Summary
Jinyan Su is a research-focused machine learning engineer specializing in safety and alignment, with nine years of experience building models that are helpful, honest, and capable of abstention when appropriate. Currently a Research Intern at Microsoft after recent research internships at Meta and Adobe, Jinyan develops post-training interventions (SFT, RL) and prompt-steering methods to improve model robustness without degrading core capabilities like math and QA. They design synthetic-data generation, reward functions, and RL environments, and have experimented with using LLMs as judges for safety evaluation and tool-enabled reasoning. A PhD candidate at Cornell and visiting scholar at Stanford, Jinyan blends rigorous academic training with hands-on product-focused research in multi-turn dialogue and retrieval-augmented agents. Based in California, they bring a pragmatic approach to alignment problems—often tackling subtle failure modes such as stale or misleading queries by engineering targeted data and evaluation pipelines.
9 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Cornell University
Bachelor of Science - BS Mathematics-Information and computational sciences, Bachelor of Science - BS Mathematics-Information and computational sciences at University of Electronic Science and Technology of China
English, Chinese, Spanish