LabCompass

Di Tang

Computer Science · Indiana University

OpenAlex ORCID
Adversarial Robustness in Machine LearningSecurity in Wireless Sensor NetworksMobile Ad Hoc NetworksEnergy Efficient Wireless Sensor NetworksNetwork Security and Intrusion Detection

Publications

52

Citations

604

Est. group size

—

Recurring co-author estimate

Active years

19

Publishing since 2008

Research summary
AI-generated

Di Tang works in computer science with a focus on security topics, ranging from the robustness of machine learning systems (such as attacks and defenses for large language models and image models) to the security and privacy of networked devices like wireless sensor networks and Internet-of-Things systems. Recent work also spans anomaly detection for critical infrastructure and, in a separate line, studies on esports participation and health. The research combines building attacks/defenses for AI systems with protecting connected devices and detecting malicious behavior.

Adversarial attacks and defenses for machine learningSecurity of large language models and AI systemsWireless sensor network and IoT securityAnomaly and malicious-behavior detectionPrivacy in networked/edge systems

Publication activity has been variable over the past decade, with peaks around 2019 and 2022 and a recent uptick in 2025, averaging about four papers per year over the last five years.

Generated by claude-opus-4-8 from public bibliographic data · Jul 11, 2026

Publication cadence
Publications per year over the last 10 years — averaging 4.0/year recently
2017: 2 publications172018: 5 publications182019: 7 publications7192020: 3 publications202021: 2 publications212022: 7 publications7222023: 3 publications232024: 3 publications242025: 6 publications252026: 1 publication26
Recent publications
Publishes in
  • arXiv (Cornell University)×10
  • Heliyon×1
  • Humanities and Social Sciences Communications×1
  • Sustainability×1
  • Water×1

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 11, 2026.

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