Beihang University
Jun ZhuDirector · Tsinghua UniversityResearcher↗
Researcher · Academic
Gao Huang
Tsinghua UniversityAssociate Professor
Huang co-created DenseNet, an architecture whose layers reuse features from every earlier layer, improving accuracy and efficiency while making very deep vision models easier to train.[1] At Tsinghua he develops dynamic networks that adapt their computation to each input.
Career & education
Current roleTsinghua University2021-presentAssociate Professor
Tsinghua University2021-presentPreviouslyTsinghua University2018-2021Assistant Professor
Cornell University2015-2018Postdoc
Tsinghua University2018-2021Cornell University2015-2018Work and education history is primarily focused on AI-relevant roles and may not be comprehensive.
Citation Trend
Total citations to scholarly work, including research papers, technical reports, books and theses, as recorded by Google Scholar. Each point is a dated snapshot.
citations117,264As of Nov 1, '26
citations+2,540Since last snapshot, Oct 1, '26
References
- Densely Connected Convolutional Networksarxiv.org
Original DenseNet paper verifies Gao Huang co-authorship, feature reuse across layers, improved training and parameter/computational efficiency.
Based on public sources. If accuracy is important, verify details using the links or references.
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Reviewed August 10, 2026 · Checked for accuracy and new information.
