Zihang Dai is a technical staff engineer and researcher with 11 years of experience at the intersection of large-scale machine learning and language modeling, currently based in the San Francisco Bay Area and working at xAI. He previously spent several years at Google advancing pretraining and efficient NLP models (contributions to XLNet and Funnel-Transformer during his student researcher period) and progressed through research scientist ranks to staff level. Zihang holds an MS and PhD in Computer Science from Carnegie Mellon and combines deep academic rigor with product-facing research experience across premier labs including MILA and Baidu. His background also spans business and strategy training from Tsinghua and Rotterdam, giving him an unusual ability to translate technical advances into strategic priorities. Known for work on energy-based GAN calibration and efficient language processing, he blends theoretical insight with practical system-building in production-scale AI teams. Colleagues describe him as a researcher-engineer who moves smoothly between novel model ideas and the engineering required to make them usable at scale.
11 years of coding experience
2 years of employment as a software developer
Bachelor of Business Administration (BBA), Management Information Systems, General, 90/100, Bachelor of Business Administration (BBA), Management Information Systems, General, 90/100 at Tsinghua University
Master of Science (M.S.), Computer Science, 4.15 / 4.33, Master of Science (M.S.), Computer Science, 4.15 / 4.33 at Carnegie Mellon University
Bachelor of Business Administration (B.B.A.), strategy consulting, 8.8/10, Bachelor of Business Administration (B.B.A.), strategy consulting, 8.8/10 at Rotterdam School of Management
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