Jerry Ding is a technology founder and CEO with 11 years of engineering experience who leads JMuse Technologies in Shanghai, building adaptive AI agents and high-capacity AI memory systems to accelerate scientific discovery. A Carnegie Mellon-trained machine learning specialist, he previously optimized Amazon Redshift’s OLAP query engine—delivering a >20% TPCH benchmark improvement—and cut Sumo Logic’s continuous query cluster needs by half during his internship. At JMuse he’s moving beyond RAG-style pipelines to enable agents that internalize tens of thousands of scientific documents and operate specialized tools, initially targeting materials science in collaboration with institutions like the Shanghai Institute of Optics and Fine Mechanics. His research focus on continuous deep learning and human controllability of generative models informs both product and research directions, pairing rigorous systems performance background with frontier AI research. He’s open to partnerships with researchers and R&D teams aiming to integrate domain knowledge into autonomous research workflows.
11 years of coding experience
2 years of employment as a software developer
Master's degree, Machine Learning, Master's degree, Machine Learning at Carnegie Mellon University
Contributions:1 release, 43 pushes, 1 branch in 1 year
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