Kun Qian
Machine Learning Engineer at Apple
Seattle, Washington, United States
Summary
👤
Senior🎓
Top SchoolKun Qian is a researcher on Apple's Foundation Model team with eight years of experience focused on domain adaptation and low-resource learning for dialog systems. He brings a strong academic foundation from Johns Hopkins, UC Davis, and Columbia (PhD work advised by Zhou Yu) and has applied his research during internships at Facebook and Salesforce. At Apple he works on mid- and post-training techniques and agentic tool use, bridging core model capabilities with practical dialog behavior. Known for tackling low-resource settings, he blends theoretical rigor with production-minded experimentation to make foundation models more adaptable across domains.
8 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University of California, DavisJohns Hopkins UniversityBachelor of Science (BS) Physics, Bachelor of Science (BS) Physics at Nanjing UniversityDoctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Columbia University
Github Skills (43)
speech-to-text10
artificial-intelligence10
speaker-verification10
csc10
error-detection10
dialog10
kenlm10
facebook10
location10
kaldi10
speech10
asr10
ctc10
cuda10
sequence-to-sequence10
Programming languages (3)
Github contributions (5)
qbetterk/ParlAI
Aug 2020 - Sep 2023
A framework for training and evaluating AI models on a variety of openly available dialogue datasets.
Contributions:49 pushes, 7 branches in 3 years 1 month
nlpdeep-learningdatasetmachine-learningtraining
qbetterk/DAML
Dec 2018 - Jun 2020
Contributions:17 commits, 17 pushes in 1 year 5 months
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