Summary
Reshad Hoque is a research scientist specializing in applied deep learning across computer vision, remote sensing, and NLP, currently working at BlueHalo from Portland, OR. With eight years of experience and a PhD focused on ML, he has developed practical models ranging from U-Net/HR-Net and transformers for sketched image segmentation to GANs and super-resolution for remote sensing imagery. He combines strong coding proficiency in Python and MATLAB with hands-on experience in PyTorch, Keras, and Hugging Face to move research prototypes toward real-world applications. His background includes academic research and teaching roles where he led projects on seagrass scar detection and fake scientific news detection, demonstrating a blend of domain breadth and problem-driven rigor. Known as a self-starter and continuous learner, he often bridges signal-processing foundations with modern deep architectures—an approach shaped by internships at Los Alamos National Laboratory and years mentoring students.
8 years of coding experience
Bachelor of Science (B.Sc.), Electronics and Communications Engineering, Bachelor of Science (B.Sc.), Electronics and Communications Engineering at Khulna University of Engineering and Technology
Master of Engineering (M.Eng.), Electrical and Electronics Engineering, 3.9, Master of Engineering (M.Eng.), Electrical and Electronics Engineering, 3.9 at Lamar University
Doctor of Philosophy - PhD, Machine learning, Deep learning, Computer vison, Natural Language Processing, 3.75, Doctor of Philosophy - PhD, Machine learning, Deep learning, Computer vison, Natural Language Processing, 3.75 at Old Dominion University
English