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Phornsawan Roemsri (MinMin)

Lubbock, TX 79409 | phornsawan.roemsri@ttu.edu | https://www.linkedin.com/in/phornsawan-roemsri/ | https://github.com/pyppr | https://phornsawan-roemsri.com

SUMMARY

Computer Science Ph.D. candidate (defense Oct. 2026) with eight first-author peer-reviewed publications in cybersecurity and data visualization. Builds end-to-end systems: network traffic classification and anomaly detection, HPC monitoring and job-outcome prediction, and interactive visual analytics in D3.js and React. Combines research depth with full-stack delivery in Python, TypeScript, and SQL.

Work authorization: F-1 student visa — eligible for 12-month OPT on graduation plus the 24-month STEM OPT extension; no employer sponsorship required for the first three years of employment.

EDUCATION

Texas Tech University, Lubbock, TX — Expected Dec. 2026

Doctor of Philosophy, Computer Science

Dissertation: Data-Driven Cybersecurity for Connected Devices: Traffic, Provenance, and Behavioral Threat Detection

Advisor: Susan A. Mengel, Ph.D.

GPA: 3.95

Mahidol University, Bangkok, Thailand — 2019

Bachelor of Engineering, Computer Engineering

GPA: 3.90

TECHNICAL SKILLS

Python | JavaScript | TypeScript | R | SQL | HTML/CSS | D3.js | React | Next.js | MySQL | Linux | Git | Slurm/HPC | Machine learning | Data visualization | Network traffic analysis | Microsoft Office

RESEARCH AND TECHNICAL EXPERIENCE

Graduate Research / Teaching Assistant, Texas Tech University, Lubbock, TX — 2020 – Present

  • Built the monitoring and visual analytics web application for the REPACSS HPC cluster — full cluster coverage, 110 CPU and 8 GPU nodes — ingesting Slurm job state, node telemetry, and power draw for job-outcome prediction and operational forensics; traced a cluster-wide thermal incident back to the single user account whose jobs caused it.
  • Developed a JWST NIRCam photometry and frame-quality pipeline (program PID 1666) that flags degraded frames automatically, producing eclipse-timing measurements for an astronomy collaboration and a published conference paper.
  • Delivered the rigid pavement technical support platform for TxDOT Research Project 0-7147 (Phase III), rebuilding the TxCRCP-ME design engine from a legacy Electron/Excel system into a Next.js application with interactive dashboards and geospatial performance analytics.
  • Designed interactive visual analytics tools in D3.js and React for IoT attack-behavior data, letting analysts trace multi-stage attack sequences that summary statistics obscured.
  • Engineered passive traffic-fingerprinting and behavioral detection methods for IoT device identification and crypto ransomware, published across four peer-reviewed conferences.

PUBLICATIONS

Eight first-author peer-reviewed publications; entries 7-8 are short papers.

  1. Roemsri, P., McCarver, A., Maccarone, T., Shaw, A. W., Gandhi, P., Kaplan, D., & Dang, T. (2026). A web-based interactive visualization tool for astronomical time series. AIP Conference Proceedings, 3378(1), 040001.
  2. Roemsri, P., Ribeiro, A. H., & Dang, T. (2025). PowerMap and time-indexed PCA trajectories: Interactive visual forensics for HPC incidents. Int. Conf. in Cybersecurity, IoT, Data Science, and Digital Forensics (CIDDF). Springer. https://doi.org/10.1007/978-3-032-19488-6_12
  3. Roemsri, P., & Dang, T. (2023). Visualization of attack behavior data in IoT network traffic. Int. Conf. on Big-Data Service and Intelligent Computation (BDSIC), 1-8.
  4. Roemsri, P., Puangpontip, S., & Hewett, R. (2023). On detecting crypto ransomware attacks: Can simple strategies be effective? Int. Conf. on Information and Computer Technologies (ICICT), 138-143. https://doi.org/10.1109/ICICT58900.2023.00030
  5. Roemsri, P., & Hewett, R. (2021). Device identification for IoT security. IEEE Int. Conf. on Signal and Image Processing (ICSIP), 866-870.
  6. Roemsri, P., & Hewett, R. (2020). Provenance location-based authentication in cloud computing. Int. Conf. on Advances in Information Technology (IAIT), Article 24, 1-8. https://doi.org/10.1145/3406601.3406629
  7. Roemsri, P., & Dang, T. (2023). An interactive multi-degree analysis approach. IEEE VAST Challenge, 9-10.
  8. Roemsri, P., & Dang, T. (2023). Effective dynamic network layout for transaction analysis. IEEE VAST Challenge, 7-8.

PROJECTS

JobNet — HPC cluster monitoring dashboard

  • Next.js and React dashboard visualizing Slurm cluster state, job flow, and node metrics, including a radial network view of job-to-node allocation.

SOJ guild management system

  • Full-stack roster, attendance, and event-scheduling system serving an active user community, with Thai-language data handling end to end.

AWARDS AND ACTIVITIES

  • Best Presentation, Session 3 — 2025 4th Asia-Pacific Computer Technologies Conference (APCT 2025), Bangkok, Thailand, Jan. 2025.
  • The Engineering Student Talent Award, first runner-up — Jun. 2017. Selected to one of the teams representing Thailand at the ASEAN programme in India.

LANGUAGES

Thai (native) | English (professional working proficiency)