LabCompass

Qingyi Gao

Computer Science · Purdue University West Lafayette

OpenAlex
Mid career · publishing since 2011
Anomaly Detection Techniques and ApplicationsGenerative Adversarial Networks and Image SynthesisAdversarial Robustness in Machine LearningNeural Networks and ApplicationsModel Reduction and Neural Networks

Publications

16

Citations

70

Est. group size

—

Recurring co-author estimate

Active years

14

Publishing since 2011

Research summary
AI-generated

Qingyi Gao's research focuses on the statistical and theoretical foundations of generative adversarial networks (GANs), a type of machine learning model used to generate realistic synthetic data such as images. This work includes developing improved GAN variants, studying how well these models generalize to new data, and applying deep neural networks to problems like variable selection (identifying which input features matter most) and adversarial robustness (making models resistant to intentionally misleading inputs).

Generative adversarial networks (GANs)Statistical theory for deep learningAdversarial robustnessNeural network generalization boundsVariable selection with neural networks

Publication output has been modest and uneven over the past decade, with bursts of activity in 2019-2021 and 2024 separated by gaps, rather than steady or clearly growing output.

Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026

Publication cadence
Publications per year over the last 10 years — averaging 0.8/year recently
17182019: 4 publications4192020: 3 publications202021: 4 publications421222023: 1 publication232024: 3 publications242526
Recent publications
Publishes in
  • Figshare×2
  • Journal of Computational and Graphical Statistics×1
  • Journal of the Royal Statistical Society Series B (Statistical Methodology)×1
  • Transportation Research Record Journal of the Transportation Research Board×1
  • Journal of the American Statistical Association×1
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This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.

Last updated Jul 20, 2026.

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