Albert Liang
Researcher at Two Sigma
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolAlbert Liang is a researcher at Two Sigma with six years of experience bridging deep learning research and applied machine learning in finance and physical sciences. He holds dual BS degrees in Computer Science and Computational Finance from Carnegie Mellon and completed an MS in Machine Learning, combining strong theoretical grounding with practical systems work. His background includes research on uncertainty estimation, PDEs, and active learning, distributed training for transformers, and production-focused internships at Google and Amazon. At CMU he taught advanced deep learning and software construction, demonstrating an ability to communicate complex concepts to large classes. Notably, he has moved between academia and industry—contributing to PyTorch/XLA and trading-model internships—bringing both rigorous research methods and production-minded engineering to AI problems.
7 years of coding experience
2 years of employment as a software developer
High School Diploma, High School Diploma at Beijing No.4 High SchoolBachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at Carnegie Mellon University School of Computer ScienceBachelor of Science - BS, Computational Finance, Bachelor of Science - BS, Computational Finance at Carnegie Mellon UniversityMaster of Science - MS, Machine Learning, Master of Science - MS, Machine Learning at Machine Learning Department at CMU
Github Skills (47)
pytorch10
xla10
python9
machine-learning9
gpu9
deep-learning9
compiler9
gpu-acceleration8
numpy8
github-flow8
tensor8
neural-network8
tpu7
autograd7
database-design6
Programming languages (6)
Github contributions (5)
thisisalbertliang/training
Feb 2022 - Apr 2022
Reference implementations of MLPerf™ training benchmarks
Contributions:30 reviews, 77 commits, 37 PRs in 2 months
implementationsdeep-learningmlperfmachine-learningtraining
thisisalbertliang/pytorch
Nov 2021 - Feb 2022
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Contributions:3 reviews, 6 PRs, 19 pushes in 2 months
pythongpu-accelerationdeep-learninggpuacceleration
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