Shah Muhammad Hamdi

Shah Muhammad Hamdi is an Assistant Professor in the Department of Computer Science at Utah State University (USU), leading the Hi-dimensional Data Analytics and Mining (HiDAM) lab. He previously held a faculty position at New Mexico State University (NMSU). He earned his Ph.D. and M.S. in Computer Science from Georgia State University (2020) and a B.Sc. from Rajshahi University of Engineering and Technology (2014). His research focuses on machine learning and data mining for graphs, time series, and spatiotemporal data, with applications in solar physics, neuroscience, and social networks. He has received notable grants, including NSF SHINE and CRII awards, and has published extensively in top venues like AAAI, ICMLA, and IEEE Big Data.

• Education:
  • Ph.D. & M.S. in Computer Science, Georgia State University (2020)
  • B.Sc. in Computer Science and Engineering, Rajshahi University of Engineering and Technology (2014)
• Research Interests:
  • Graph representation learning and feature selection
  • Time series classification and counterfactual explanations
  • Applications in solar flare prediction, neuroscience (fMRI analysis), and social media discourse

Recent Achievements: His work includes pioneering methods for solar flare prediction using multivariate time series and functional networks, as well as developing frameworks for explainable AI and data augmentation. He leads initiatives in machine learning cyberinfrastructure for multivariate time series and functional networks, funded by NSF grants.

• Awards:
  • NSF SHINE Award (2023): Solar flare prediction via graph-based ML
  • NSF CRII Award (2022): Cyberinfrastructure for multivariate time series analysis
• Advising & Grants:
  • Ph.D. students: Reza EskandariNasab, Onur Vural, Santosh Chapagain
  • Recent publications span solar physics, explainable AI, and social media analytics

Labs & Teams: HiDAM Lab at USU focuses on high-dimensional data analytics, integrating machine learning and domain-specific applications.