Main profile

Hal

Daume III

Associate Professor

Interests: 

Computational Linguistics

Natural Language Processing, Machine Learning

Units: 

Computer Science, UMIACS

Degree(s): 

Ph.D., 2006, Computer Science, University of Southern California
M.S., 2003, Computer Science, University of Southern California
B.S., 2001, Mathematical Sciences, Carnegie Mellon University

Contact: 

hal3@umd.edu

301-405-1073

3227 AV Williams

Role(s): 

Faculty

Website: 

Google Scholar Profile

Personal Website

About: 

A professor named Hal Daumé III. He wields appointments in Computer Science and Language Science at UMD; he is currently on leave from UMD, spending time in the machine learning and fairness groups at Microsoft Research NYC. He and his wonderful advisees study questions related to how to get machines to becomes more adept at human language, 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 language
        through natural interaction with people/users?

and (2) how can we do this in a way that promotes fairness,
        transparency and explainability in the learned models?

He's discussed interactive learning informally recently in a Talking Machines Podcost and more technically in recent talks; and has discussed fairness/bias in broad terms in a recent blog post. Hal is committed to promoting an inclusive scientific environment; if you are thinking of inviting him for a talk or to participate in an event, please ensure that the event is consistent with this goal (see the first question on the FAQ).

Hal is super fortunate to have awesome colleagues in the Computional Linguistics and Information Processing Lab (which he currently directs). He maintains the structured prediction framework in VW. If you want to contact him, email is your best bet; you can also find him on @haldaume3 on Twitter. Or, in person, in the CLIP lab (AVW 3126) or his office (AVW 3227). If you're a prospective grad student or grad applicant, please read his FAQ!

Collaborators: 

Philip Resnik
Doug Oard
Jimmy Lin
Jordan Boyd-Graber
Samir Khuller