Summary
Ibne Shihab is an Applied Scientist II at Amazon with a Ph.D. in Computer Science and nine years of experience building applied AI systems that bridge computer vision, LLMs, and reinforcement learning. He has led real-world transportation safety projects for the Iowa DOT—deploying snowplow navigation, real-time crash detection with LLM-generated narratives, and multimodal video-text analysis under extreme weather. His work spans production ML at Amazon (knowledge-graph frameworks, novel KGE models and recommenders) and precision agriculture (soil-mapping engines that improved accuracy by 35% and cut processing time by 20%). A published researcher and reviewer at venues like CVPR and EMNLP, he combines rigorous academic methods with pragmatic engineering across PyTorch, RLlib, LangChain, CARLA/SUMO, and AWS. He also explores emerging frontiers such as quantum ML and synthetic crash-video generation, reflecting a consistent focus on turning complex, multimodal data into reliable, safety-critical systems. Based in Sunnyvale, he’s known for fast responses—just start your message with “Cricket.”
9 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD, Machine learning ,Deep Learning, Robotics, Large Language Models, Doctor of Philosophy - PhD, Machine learning ,Deep Learning, Robotics, Large Language Models at Iowa State University
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Vermont
Nanodegree program, Intro To Machine Learning With PyTorch, Nanodegree program, Intro To Machine Learning With PyTorch at Udacity
Bachelor of Science - BS, Computer Science and engeneering, Bachelor of Science - BS, Computer Science and engeneering at BRAC University