Kai Wang

【個人資訊】

學校名稱：喬治亞理工學院

研究領域：最佳化演算法(Optimization)、機器學習(ML)

職稱：助理教授

個人網站：https://guaguakai.com/

與臺大教授合作經驗：

• 林軒田教授：損失函數設計 (Loss function design)、梯度下降 (Gradient descent)
• 孫紹華教授：強化學習 (Reinforcement learning)。
• 陳和麟教授：賽局理論 (Game theory)。
• 簡翌教授：AI安全 (AI safety)。

【研究實習計畫】

研究內容簡介

專注於最佳化與機器學習的結合及其社會應用，包含：

1. 演算法整合：最佳化演算法與機器學習演算法的深度結合
2. 生成式模型應用：生成式模型在最佳化、強化學習及模型架構設計上的應用
3. 社會影響力AI：人工智慧於醫療衛生、環境保護、社會科學及賽局理論之研究

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：

• 具備最佳化 (Optimization)、機器學習及演算法的專業知識
• 具備強化學習(RL)與生成式模型（如Diffusion models、Transformer架構）的實作經驗

其他要求：具備流利的英文能力

可接受期長：暑期

接受名額：2名。

簽證文件辦理：由PI透過系所申請，辦理時長較長（3個月以上）

相關費用與福利：

• PI負擔簽證服務費用(DS-2019)
• 相關待遇：若經費許可，可補助部分生活費
• 住宿由學生自行尋覓（無校內住宿或補助）

學分提供：否

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[ Personal Portfolio ]

University: Georgia Institute of Technology (Georgia Tech)

Research  Areas: Knowledge of Optimization and Learning Algorithms (KOALA)

Position: Assistant Professor

Personal Website: https://guaguakai.com/

Collaboration with NTU Faculty:

• Prof. Hsuan-Tien Lin: Loss function design,gradient descent
• Prof. Shao-Hua Sun: Reinforcement learning
• Prof. Ho-Lin Chen: Game theory
• Prof. I Chien: AI safety

[ Research Internship Program ]

Research Overview

The lab focuses on the integration of optimization and machine learning, as well as their societal applications, including:

1. Algorithm Integration: Deep integration of optimization algorithms and machine learning algorithms.
2. Applications of Generative Models: Applying generative models to optimization, reinforcement learning, and modelarchitecture design.
3. Social Impact AI: Research on the application of AI in healthcare, environmental protection,social sciences, and game theory.

Target Student Level:

• Undergraduate students (junior year and above)
• Master’s students
• Ph.D. students

Expected Skills and Qualifications:

• Solid background in optimization, machinelearning, and algorithms
• Practical experience in reinforcement learning(RL) and generative models (e.g., diffusion models, Transformer architectures)

Additional Requirement: Fluent English proficiency

Available Duration: Summer

Number of Positions: 2

Visa Processing: Handled by the PI through the department; processing time is relatively long(over 3 months)

Costs and Benefits:

• The PI will cover the visa processing fee (DS-2019)
• Partial living expense support may be provided, subject to funding availability
• Students are responsible for arranging their own accommodation (noon-campus housing or subsidy provided)

Academic Credit: Not offered