Phornsawan "Minmin" Roemsri

Lubbock, TX 79409 | phornsawan.roemsri@ttu.edu

Education

Doctor of Philosophy, Computer Science, Texas Tech University, Lubbock, TX — Jan. 2020 – Dec. 2026 (expected)

  • Dissertation: Data-Driven Cybersecurity for Connected Devices: Traffic, Provenance, and Behavioral Threat Detection
  • Advisor and Committee Chair: Susan A. Mengel, Ph.D.
  • Committee: Bashir Morshed, Ph.D.; Yu Zhuang, Ph.D.; Victor Sheng, Ph.D.; Thomas Maccarone, Ph.D. (Dean's Representative, Physics & Astronomy)
  • Defense: October 2026

Research Interests

Cybersecurity for connected and IoT devices — passive traffic fingerprinting for device identification, provenance-based authentication, and behavioral detection of ransomware. Data and information visualization — visual analytics for network attack behavior, HPC operational and incident forensics, and astronomical time-series data. Current work centers on matching detection mechanisms to the cost structure of the problem rather than defaulting to model complexity, and on making detection results interpretable to the analyst who must act on them.

Research Experience

Graduate Research Assistant, Department of Computer Science, Texas Tech University, Lubbock, TX

  • Built a monitoring and visual analytics pipeline for the REPACSS HPC cluster, integrating Slurm job state, node telemetry, and power data for operational analysis and job-outcome prediction.
  • Developed a JWST NIRCam photometry and frame-quality pipeline for the eclipsing binary ZTF J153932.16+502738.8 (PID 1666), producing eclipse-timing measurements for a Physics & Astronomy collaboration.
  • Designed visualization systems (D3.js, React) for IoT network attack behavior and multi-stage incident data.

Graduate Research Assistant, Texas Tech University, Lubbock, TX

  • Developed passive traffic-fingerprinting methods for IoT device identification.
  • Built and evaluated detection methods for crypto ransomware behavior.
  • Designed a provenance location-based authentication scheme for cloud computing.

Publications

Peer-reviewed conference papers — first author on all entries.

  1. Roemsri, P., & Dang, T. (2023). Visualization of attack behavior data in IoT network traffic. Proceedings of the International Conference on Big Data and Smart Information Computing (BDSIC).
  2. Roemsri, P., Puangpontip, S., & Hewett, R. (2023). On detecting crypto ransomware attacks. Proceedings of the International Conference on Information and Computer Technologies (ICICT).
  3. Roemsri, P., & Hewett, R. (2021). Device identification for IoT security. Proceedings of the International Conference on Signal and Image Processing (ICSIP).
  4. Roemsri, P., & Hewett, R. (2020). Provenance location-based authentication in cloud computing. Proceedings of the International Conference on Advances in Information Technology (IAIT).

In progress

  • Roemsri, P., Maccarone, T., et al. Manuscript in preparation, 2026.

Technical Skills

  • Languages: Python, JavaScript, TypeScript, R, SQL, HTML/CSS
  • Visualization: D3.js, React, Next.js
  • Data and systems: MySQL, Linux, Git, Slurm/HPC environments, Microsoft Office
  • Domains: network traffic analysis, machine learning for classification, astronomical photometry pipelines

Languages

  • Thai — native
  • English — professional working proficiency