Raymond A. Yeh

【一、個人Portfolio】

·       學校名稱：Purdue University (普渡大學)

·       實驗室名稱：ML/CV Lab

·       研究領域：機器學習 (Machine Learning)、電腦視覺(Computer Vision)

·       職稱：Assistant Professor (助理教授)

·       電子郵件：rayyeh@purdue.edu

·       個人網站：https://raymond-yeh.com/

【二、研究實習計畫】

·       研究內容簡介： 目前的重點研究方向為：

1.     機器反學習(Machine Unlearning)：探討如何讓模型安全且有效地「反學習」特定的訓練數據。

2.     等變性穩健視覺模型(Robust Vision Models through Equivariance)：從等變性的角度切入，提升視覺模型的穩定性與穩健性。

3.     其他：與電腦視覺(CV) 和機器學習(ML) 相關的其他課題亦有合作空間。

·       期待學生教育程度：大三（含）以上大學生、碩士生、博士生。

·       期待學生技能與特質：

o  具備使用機器學習工具箱的經驗，特別是PyTorch。

o  具備機器學習(ML)與深度學習(DeepLearning)的基礎背景知識。

o  具備強大的工程實作 (Engineering)與原型開發 (Prototyping) 能力。

·       其他要求：具備足以進行學術研究討論的英文水平。

·       實習行政資訊：

o  可接受期長：暑期

o  接受名額：2 名。

o  簽證文件辦理：由PI 透過系所申請，辦理時長約2-3 個月。

o  相關費用：

§  PI 負擔簽證服務費用 (DS-2019)。

§  住宿由學生自行尋覓（無校內住宿或補助）。

o  學分提供： 否。

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I. Personal Portfolio

• University: Purdue University
• Laboratory: ML/CV Lab
• Research  Areas: Machine Learning, Computer Vision
• Position: Assistant Professor
• Email: rayyeh@purdue.edu
• Personal Website: https://raymond-yeh.com/

II. Research Internship Program

• Research Overview: The current main research directions include:

1.     Machine Unlearning:
Investigating how models can safely and effectively “unlearn” specific trainingdata.

2.     Robust Vision Models through Equivariance:
Improving the stability and robustness of vision models from the perspective ofequivariance.

3.     Other Topics:
Additional research topics related to computer vision (CV) and machine learning(ML) are also open for collaboration.

• Target Student Level: Undergraduate students (junior year and above), master’s students, and Ph.D. students

• Expected Skills and Qualifications:

o  Experience using machine learning frameworks,especially PyTorch

o  Foundational knowledge in machine learning (ML)and deep learning

o  Strong engineering and prototyping skills

• Additional Requirement: Sufficient English proficiency for academic research discussions

• Administrative Information:

o  Available Duration: Summer

o  Number of Positions: 2

o  Visa Processing: Handled by the PI through the department; estimated processing time isapproximately 2–3 months

o  Costs:

§  The PI will cover the visa processing fee (DS-2019)

§  Students are responsible for arranging their own accommodation (noon-campus housing or subsidy provided)

o  Academic Credit: Not offered