四大学域介绍 | 人工智能

学域介绍

融合学科重点领域

• 人工智能与设计

• 人工智能与商业

• 人工智能与金融

• 人工智能与制造

• 人工智能与医学

• 人工智能与安全隐私

• 人工智能与智慧生活

人才培养

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// 必修课程（6学分）

跨学科核心课程（二选一）

 ◽ 跨学科研究方法 2学分 

本课程旨在让学生使用多种方法对现实中的案例进行定量分析。学生将学习如何在跨学科项目中使用不同工具，以及如何自主获得新技能。本课程提供跨学科/多功能的多个模块，学生可以运用其解决各种各样的实际问题。

 ◽ 跨学科设计思维 2学分 

本课程侧重于用户协作设计方法，它主要用于产出包容的、利益相关者视角和产品功能视角相融合的产品解决方案。学生将通过采用递归用户反馈的参与方法、实验性的原型设计、以及散发和聚合性的思维策略，创造特定的产品（Product）/流程（Process）/政策（Policy）/协议（Protocol）/计划（Plan）（5P）概念模型。代表性的课程专题包括设计思维；利益相关者研究；概念开发、筛选和选择以及交互设计。

枢纽核心课程

 ◽ 信息科学与技术：基本要素与趋势 

这门基于探究的课程旨在向学生介绍信息时代推动数字转型所需要的概念和技能。学生将学习如何在信息枢纽的四个主要领域（即人工智能、数据科学与分析、物联网以及计算媒体与艺术）进行科学研究，探索现实生活中的技术应用，并讨论未来可能的重大挑战。该课程融合了各种教学和学习形式，包括讲座授课、研讨会、在线课程、小组讨论和一个课程项目。

其他枢纽核心课程（三选一）

  ◽ 功能枢纽：面向可持续的未来的功能枢纽入门 

本课程涵盖功能枢纽四大学域的背景知识，包括先进材料、可持续能源与环境、微电子学、地球与海洋大气科学。 

 ◽ 社会枢纽：技术创新与社会企业家精神 

本课程讨论了技术突破给人类社会带来的机遇和风险。为了使技术的积极效益最大化，社会成本最小化，我们需要什么样的政策反应？特别是我们如何利用技术进步、创业思维来解决社会所面临的挑战（如失业、收入不平等和社会分化、环境恶化、健康差异、人口老龄化等）？该课程使用案例研究，或者跨境时间序列数据分析，来促进对各种社会问题的讨论，并寻找现实世界中的创新解决方案。

 ◽ 系统枢纽：基于模型的系统工程 

基于模型的系统工程（MBSE）是一种现代的系统工程方法，它使用概念模型，让系统架构师、设计师、开发人员和利益相关者之间进行交流。对象-过程方法学（OPM）是一种MBSE语言和方法，用于构建所有系统的彼此独立的概念模型。该课程为学生提供了MBSE的基本知识和工具，侧重于系统的概念模型，使学习者具有学科上的竞争优势。

// 选修课程示例（15学分）

专业必修课程：3学分，学生需要从下列AI必修课程中选择任意一门

 ◽ 高级人工智能  3学分 

该课程将涵盖先进的人工智能概念与技术。主要课题有：问题解决，知识与推理，规划，不确定的知识与推理，机器学习和机器人技术。

 ◽ 机器学习  3学分

介绍主要的机器学习范式和技术，基本应用统计和信息理论，决策树，神经网络，贝叶斯分类，核方法（Kernel methods），聚类分析，密度估计，特征选择和提取，隐马尔可夫模型（hidden Markov models），强化学习，基于案例的学习，模型选择和各种模型应用。

 ◽ 统计机器学习  3学分

本课程涵盖统计学习的方法、主要软件工具及其使用。该课程通过介绍统计学习的主要思想，将帮助学生了解数据挖掘方法的基础概念。主题包括回归模型，逻辑回归，特征选择，模型选择，基数扩展和正则化，模型评估和选择；加性模型（additive models）；图形模型（graphical models），决策树，boosting模型；支持向量机（SVM）；聚类分析。

专业选修课程示例：12学分

 ◽ 高级深度学习 3学分

本课程涵盖深度学习的最新发展。课程内容包括元学习、模型压缩、联邦学习、表征学习、可解释人工智能、对抗攻防、以及深度学习理论的最新发展。

 ◽ 机器学习专题   3学分

涵盖机器学习的前沿技术，包括认知科学、迁移学习、多任务学习、主动学习、终身学习、集合学习，以及深度学习的发展。

 ◽ 人工智能专题  3学分 

人工智能的高级专题课程，包括设计领域的人工智能、金融领域的人工智能、制造领域的人工智能、医学领域的人工智能、安全和隐私领域的人工智能、智慧生活领域的人工智能、人工智能、多智能体系统、计算机博弈论。

 ◽ 贝叶斯机器学习  3学分

本课程从贝叶斯概率学的角度介绍现代机器学习技术。课程内容包括贝叶斯推断、贝叶斯线性回归、贝叶斯模型选择、贝叶斯逻辑回归、高斯过程回归、贝叶斯优化、蒙特卡罗抽样和贝叶斯深度学习。

◽ 自然语言处理  3学分

本课程将介绍句法分析、解释、上下文建模、规划识别、自然语言生成的相关技术。将重点介绍统计方法，神经心理学和语言学限制、大规模文本语料库。课程应用包括机器翻译、对话系统的建立、认知建模、和NLP 中的知识获取。

◽ 机器人学的感知和信息处理  3学分

本课程将介绍用于实现机器人感知和行为的基本理论框架、方法、概念、工具和技术，其中重点介绍这些技术在自主移动机器人上的应用。该课程从介绍贝叶斯编程和概率方法开始，后面涵盖通用机器学习，特别是深度学习方法。对于每个知识点，我们将讨论实际的案例，并指导学生对方法进行选择。课程还包括强化学习在复杂系统控制中的应用。将介绍用于移动机器人系统实验的重要的程序库。学生将有机会在真实的平台上测试他们的算法及实现。

就业前景

师资介绍

XIONG Hui

熊辉

学域主任，讲座教授

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博士毕业于明尼苏达大学双城分校计算机科学、统计学专业。AAAS会士，IEEE会士，ACM杰出科学家，人工智能·体育大数据中心主任

邮箱：xionghui@ust.hk

个人主页：https://facultyprofiles.hkust-gz.edu.cn/faculty-personal-page?id=253

Research Interests:

• Data mining and knowledge discovery

• big data analytics

• mobile computing

• business intelligence

• information assurance

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Biography:

Prof. XIONG Hui is currently the Head and Chair Professor of the Artificial Intelligece Thrust at the Hong Kong University of Science and Technology (Guangzhou).Prof. Xiong’s main research areas are data mining, business intelligence, mobile computing, and big data of human resources. He has obtained AAAS Fellow, IEEE Fellow, ACM Distinguished Scientist, Changjiang Chair Professor of the Ministry of Education of China, Overseas Jieqing B (Collaborative Research Fund for Overseas, Hong Kong and Macau Scholars) of the National Science Foundation of China, Harvard Business Review’s “2018 Ram Charan Award for Management Practices”-- Full Prize, 2017 IEEE ICDM Outstanding Service Award, ICDM-2011 Best Research Paper Award,and AAAI-2021 Best Paper Award. In terms of talent cultivation, most of the PhD supervised by Prof. Xiong have become tenure-track professors at prestigious universities in United States, including University of Tennessee-Knoxville, University of Arizona, Stony Brook University, University of Central Florida, George Mason University, City University of Hong Kong, University of Kansas and ESCP Business School-Paris.

CHEN Yingcong

陈颖聪

助理教授

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博士毕业于香港中文大学计算机科学与工程专业

邮箱：yingcongchen@ust.hk

个人主页：https://www.yingcong.me/

Research Interests:

• Computer Vision

• Machine Learning

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Biography:

Ying-Cong Chen is an Assistant Professor at AI Thrust, Information Hub of Hong Kong University of Science and Technology (Guangzhou). He is also an Affiliated Assistant Professor of the department of Computer Science & Engineering (Clear Water Bay Campus). He was a Postdoctoral Associate at Computer Science & Artificial Intelligence Lab of Massachusetts Institute of Technology, working with Prof. Dina Katabi. He obtained his Ph.D. degree from the Chinese University of Hong Kong, working with Prof. Jiaya Jia. His research lies in the broad area of computer vision and machine learning, aiming for empowering machine with the capacity to understand human appearance, physiology and psychology. His works contribute to a wide range of applications, including contactless health monitoring, semantic photo synthesis, and intelligent video surveillance.

LIU Hao

刘浩

助理教授

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博士毕业于香港科技大学

邮箱：liuh@ust.hk

个人主页：https://raymondhliu.github.io/

Research Interests:

• Data mining

• Machine learning

• Big data management

• Applications on mobile analytics and urban computing

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Biography:

Hao Liu received his Ph.D. degree from the Hong Kong University of Science and Technology (HKUST) in 2017. He is currently an assistant professor at the Artificial Intelligence Thrust, HKUST (Guangzhou), and an Affiliated Assistant Professor at the Department of Computer Science and Engineering, HKUST (Clear Water Bay).

Dr. Liu’s current research interests include spatiotemporal data mining, graph learning, reinforcement learning, and their applications on urban computing, intelligent transportation, and recommender systems.

In the past two years, he has filed over 50 Chinese/U.S. patents and published over 20 research papers at prestigious journals and conferences, such as TKDE, SIGKDD, SIGIR, WebConf, VLDB, AAAI, and IJCAI. He also regularly served as the reviewer and (senior) program committee member of many top-tier journals and conferences, such as IEEE TKDE, IEEE TITS, TRC, ACM SIGKDD, AAAI, and IJCAI. In addition, he is the organizer and questioner of the KDD Cup 2019 Machine Learning competition, which has been well-recognized as the world’s top data science competition in the past twenty years.

Many of his works have been deployed on real-world products and influenced the daily lives of millions of residents in China. For instance, the multi-modal transportation engine he proposed has been deployed on Baidu Maps and has served over five billion routing requests issued by 200 million distinct users from 2019 to 2020. For his research on intelligent transportation and urban computing, he was named in Forbes 30 Under 30 China list for science and healthcare 2021.

WANG Lin

王林

助理教授

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博士毕业于韩国科学技术院IE, CS and ME 人工智能专业

邮箱：linwang@ust.hk

个人主页：https://addisonwang2013.github.io/vlislab/linwang.html

Research Interests:

• Computer vision

• Computational photography

• Deep learning

• Intelligent systems

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Biography:

Dr. WANG Lin (Addison) is an Assistant Professor in the Artificial Intelligence (AI) Thrust of Information Hub (GZ Campus) and an Affiliate Assistant Professor in the Department of Computer Science and Engineering (CWB Campus), the Hong Kong University of Science and Technology (HKUST). He was a Postdoc researcher at the Korea Advanced Institute of Science and Technology (KAIST) from August to December 2021. Before that, he got his Ph.D. Degree (with highest Ph.D. Research Award) from KAIST, working with Prof. Kuk-Jin Yoon (KAIST) and Prof. Tae-Kyun Kim (Imperial College London). Dr. WANG had study and research experience in three Departments (Mechanical Eng., Industrial Eng., and Computer Science), and he is familiar with the inter-disciplinary research problems. His research interests lie in computer vision, computational photography, deep learning, and intelligent systems, especially self-driving cars, robotics, VR/AR, and Metaverse. His research highlights are mainly manifested in computer vision with the novel camera sensors (neuromorphic, thermal, and omnidirectional cameras), vision in all seasons, adverse vision problems, low-level vision, and visual understanding for intelligent systems. His research passion is to break the limitations of traditional RGB camera-based computer vision and make the computer vision algorithms more adaptive to tackling real-world problems.

CHEN Yize

陈绎泽

助理教授

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博士毕业于华盛顿大学电子与计算机工程专业

个人主页：https://www.yizechen.com/

Research Interests:

• Optimization and control

• Reinforcement learning

• Deep learning

• Smart grids and energy systems

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Biography:

CHEN is currently a postdoc researcher at the Berkeley Lab, working closely with Daniel Arnold and Sean Peisert. He obtained my Ph.D. in Electrical and Computer Engineering from University of Washington in 2021, advised by Baosen Zhang, and his undergraduate degrees in Automation from Chu Kochen College at Zhejiang University in 2016, working with Jiming Chen. In his research, He focuses on the intersection between control, optimization and machine learning, and he is interested in designing cyber-physical systems especially power systems with performance guarantees. He committed to achieving sustainable and autonomous clean energy systems.

He will be joining the AI Thrust, Information Hub at Hong Kong University of Science and Technology (Guangzhou) as an assistant professor in the summer of 2022, also affiliated with the Department of Computer Science and Engineering at HKUST.

He is actively looking for students working at the exciting intersections of machine learning and clean energy systems! If you are interested in working with him, please send him an email at yizechen@ust.hk. Multiple positions for funded graduate students are available for the study of machine learning, power systems, control and optimization.

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Adjunct Professors

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Co-Advisors from CWB Campus

YANG Qiang

杨强

讲座教授

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Department of Computer Science and Engineering

PhD in Computer Science at University of Maryland

邮箱：qyang@ust.hk

个人主页：http://home.cse.ust.hk/~qyang/

Research Interests:

• Artificial Intelligence

• Transfer learning

• Machine learning

• Planning

• Data mining

ZHANG Tong

张潼

讲座教授

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Department of Mathematics, Department of Computer Science and Engineering

PhD in Computer Science at Stanford University

邮箱：tongzhang@ust.hk

个人主页：https://www.math.hkust.edu.hk/people/faculty/profile/tongzhang/

Research Interests:

• Smart grids

• Networking

• Wireless networking

• Cloud/Edge computing

CAI Jianfeng

蔡剑锋

教授

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Department of Mathematics

Ph.D. in Mathematics at Chinese Univerisity of Hong Kong

邮箱：jfcai@ust.hk

个人主页：https://www.math.hkust.edu.hk/~jfcai/

Research Interests:

• Smart grids

• Networking

• Wireless networking

• Cloud/Edge computing

YAO Yuan

姚远

副教授

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Department of Mathematics, Department of Chemical and Biological Engineering

Ph.D. in Mathematics at the University of California at Berkeley

邮箱：yuany@ust.hk

个人主页：https://www.math.hkust.edu.hk/~yuany/

Research Interests:

• Topological & geometric methods in data analysis

• Statistical machine learning

• Applications in computer and life sciences

SONG Yangqiu

宋阳秋

助理教授

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Department of Computer Science and Engineering, Department of Mathematics

Ph.D., Machine Learning and Data Mining, Tsinghua University

邮箱：yqsong@cse.ust.hk

个人主页：https://www.cse.ust.hk/~yqsong/

Research Interests:

• Artificial intelligence

• Data mining

• Natural Language Processing

• Knowledge Graph

• Information Networks.

宣讲视频

署理主任寄语

Welcome to the Artificial Intelligence Thrust of Information Hub at the Hong Kong University of Science and Technology (Guangzhou). We strive to be one of the most innovative and cutting-edge places of learning and research in the world. Our mission is to pursue both fundamental research in Artificial Intelligence (AI) and applied research on a wide range of AI-enabling technologies that can help transform existing legacy applications or build new modern applications.

AI thrust is new-born and ever-growing. By inheriting HKUST’s tradition of “excellence” and “academic freedom”, our thrust has outstanding and creative faculty members with high reputation in the emerging fields of AI, such as AI for Design and Manufacture, AI for Business, AI for Finance, AI for Medicine, AI for Security, AI for Smarty Cities and AI for Smart Living. Faculty and students conducting research in these cutting-edge fields have achieved outstanding achievements and received high reputation in both academic and industrial fields, including but not limited to winning awards in numerous prestigious competitions and top-notch conferences, publishing papers in prestigious journals, as well as cooperating with well-known companies, such as Alibaba, Baidu, and Tencent.

AI is playing a more and more important role in every science and society in the world today. I invite you to explore our website at https://infh.hkust-gz.edu.cn/en/academics/ai where you will find detailed information on our academic program and personal profiles of our faculty members. We look forward to prospective students joining our thrust to conduct research for the future development in research and academic fields. No matter you are in the process of joining us or just hoping to know more about us, we welcome your invaluable thoughts and creative ideas for the future development of AI Thrust.

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编辑 | Sherry，Elise

排版 | Sherry

审核 | 蒋丽滢，Elise

特别鸣谢 | 熊辉教授