Kun Qian
Software Engineer, AIML at Google
New York, New York, 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
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 (41)
speech-to-text10
pytorch10
artificial-intelligence10
python10
speaker-verification10
csc10
error-detection10
kenlm10
kaldi10
speech10
asr10
cuda10
sequence-to-sequence10
speech-recognition10
shell10
Programming languages (4)
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
ai
qbetterk/DAML
Dec 2018 - Jun 2020
Source code for the ACL 2019 paper entitled "Domain Adaptive Dialog Generation via Meta Learning" by Kun Qian and Zhou Yu
Contributions:17 commits, 17 pushes in 1 year 5 months
meta-learning
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