Jin Huang is an Applied Researcher specializing in generative AI for image and video synthesis, currently advancing diffusion and transformer-driven models at Pixocial. He holds a PhD in Computer Science from the University of Notre Dame, where his interdisciplinary research fused computer vision, machine learning, and cognitive science to develop human-in-the-loop frameworks that align model outputs with human perception. Over 11 years he has worked across academia and industry—from medical imaging and human activity recognition to fine-tuning multimodal foundational models—bringing both theoretical rigor and product-minded experimentation. Jin’s practical toolkit spans Python, PyTorch, HuggingFace and visual psychophysics, and he uniquely combines psychophysical insights with large-model engineering to improve controllability and realism in video generation. Based in Bellevue, WA, he balances deep research pedigree with applied work that bridges cutting-edge generative research and real-world retrieval and editing problems.
10 years of coding experience
9 years of employment as a software developer
Master’s Degree, Computer Science, 3.62/4.0, Master’s Degree, Computer Science, 3.62/4.0 at New York University
Bachelor's degree in Engineering, Software Engineering, 80/100, Bachelor's degree in Engineering, Software Engineering, 80/100 at Nankai University
Doctor of Philosophy - PhD, Computer Science, 3.75/4.0, Doctor of Philosophy - PhD, Computer Science, 3.75/4.0 at University of Notre Dame
None Degree Exchange Program, Computer Science, None Degree Exchange Program, Computer Science at University of Tsukuba
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Jin Huang - Applied Researcher at Pixocial, Human-First AI