Yang Liu
Clinical Laboratory Supervisor
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolYang Liu is a Clinical Laboratory Supervisor in New York with eight years of experience bridging biomedical diagnostics and software engineering. He holds a computer science master’s from the University of Pennsylvania and a strong clinical laboratory science background from Stony Brook, enabling him to translate laboratory workflows into reliable, instrument-level processes. Technically fluent in C++, Java, Linux, Python and modern web stacks, he has contributed to notable open-source financial RL projects (FinRL, ElegantRL), where his work ranged from refining user-facing documentation to modifying core actor-critic network components. Comfortable moving between bench and code, he has implemented firmware and IPC on embedded Linux systems and hands-on hematology, flow cytometry, and histology diagnostics. His profile reflects a rare combination of clinical rigor and applied ML/embedded engineering, with proven experience improving reproducibility and user experience in both lab and open-source environments.
8 years of coding experience
5 years of employment as a software developer
Bachelor of Science - BS Clinical Laboratory Science/Medical Technology/Technologist, Bachelor of Science - BS Clinical Laboratory Science/Medical Technology/Technologist at Stony Brook UniversityMaster of Computer and Information Technology Computer Science, Master of Computer and Information Technology Computer Science at University of Pennsylvania
Github Skills (13)
finance10
deep-reinforcement-learning10
pytorch10
jupyter-notebook10
sac10
python10
reinforcement-learning10
documentation10
machine-learning9
dqn9
tdd8
tensorflow8
ppp7
Programming languages (4)
Github contributions (5)
AI4Finance-Foundation/FinRL
Nov 2020 - Jan 2023
FinRL: Financial Reinforcement Learning. 🔥
Role in this project:
Technical Writer
Technical WriterContributions:2 reviews, 353 commits, 33 PRs in 2 years 2 months
Contributions summary:Yang primarily updated the `FinRL_single_stock_trading.ipynb` file, making minor edits to the introductory text and documentation. These changes include correcting wording, adding a note about loading the notebook in Colab, and generally refining the introductory explanations and links. The user's commits focus on clarifying the content and improving the user experience related to the notebook's introduction and supporting resources.
stable-baselinesdrl-frameworkdeep-reinforcement-learningsecfinance
AI4Finance-Foundation/ElegantRL
Jan 2021 - Jan 2023
Massively Parallel Deep Reinforcement Learning. 🔥
Role in this project:ML Engineer
ML EngineerContributions:266 commits, 23 PRs, 260 pushes in 1 year 11 months
Contributions summary:Yang primarily updated and modified the `ElegantRL.py` and `AgentNet.py` files, which suggests a focus on the core reinforcement learning components. The changes included adjustments to the Actor and Critic networks, specifically within the context of the Actor-Critic and SAC algorithms. The code modifications suggest the user is working on the model architecture.
mahjongdeep-reinforcement-learningtd3bipedalwalkerhardcorereinforcement
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