Shah Muhammad Hamdi
Shah Muhammad Hamdi

Assistant Professor of Computer Science

School of Computing, Utah State University

About Me

Shah Muhammad Hamdi is an Assistant Professor of Computer Science at Utah State University. His research develops machine learning techniques tailored to multivariate time series and graph data, with applications to the prediction and analysis of extreme solar events such as solar flares and solar energetic particles. He leads the design of ML-based cyberinfrastructure to integrate heterogeneous, large-scale scientific data and support reproducible forecasting workflows for the space weather community. Hamdi has secured over $1.3M in extramural funding, published more than 70 refereed papers, and was recognized as the Outstanding Computer Science Faculty Researcher of the Year in 2024.

Interests
  • Applied Machine Learning
  • Time Series and Graph Learning
  • Cyberinfrastructure for Science
  • AI for Earth and Space Sciences
Education

  • Ph.D., Computer Science (2020)

    Georgia State University

  • M.S., Computer Science (2020)

    Georgia State University

  • B.Sc., Computer Science & Engineering (2014)

    Rajshahi University of Engineering and Technology, Rajshahi, Bangladesh

Recent News
  • August 2025 — Congratulations to Reza on our IEEE ICDM 2025 paper.
  • August 2025 — Congratulations to Santosh on our ACM CIKM 2025 paper.
  • August 2025 — Congratulations to Peiyu and Pouya on our two IEEE DSAA 2025 papers.
  • July 2025 — We received the NSF CAIG grant Award #2530946!
  • December 2024 — Congratulations to Reza on our SIAM SDM 2025 paper.
  • December 2024 — Congratulations to Onur, Peiyu, Reza, and Pouya on four IEEE Big Data 2024 papers.
  • December 2024 — Congratulations to Khaznah, Pouya, and Omar on three ICPR 2024 papers.
  • October 2024 — Congratulations to Santosh on our IEEE DSAA 2024 paper.
  • May 2024 — Congratulations to Cory and Santosh on our AAAI ICWSM 2024 paper.
  • December 2023 — Congratulations to Omar, Peiyu, Cory, and Santosh on three IEEE Big Data 2023 papers.
  • February 2023 — I received the NSF SHINE grant Award #2301397!
  • December 2022 — Congratulations to Omar and Peiyu on two IEEE Big Data 2022 papers.
  • October 2022 — Congratulations to Soukaina on our ACM CIKM 2022 paper.
  • August 2022 — I started my Assistant Professor position at CS USU.
  • May 2022 — Congratulations to Cory on our AAAI ICWSM 2022 paper.
  • January 2022 — I received the NSF CRII award Award #2305781!
  • August 2020 — I started my Assistant Professor position at CS NMSU.
Featured Publications
MohammadReza EskandariNasab, Shah Muhammad Hamdi, Soukaina Filali Boubrahimi (2025). AVATAR: Adversarial Autoencoders with Autoregressive Refinement for Time Series Generation. Proceedings of the 2025 SIAM International Conference on Data Mining (SDM).
S. Chapagain, Shah Muhammad Hamdi, S. Filali Boubrahimi (2025). Pruning Strategies for Backdoor Defense in LLMs. Proceedings of the 34th ACM International Conference on Information and Knowledge Management (CIKM).
Onur Vural, Muhammad Hamdi Shah, Soukaina Filali Boubrahimi (2025). Solar Flare Prediction Using Multivariate Time Series of Photospheric Magnetic Field Parameters: A Comparative Analysis of Vector, Time Series, and Graph Data Representations. Remote Sensing.
M. EskandariNasab, Shah Muhammad Hamdi, S. Filali Boubrahimi (2025). TIMED: Adversarial and Autoregressive Refinement of Diffusion-Based Time Series Generation. Proceedings of the 2025 IEEE International Conference on Data Mining (ICDM).
MohammadReza EskandariNasab, Shah Muhammad Hamdi, Soukaina Filali Boubrahimi (2024). Impacts of data preprocessing and sampling techniques on solar flare prediction from multivariate time series data of photospheric magnetic field parameters. The Astrophysical Journal Supplement Series.
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Papers
Pouya Hosseinzadeh, Soukaina Filali Boubrahimi, Shah Muhammad Hamdi (2025). An End-to-end Ensemble Machine Learning Approach for Predicting High-impact Solar Energetic Particle Events Using Multimodal Data. The Astrophysical Journal Supplement Series.
MohammadReza EskandariNasab, Shah Muhammad Hamdi, Soukaina Filali Boubrahimi (2025). AVATAR: Adversarial Autoencoders with Autoregressive Refinement for Time Series Generation. Proceedings of the 2025 SIAM International Conference on Data Mining, SDM 2025, Alexandria, VA, USA, May 1-3, 2025.
URL DOI
MohammadReza EskandariNasab, Shah Muhammad Hamdi, Soukaina Filali Boubrahimi (2025). AVATAR: Adversarial Autoencoders with Autoregressive Refinement for Time Series Generation. Proceedings of the 2025 SIAM International Conference on Data Mining (SDM).
P. Hosseinzadeh, P. Li, O. Bahri, S. Filali Boubrahimi, Shah Muhammad Hamdi (2025). CACTUS: Cross-Aligned Counterfactual Explanation for Time Series Classification. Proceedings of the 2025 IEEE 12th International Conference on Data Science and Advanced Analytics (DSAA).
P. Li, O. Bahri, P. Hosseinzadeh, S. Filali Boubrahimi, Shah Muhammad Hamdi (2025). Diverse and Plausible Counterfactual Explanations for Time Series via Latent Space Optimization. Proceedings of the 2025 IEEE 12th International Conference on Data Science and Advanced Analytics (DSAA).
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