Summary
Adeel Zafar is a research-focused software engineer and PhD candidate in Computer Science at the University of Houston with 11 years of experience applying computer graphics, deep learning, and data analytics to large volumetric flow datasets. He develops algorithms and visual analytics systems for segmentation and extraction of physical structures like vortices from turbulent flow simulations, blending hands-on deep learning (PyTorch, TensorFlow, Keras) with OpenCV and mesh-based techniques. His background spans image algorithm engineering and production support for enterprise systems, giving him a strong practical grounding in deployment and debugging alongside research. He has a solid academic foundation with advanced degrees from Shanghai Jiao Tong University and NUST, and a 3.83/4.0 GPA in his ongoing PhD. Notably, his work sits at the intersection of flow visualization and computer graphics, enabling interpretable analysis of complex simulation data rather than just raw model outputs.
11 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, 3.83 / 4.0, Doctor of Philosophy - PhD, Computer Science, 3.83 / 4.0 at University of Houston
Bachelor of Software Engineering, Computer Software Engineering, 3.51 / 4.00, Bachelor of Software Engineering, Computer Software Engineering, 3.51 / 4.00 at National University of Sciences and Technology (NUST)
Master of Software Engineering, Computer Software Engineering, 3.72 / 4.00, Master of Software Engineering, Computer Software Engineering, 3.72 / 4.00 at Shanghai Jiao Tong University
English