Zixuan Ke
Research Scientist at Salesforce Research
San Francisco Bay Area United States
Summary
👤
Senior🎓
Top SchoolZixuan Ke is a research scientist based in the San Francisco Bay Area with a decade of experience advancing autonomous, agentic systems through deep work in reasoning, LLM post-training, continual learning, and NLP. Now at Salesforce Research after a PhD at University of Illinois Chicago, Zixuan has a strong publication record across top venues (ICLR, NeurIPS, ICML, ACL, EMNLP) and internships at DeepMind, Meta, and Amazon that bridged academic rigor with applied system-building. His recent work focuses on aligning retrieval and LLM behavior and enabling agents to adapt in changing domains, reflecting a practical bent toward robust, deployable models. Notably, he blends classical argument-mining roots with cutting-edge agent and continual-learning methods, showing both breadth and a sustained record of evolving research themes.
10 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Illinois Chicago
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (17)
pre-trained-model10
attention-mechanism10
text-classification10
natural-language-processing10
roberta10
transfer-learning10
transformer-architecture10
pytorch9
machine-learning9
fine-tuning9
deep-learning9
information-theory8
meta-learning7
sequence7
philosophy5
Programming languages (1)
Github contributions (5)
ZixuanKe/CAT
Oct 2020 - Nov 2021
Code for NeurIPS 2020 Paper --- Continual Learning of a Mixed Sequence of Similar and Dissimilar Tasks
Contributions:2 commits, 10 pushes, 1 branch in 1 year 1 month
pytorchsequenceneurips-2020similardeep-learning
ZixuanKe/PyContinual
Jun 2021 - Dec 2022
PyContinual (An Easy and Extendible Framework for Continual Learning)
Contributions:29 commits, 4 PRs, 24 pushes in 1 year 6 months
transformer-architecturepytorchpre-trained-modelattention-mechanismtransfer-learning
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