Mingming Gong
Mingming Gong
University of Melbourne
Names
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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.
****@pitt.edu
, ****@gmail.com
, ****@unimelb.edu.au
Personal Links
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Education & Career History
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Assistant Professor
University of Melbourne (unimelb.edu.au)
2019 – 2023
Postdoc
University of Pittsburgh (pitt.edu)
2017 – 2019
Postdoc
Carnegie Mellon University (cmu.edu)
2017 – 2019
PhD student
University of Technology Sydney (uts.edu.au)
2012 – 2017
Advisors, Relations & Conflicts
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Postdoc Advisor
Kayhan Batmanghelich
****@pitt.edu
2017 – 2019
PhD Advisor
Dacheng Tao
****@sydney.edu.au
2012 – 2017
Postdoc Advisor
Kun Zhang
****@cmu.edu
2012 – 2017
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
causal learning and reasoning
2016 – 2022
domain adaptation/generalization
2015 – 2022
computer vision
2013 – 2022