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You enter a dark forest. Standing in front of you is:

A professor named Hal Daumé III (he/him). He wields appointments in Computer Science where he is a Perotto Professor, as well as Language Science at UMD (in Fall 2021 he is teaching Just Machine Learning); he is also a Senior Principal Researcher the machine learning and fairness groups at Microsoft Research NYC. He and his wonderful advisees like to study questions related to how to get machines to becomes more adept at human language (and artificial intelligence tasks more broadly), by developing models and algorithms that allow them to learn from data. (Keywords: natural language processing and machine learning.) The two major questions that really drive their research these days are:

    (1) how can we get computers to learn
        through natural interaction with people/users?

and (2) how can we do this in a way that minimize harms
        in the learned models?

He's discussed interactive learning informally in a Talking Machines Podcast and more technically in recent talks; and has discussed fairness/bias in broad terms in a (now somewhat outdated) blog post. He is the author of the online textbook A Course in Machine Learning, which is fully open source.

Hal is super fortunate to be a member of, and have awesome colleagues in the Computional Linguistics and Information Processing Lab (which he formerly directed), the Human-Computer Interaction Lab, and the Center for Machine Learning. If you want to contact him, email is your best bet; you can also find him on @haldaume3 on Twitter. Or, in person, in his office (IRB 4150).

If you're a prospective grad student or grad applicant, please read his FAQ to answer some common questions. If you're thinking of inviting him for a talk or event, please ensure that the event is organized in an inclusive manner (inclusion rider). More generally, if you are organizing a conference, workshop or other event, you may wish to read the NeurIPS D&I survey results (joint with Katherine Heller), Humberto Corona's collection of resources/advice, or two blog posts on this topic.

I acknowledge that I live and work on the ancestral and unceded lands of the Piscataway People, who were among the first in the Western Hemisphere to encounter European colonists, as well as the lands of the Lenape and Nacotchtank people.

Recent Publications:

From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence
David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna Wallach and Jennifer Wortman Vaughan
HCOMP, 2021
[Abstract] [BibTeX]

Analyzing Stereotypes in Generative Text Inference Tasks
Anna Sotnikova, Yang Trista Cao, Hal Daumé III and Rachel Rudinger
ACL (findings), 2021
[Abstract] [BibTeX]

Multi-Step Reasoning Over Unstructured Text with Beam Dense Retrieval
Chen Zhao, Chenyan Xiong, Jordan Boyd-Graber and Hal Daumé III
NAACL (short), 2021
[Abstract] [BibTeX]

Distantly-Supervised Evidence Retrieval Enables Question Answering without Annotated Evidence Pieces
Chen Zhao, Chenyan Xiong, Jordan Boyd-Graber and Hal Daumé III
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2021
[BibTeX]

Prior and Prejudice: The Novice Reviewers' Bias against Resubmissions in Conference Peer Review
Ivan Stelmakh, Nihar B. Shah, Aarti Singh and Hal Daumé III
CSCW, 2021
[Abstract] [BibTeX]

More papers please!

Recent Talks:

(Meta-)Learning from Interaction
NYU Machine Learning Reading Group 2019
[PDF] [ODP]

Out of Order! Flexible neural language generation
NAACL 2019 NeuralGen Workshop
[PPTx]

Beyond demonstrations: Learning behavior from higher-level supervision
ICML 2019 I3 Workshop
[PPTX]

Imitation Learning
Vector Institute Reinforcement Learning Summer School 2018
[PDF] [ODP]

Learning language through interaction
December 2016, Georgetown, Amazon, USC, GATech, UW, ...
[PDF] [ODP] [Video]

Bias in AI
November 2016, UMD MCWIC Diversity Summit
[PDF] [ODP] [PPTx (exported)] [Blog Post]

More talks please!

Contact information:
    email: me AT hal3 DOT name               skype: haldaume3
    phone: 301-405-1073                    twitter: haldaume3
   office: IRB 4150                         github: hal3
I can't reply to all prospective students email; please read this before emailing me.

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.