Tianxiao Jiang is an ML research engineer and manager with 13 years of experience bridging computational neuroscience and production-scale deep learning systems in the San Francisco Bay Area. He holds a PhD in Computational Neuroscience and has applied signal processing, clustering, and statistical methods to brain–machine interfaces and functional brain mapping, achieving results like 99% hand-posture classification in prior research. Over the past several years he transitioned into hardware-aware model engineering and generative AI infrastructure at companies such as Cerebras and SambaNova, building efficient models and compiler/frontend tooling for dataflow hardware. Tianxiao combines research rigor with hands-on software engineering—authoring open-source neural signal analysis tools and shipping enterprise ML systems—and is currently exploring the intersection of neuroscience and genomics. He is particularly focused on deep learning and system-level optimization, comfortable moving from C++/computational geometry to TensorFlow and NLP stacks. Colleagues describe him as a pragmatic researcher who turns complex academic insights into deployable, high-performance ML solutions.
13 years of coding experience
11 years of employment as a software developer
Doctor of Philosophy - PhD Computational Neuroscience Biomedical Engineering, Doctor of Philosophy - PhD Computational Neuroscience Biomedical Engineering at University of Houston
Bachelor of Science (BS) Electrical Electronics and Communications Engineering, Bachelor of Science (BS) Electrical Electronics and Communications Engineering at Shanghai Jiao Tong University
Contributions:4 commits, 2 pushes in 3 years 4 months
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