshay Krishnamurthy, Alekh Agarwal, Hal Daumé III and John Langford
International Conference on Machine Learning (ICML), 2015
[Abstract] [BibTeX]

credits: design and font inspired by Seth Able's LoRD, some images converted to ANSI using ManyTools, original drawing of me by anonymous.
last updated on thirty august, two thousand twenty one.