謝宜靜
Deep Learning Algorithm Engineer | Carnegie Mellon University MS ECE '22
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
Carnegie Mellon University's College of Engineering
Carnegie Mellon University
Taiwan
Skills
Languages
English
・
Professional
Chinese
・
Native or Bilingual
Work experiences
Research Assistant
Carnegie Mellon University's College of Engineering・Internship
Jun 2021 ~ Aug 2021
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3 mosPittsburgh, PA, USA
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
Educations
Carnegie Mellon University
Master of Science (MS)・Electrical and Computer Engineering
2021 - 2022
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3.7/4 GPADescription
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
國立臺灣海洋大學
Bachelor of Science (BS)・電機工程學系
2016 - 2020
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4/4 GPAActivities and societies
‧ ML經驗 : 大二進入系上王榮華主任的實驗室後，除了協助電機系與其它系合作的科技部計畫—AI技術應用於智慧化養殖系統的建置外，個人也有做影像處理在機器學習上應用的專題 :
Automatic Fish Detection and Tracking in Underwater Videos (請參閱作品集)
‧ 助教 : 由於大一學業的優良表現，在教授的推薦下，我擔任了交換電路與邏輯設計的助教和微積分的助教。
擔任助教的期間，每個禮拜的課後輔導磨練了我將複雜的觀念用簡單的方式闡述的能力，這使我日後與教授做研究專題時能進行有效的溝通，簡單明瞭地闡述自己的想法。除此之外，擔任交換電路與邏輯設計的助教期間，面對超過百人的課堂，我代替身體微恙的教授上過至少兩次課，讓我克服了公開演講的恐慌並促成了我日後擔任海洋大學電機系畢業生致詞的榮譽。
Description
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。
Clarkson University
Other・Electrical Engineering, Computer Science
2018 - 2019
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4/4 GPADescription
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。
