Jiaming Song
PhD Student at Stanford University
Palo Alto, California, United States
Summary
🤩
Rockstar🎓
Top SchoolJiaming Song is a fifth-year PhD student in Computer Science at Stanford focused on machine learning and deep learning under Stefano Ermon, with 11 years of research and engineering experience spanning academia and industry. He earned his BEng from Tsinghua and collaborated there with Jun Zhu and Lawrence Carin on scalable Bayesian methods before moving to Stanford for deep generative and reinforcement learning research. His internships at OpenAI, Facebook, Megvii, and Microsoft Research Asia produced practical systems for model distillation, detection, and deep RL, and he has pursued scalable inference work that achieved 1000x speedups for link prediction. Jiaming contributes research on conditional deep generative models for time series and maintains a publications page and personal site showcasing his work. Based in Palo Alto and coding as @lumalabs on GitHub, he blends strong theoretical foundations with systems-minded implementations that bridge large-scale data and probabilistic modeling. An under-the-radar strength is his consistent focus on scalability—both algorithmic and engineering—that turns research insights into usable, high-throughput solutions.
11 years of coding experience
2 years of employment as a software developer
Bachelor of Engineering (BEng), Computer Science, Bachelor of Engineering (BEng), Computer Science at Tsinghua UniversityDoctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at Stanford University
Chinese, German, English
Github Skills (107)
unreal-engine-410
python10
simulator10
implicit10
deep-learning10
gpu10
gpu-acceleration10
ros10
optimization10
acceleration10
ml10
numpy10
denoising10
neural-network10
deep-reinforcement-learning10
Programming languages (8)
Github contributions (5)
ermongroup/a-nice-mc
Jun 2017 - Jul 2018
Code for "A-NICE-MC: Adversarial Training for MCMC"
Contributions:1 release, 35 commits, 4 PRs in 1 year 1 month
pytorchdeep-learningadversarialadversarial-trainingtraining
d2c-model/d2c-model.github.io
Jun 2021 - Oct 2021
Website for D2C paper
Contributions:9 commits, 1 PR, 8 pushes in 4 months
javascriptd2c
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