Daniel Lowd

University of Oregon

Names

How do you usually write your name as author of a paper? Also add any other names you have authored papers under.

Daniel Lowd

Emails

Enter email addresses associated with all of your current and historical institutional affiliations, as well as all your previous publications, and the Toronto Paper Matching System. This information is crucial for deduplicating users, and ensuring you see your reviewing assignments.

****@cs.uoregon.edu

Education & Career History

Enter your education and career history. The institution domain is used for conflict of interest detection and institution ranking. For ongoing positions, leave the end field blank.

Associate Professor
University of Oregon (uoregon.edu)
2017Present
 
Assistant Professor
University of Oregon (uoregon.edu)
20092017
 
PhD student
University of Washington (washington.edu)
20032009
 
Undergrad student
Harvey Mudd College (hmc.edu)
19992003
 

Advisors, Relations & Conflicts

Enter all advisors, co-workers, and other people that should be included when detecting conflicts of interest.

Coworker
Vibhav Gogate
****@hlt.utdallas.edu
2013Present
 
Coworker
Jesse Davis
****@cs.kuleuven.be
2009Present
 
PhD Advisee
Javid Ebrahimi
****@gmail.com
20152018
 
PhD Advisee
Amirmohammad Rooshenas
****@cs.umass.edu
20122017
 
PhD Advisee
MohammadAli Torkamani
****@amazon.com
20112016
 
PhD Advisor
Pedro Domingos
****@cs.washington.edu
20032009
 

Expertise

For each line, enter comma-separated keyphrases representing an intersection of your interests. Think of each line as a query for papers in which you would have expertise and interest. For example: deep learning, RNNs, dependency parsing

tractable probabilistic models, arithmetic circuits, sum-product networks
2008Present
 
statistical relational learning, Markov logic, relational models, statistical relational AI
2005Present
 
adversarial machine learning, adversarial examples, security of machine learning, machine learning vulnerabilities
2004Present
 
probabilistic graphical models, Bayesian networks, Markov networks, dependency networks, structure learning
2003Present