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zefangshen · Jul 17, 2024 · 9a51688 · 9a51688
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@@ -20,7 +20,7 @@ I develop AI-based solutions and conduct novel Machine Learning research. See my
 
 I possess expertise in building data science pipelines using Python and R. I applied various machine learning algorithms (support vector machines, random forests, XGBoost, Gaussian Processes) and deep learning architectures (convolutional neural networks, LSTMs, attention-based models) to deliver high-impact solutions. My work has resulted in high-quality publications and real-world applications.
 
-My research tackles challenging problems in machine learning for spectroscopy and robotics, resulting in publications in top tier journals such as ISPRS Journal of Photogrammetry and Remote Sensing (IF12.7), Earth-Science Reviews (IF12.1), Global Change Biology (IF11.6), Communications earth & environment (IF7.9), SOIL(IF6.8), etc. Of particular distinction is my receipt of the <a href="https://asmejmd.org/2019/10/01/announcing-the-journal-of-mechanical-design-2018-editors-choice-paper-award/">Journal of Mechanical Design 2018 Editors' Choice Paper Award</a> given to one article among all in 2018 for fundamental contribution in robotic design.
+My research tackles challenging problems in machine learning for spectroscopy and robotics, resulting in publications in top tier journals such as ISPRS Journal of Photogrammetry and Remote Sensing (IF12.7, 2022), Earth-Science Reviews (IF12.1), Global Change Biology (IF11.6), Communications earth & environment (IF7.9), SOIL(IF6.8), etc. Of particular distinction is my receipt of the <a href="https://asmejmd.org/2019/10/01/announcing-the-journal-of-mechanical-design-2018-editors-choice-paper-award/">Journal of Mechanical Design 2018 Editors' Choice Paper Award</a> given to one article among all in 2018 for fundamental contribution in robotic design.
 
 I am passionate about transforming research outputs into real-world solutions. With my full-stack data science skills (backend: Python Django; frontend: Bootstrap/React; Deployment: AWS), I implemented machine learning pipelines for the modeling of spectral data into a web application, which resulted in the world’s first global service for estimating of soil organic carbon with spectra.