qiang liu (Preferred)
, Qiang Liu
qiang liu
University of Texas, Austin
Names
How do you usually write your name as author of a paper? Also add any other names you have authored papers under.
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.dartmouth.edu
, ****@dartmouth.edu
, ****@gmail.com
, ****@cs.utexas.edu
, ****@cs.utexas.edu
Personal Links
Add links to your profiles on other sites. (Optional)
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.
Assistant Professor
University of Texas, Austin (utexas.edu)
2018 – Present
Assistant Professor
Dartmouth College (dartmouth.edu)
2015 – 2018
Postdoc
Massachusetts Institute of Technology (mit.edu)
2014 – 2015
PhD student
University of California, Irvine (uci.edu)
2008 – 2014
Advisors, Relations & Conflicts
Enter all advisors, co-workers, and other people that should be included when detecting conflicts of interest.
Coworker
Jian Peng
****@illinois.edu
2018 – Present
coworker
Jason lee
****@gmail.com
2018 – Present
coworker
dengyoung Zhou
****@google.com
2018 – Present
coworker
Lihong li
****@google.com
2018 – Present
Coworker
Dengyong Zhou
****@google.com
2018 – 2018
Coworker
Lihong li
****@google.com
2018 – 2018
Coworker
jiang peng
****@illinois.edu
2018 – 2018
Coworker
Jason lee
****@marshall.usc.edu
2018 – 2018
Postdoc Advisor
John Fisher III
****@csail.mit.edu
2015 – 2015
PhD Advisor
Alexander Ihler
****@ics.uci.edu
2011 – 2014
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
machine learning
Present
reinforcement learning, off-policy evaluation
Present
deep learning
Present
approximate inference, variational inference, MCMC, probabilistic inference, bayesian inference, langevin dynamics, Monte Carlo, importance sampling, Stein variational
2014 – Present
variational inference, approximate inference, MCMC, Monte Carlo, graphical models, Stein's method
2010 – 2018