LabCompass

Taeuk Jang

Social Sciences · Purdue University West Lafayette

OpenAlex
Mid career · publishing since 2006Rising activity
Ethics and Social Impacts of AIMultimodal Machine Learning ApplicationsPrivacy-Preserving Technologies in DataNatural Language Processing TechniquesAdversarial Robustness in Machine Learning

Publications

11

Citations

84

Est. group size

—

Recurring co-author estimate

Active years

20

Publishing since 2006

Research summary
AI-generated

Taeuk Jang works on making machine learning systems fairer and less biased, particularly in vision-language models (systems that connect images and text) and other AI applications. Their research develops methods to detect and reduce unwanted bias related to sensitive attributes, while also touching on data privacy and robustness against adversarial attacks. This work is relevant to students interested in the ethical and technical challenges of building trustworthy AI systems.

Fairness and bias mitigation in machine learningVision-language modelsAdversarial and robust AI methodsPrivacy-preserving data techniquesRepresentation learning

Publication output has grown since 2021, with activity increasing notably in 2024 after a slower period in earlier years of the decade.

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

Publication cadence
Publications per year over the last 10 years — averaging 1.6/year recently
171819202021: 2 publications212022: 2 publications222023: 1 publication232024: 4 publications4242025: 1 publication2526
Recent publications
Publishes in
  • Proceedings of the AAAI Conference on Artificial Intelligence×3
  • arXiv (Cornell University)×2
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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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