PhD Student: Seraj Mostafa


Big Data Analytics Lab

Department of Information Systems
University of Maryland, Baltimore County
Baltimore, Maryland, U.S.A.
Email: serajmost _at_ umbc_dot_edu
Lab: ITE 471
Profiles: Google Scholar, LinkedIn


Short Biography

Seraj is a Ph.D. student at the Department of Information Systems working with Dr. Jianwu Wang. His main focus is using the AI approches in Earth Informatics research in the remote sensing domain. He began as a Ph.D. student in Fall 2021 to work on Ocean Eddy detection and localization project funded by NASA’s Jet Propulsion Lab (JPL). Later, he worked on identifying Gravity Wave in the upper atmosphere, another project funded by NASA goddard space and flight center. His current focus is on Distributed Analytics on HPC platform for large scale remote sensing data and complex deep neural network training to aid in Artificial Intelligence techniques for Earth Informatics. For this work he is supported jointly by NASA Access project and Research Computing of Division of IT (DoIT) at UMBC that supports UMBC’s High Performance Computing in the Cloud.

Research Focus

    • Artificial Intelligence for Climate Change/Earth Informatics
    • Distributed Deep Learning/Analytics
    • High Performance Computing

Invited Talk

    • Seraj received an invitation to the U.S. Naval Research Lab (NRL) in Mississippi on September 12, 2023, to discuss his AI-driven Remote Sensing work. During the visit, he presented how AI techniques can be applied to Ocean Research, offering potential benefits to the U.S. Navy.


    • 2021 ~ ongoing: Ph.D.  in Information Systems, University of Maryland, Baltimore County, Maryland, USA
    • 2017 ~ 2020: M.Sc. in Computer Science, Montana State University, Bozeman, Montana, USA
    • 2010 ~ 2012: M.Sc. in Computer Science and Engineering, Luleå University of Technology, Luleå, Sweden
    • 2001 ~ 2004: B.Sc. in Computing Information Systems, London Metropolitan University, UK


    • CNN based Ocean Eddy Detection using Cloud Services, Published by the 2023 IEEE Geoscience and Remote Sensing Society (IGARSS). [Publication Link]
    • Atmospheric Gravity Wave Detection Using Transfer Learning Techniques. Published by the 2022 IEEE/ACM 9th International Conference on Big Data Computing, Applications and Technologies (BDCAT 2022). [Publication Link]
    • Benchmarking Probabilistic Machine Learning Models for Arctic Sea Ice. Published by the 2022 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2022), IEEE. [Publication Link]
    • More at Google Scholar



    • Summer 2022 REU program: A NSF funded program to support Research Experience for Undergraduates (REU) from various US universities. Seraj advised 5 students in a Transfer Learning Project to detect Gravity Wave from Remote Sensing Satellite Imagery.
    • Seraj also advised 4 Masters students for AWS cloud environments namely, SageMaker and EC2 to deploy RESTFull API services to automate Machine Learning model training and inference processes.