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https://yijing-sie.github.io/

I am a deep learning algorithm engineer, with a master's degree in Electrical and Computer Engineering from Carnegie Mellon University and a bachelor's degree in Electrical Engineering from National Taiwan Ocean University. 

I conducted two machine learning independent research projects in college, the first about Object Detection and the second about Anomaly Detection; During my time at CMU, I further deepened and broadened my knowledge and skills in machine learning and deep learning via coursework and projects.

I am looking to expand my network, so please feel free to connect with me or message me with any inquiries!

Programming Language: Python, C, Java, C++, Haskell, MATLAB 
Operating Systems: Linux, Microsoft Windows
Scientific Libraries: PyTorch, TensorFlow, NumPy, SciPy, Pandas, Scikit-Learn, FastAPI, OpenCV, JavaFx, PySpark
Technical Tools: Docker, Git, bash, Android Studio

At CMU, I deepened and broadened my knowledge and skills in machine learning with coursework.

In the summer of 2021, I became a research assistant, assisting in one of Dr. Kun Zhang’s research projects about the causal representation of multimodal data. 

• Studied state-of-the-art research work in causal representation and multi-tasking learning and summarized findings
• Collaborated with other students to study a theoretical model for the causal representation of multimodal
 data
• Scheduled and attended regular meetings with professors

Carnegie Mellon University

大一期間，我專心致至，以課業為主而成為了系上第一。

在課業最繁重的大二階段，為了學習更多課堂外的知識，除了盡全力並成功地繼續維持系排第一的優異成績外，我也擔任了為期一年的助教。同時，我也加入系上王榮華主任的實驗室，做機器學習相關的專題。

大三那年，為了本身的興趣和理想，我離開了臺灣到美國深造成為了Clarkson University 的 交換學生。

回國後，大四的我開始申請國外研究所，並很榮幸的拿到了: Columbia University - Computer Science, Carnegie Mellon University - Electrical and Computer Engineering 和 University of Maryland - Machine Learning 的研究所秋季入學錄取通知。

國立臺灣海洋大學

大三那年，為了學到更多機器學習相關的知識，滿足我對其的熱情與求知慾望，在教授的推薦下，我便隻身飛往相距約9000公里遠的美國到Clarkson University做一年的交換學生。
在Clarkson University就讀時，我與當時一位Computer Science的教授做異常偵測在機器學習上應用的研究專題 (請參閱作品集) 並透過修課強化了程式語言及機器學習理論的能力。

Clarkson University

Deep Learning Algorithm Engineer | Carnegie Mellon University MS ECE '22

謝宜靜

Carnegie Mellon University's College of Engineering

Research Assistant

I assisted in one of Dr. Kun Zhang’s research projects about the causal representation of multimodal data. 

• Studied state-of-the-art research work in causal representation and multi-tasking learning and summarized findings
• Collaborated with other students to study a theoretical model for the causal representation of multimodal
 data
• Scheduled and attended regular meetings with professors

Overviewed by Dr. Kun Zhang and Dr. Yuejie Chi

https://github.com/yijing-sie/Multimodal-Data-and-Causal-Representation-Learning

謝宜靜’s posts