Julian McAuley

University of California, San Diego, University of California, San Diego

Names

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

Julian McAuley (Preferred)
,
Julian Mcauley
,
Julian John McAuley

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.ucsd.edu
,
****@eng.ucsd.edu
,
****@gmail.com
,
****@ucsd.edu
,
****@cse.ucsd.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.

Full Professor
University of California, San Diego, University of California, San Diego (eng.ucsd.edu)
2021Present
 
Associate Professor
University of California, San Diego, University of California, San Diego (eng.ucsd.edu)
20192021
 
Assistant Professor
University of California, San Diego, University of California, San Diego (eng.ucsd.edu)
20142019
 

Advisors, Relations & Conflicts

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

Coauthor
Zhen Zhang
****@comp.nus.edu.sg
2016Present
 
Coauthor
Serge Belongie
****@cs.ucsd.edu
20152015
 
Coauthor
Rogerio Feris
****@us.ibm.com
20112015
 
Coauthor
Tiberio Caetano
****@nicta.com.au
20112014
 
Coauthor
Pedro Felzenszwalb
****@brown.edu
20112014
 
Coauthor
Tong Zhao
****@stu.xmu.edu.cn
20112014
 
Coauthor
Matthew Turk
****@cs.ucsb.edu
20092009
 
Coauthor
Longbin Chen
****@houzz.com
20092009
 
Advisor
Teofilo Emidio de Campos
****@st-annes.oxon.org
20092009
 

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

Recommender Systems
Present