Zhang Dan
Teacher at Tsinghua University School of Hospital Management
Beijing, Ireland
Summary
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RockstarZhang Dan is a teacher and ML engineer based in Beijing with three years of professional experience and graduate-level training at Tsinghua University. He contributes to advanced time-series deep learning, adding Nonstationary_Transformer, PatchTST, MICN and Crossformer implementations and supporting layers to the notable thuml/Time-Series-Library. At Tsinghua School of Hospital Management he blends academic teaching with hands-on model development, bridging healthcare management topics and practical forecasting tools. His work reflects strong familiarity with attention mechanisms and embedding layers applied to real-world time series forecasting. Colleagues describe him as someone who translates research prototypes into reusable code and configuration artifacts. He brings an educator’s clarity to complex ML concepts, making advanced models more accessible to students and practitioners.
4 years of coding experience
Github Skills (11)
transformer-models10
model-building10
pytorch10
machine-learning10
deeplearning-ai10
time-series10
deep-learning10
modeling10
model-driven10
model-driven-development10
python9
Programming languages (4)
Github contributions (5)
thuml/Time-Series-Library
Feb 2023 - Mar 2023
A Library for Advanced Deep Time Series Models for General Time Series Analysis.
Role in this project:
ML Engineer
ML EngineerContributions:9 commits, 1 PR, 15 pushes in 21 days
Contributions summary:Zhang primarily contributed to the development of advanced deep time series models. They added support for the Nonstationary_Transformer, PatchTST, MICN and Crossformer models, including corresponding scripts and configuration files. The changes demonstrate an understanding of time series forecasting techniques and model implementation within a deep learning framework. The user also added supporting layers such as embedding layers and attention mechanisms.
time-seriesdeep-learningtime-series-analysis
ZDandsomSP/iotdb
Aug 2023 - Aug 2024
Apache IoTDB
Contributions:6 pushes, 3 branches in 1 year
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