Qingkai Fang is a Ph.D. candidate in Natural Language Processing at the University of Chinese Academy of Sciences, graduating in June 2026, with eight years of research experience across speech, vision and multimodal language models. He has authored over 10 papers at top venues (NeurIPS/ICLR/ACL/EMNLP), eight as first author, and has industry research internships at ByteDance, Peking University, and UCAS focused on end-to-end speech translation, multimodal machine translation, and pose-aware vision tasks. Qingkai blends deep academic rigor with applied impact—one of his first-author works was accepted at ACL 2022 during his ByteDance internship—and consistently moves ideas from prototype to peer-reviewed publication. Based in Haidian District, Beijing, he combines strong theoretical foundations with practical system-building skills and a top undergraduate GPA (3.83/4.0) from Beijing University of Posts and Telecommunications. Colleagues would note his knack for integrating speech and visual modalities into scalable translation systems, making him well suited for research roles that bridge core modeling and deployment.
8 years of coding experience
Doctor of Philosophy - PhD, Natural Language Processing, Doctor of Philosophy - PhD, Natural Language Processing at University of Chinese Academy of Sciences
Bachelor's degree, Computer Science and Technology, 3.83/4.0, Bachelor's degree, Computer Science and Technology, 3.83/4.0 at 北京邮电大学
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