LabCompass

S M Nahid Mahmud

Computer Science · Purdue University West Lafayette

Early career · publishing since 2020

Publications

14

Citations

73

Est. group size

Recurring co-author estimate

Active years

7

Publishing since 2020

Research summary
AI-generated

S M Nahid Mahmud works on control theory and reinforcement learning, focusing on designing methods that let automated systems learn optimal control strategies while guaranteeing safety and stability, even when a system's dynamics are uncertain or only partially observed. This research is relevant to robotics and other engineered systems where both performance and safety constraints must be maintained during learning and operation.

Safe reinforcement learningAdaptive and optimal controlModel-based control under uncertaintyOutput-feedback control systemsInverse reinforcement learning

Publication output rose from none before 2020 to a peak around 2021, then gradually declined through 2024-2025 with an isolated 2026 entry, suggesting a slowing pace over the past few years.

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

Publication cadence
Publications per year over the last 10 years — averaging 1.4/year recently
1718192020: 3 publications202021: 4 publications4212022: 3 publications222023: 2 publications232024: 1 publication24252026: 1 publication26
Recent publications
Publishes in
  • arXiv (Cornell University)×4
  • Automatica×1
  • Frontiers in Robotics and AI×1
  • International Journal of Robust and Nonlinear Control×1
  • SHAREOK (University of Oklahoma)×1
Similar researchers
By research-topic overlap
  • Avimanyu Sahoo

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  • Jiayu Chen

    Computer Science · Purdue University West Lafayette

  • Tengyu Xu

    Computer Science · The Ohio State University

  • Zaiwei Chen

    Computer Science · Purdue University West Lafayette

  • Washim Uddin Mondal

    Computer Science · Purdue University West Lafayette

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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