Maminur Islam is an Assistant Professor and PhD-trained computer scientist with nine years of experience bridging research-grade AI and production software engineering. His work spans statistical relational models, scalable inference for Markov Logic Networks, and deep learning for computer vision, including GAN-based super-resolution and image segmentation. He published in top AI conferences and during an Adobe Research internship built models to predict video watchability and an explainer that pinpoints sensitive frames—an invention now under patent review. Before academia he led full-stack teams building microservices and performant dashboards for onshore and offshore clients, bringing practical systems thinking to research problems. Based in Connecticut and educated at BUET and the University of Memphis, he uniquely couples background-knowledge-rich MLNs with data-hungry neural networks to tackle real-world, large-scale perception tasks.
9 years of coding experience
8 years of employment as a software developer
Graduate Computer Science, Graduate Computer Science at University of Memphis
Bachelor of Science (BSc) Computer Science and Engineering, Bachelor of Science (BSc) Computer Science and Engineering at Bangladesh University of Engineering and Technology
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