Title: Advanced Topics in Graph Representation Learning

Time: 02:00pm 

Venue: Online via Zoom (Registration is required - by invitation)

Speaker(s): Dr. Chao Huang, Assistant Professor, Musketeers Foundation Institute of Data Science (HKU-IDS) and Dept. of CS, HKU

Remark(s): 

The Department of Computer Science is pleased to announce the following interesting mini lecture series to be given by Dr. Chao Huang in February - April 2022. All CS RPg students and senior undergraduate students are welcome to join.

Title: Advanced Topics in Graph Representation Learning
Speaker: Dr. Chao Huang, Assistant Professor, Musketeers Foundation Institute of Data Science (HKU-IDS) and Department of Computer Science, HKU
Period: February 23 - April 6, 2022 (Wednesday) (total 5 lectures, see detailed schedule below)
Time: 2:00 pm - 3:00 pm
Venue: Online via Zoom (Registration is required - by invitation)

Description:
Graph representation learning research has grown at an incredible pace in data mining and machine learning communities. This lecture series will cover recent core techniques and advances in graph representation research for modeling a variety of real-world applications and problems, including graph representation, heterogeneous graph mining, graph neural networks, recommendation with graphs, graph-based spatial-temporal learning, and others.

About the Speaker:
Dr. Chao Huang, Assistant Professor, Musketeers Foundation Institute of Data Science (HKU-IDS) and Department of Computer Science, HKU. His research focuses on developing novel machine learning frameworks to tackle various challenges in Data Mining, Information Retrieval, Spatial-Temporal Data Analytics, User Behavior Modeling, Recommendation, Graph Mining, and Deep Representation Learning. Prior to that, he received his Ph.D. in Computer Science from the University of Notre Dame in USA.

Schedule and topics:

Lecture 1:
February 23, 2022 (Wed)
Introduction of graph mining;
Core concepts of graph representation learning/network embedding;
Heterogeneous graph analysis

Lecture 2:
March 2, 2022 (Wed)
Graph neural networks (GNN)/GNN-based applications/self-supervised graph learning

Lecture 3:
March 23, 2022 (Wed)
Recommendation with graphs I;
Social and knowledge-aware recommender systems/user personalization

Lecture 4:
March 30, 2022 (Wed)
Recommendation with graphs II;
Recommendation with behavior heterogeneity and diversity

Lecture 5:
April 6, 2022 (Wed)
Graph-based spatial-temporal learning for smart cities

Title: Elevating the human experience: XR technologies and the Metaverse

Time: 03:30pm 

Venue: Online via Zoom (Registration is required)

Speaker(s): Dr. Loretta Choi, Lecturer, Department of Computer Science, HKU

Remark(s): 

Title: Advanced Topics in Graph Representation Learning

Time: 02:00pm 

Venue: Online via Zoom (Registration is required - by invitation)

Speaker(s): Dr. Chao Huang, Assistant Professor, Musketeers Foundation Institute of Data Science (HKU-IDS) and Dept. of CS, HKU

Remark(s): 

The Department of Computer Science is pleased to announce the following interesting mini lecture series to be given by Dr. Chao Huang in February - April 2022. All CS RPg students and senior undergraduate students are welcome to join.

Title: Advanced Topics in Graph Representation Learning
Speaker: Dr. Chao Huang, Assistant Professor, Musketeers Foundation Institute of Data Science (HKU-IDS) and Department of Computer Science, HKU
Period: February 23 - April 6, 2022 (Wednesday) (total 5 lectures, see detailed schedule below)
Time: 2:00 pm - 3:00 pm
Venue: Online via Zoom (Registration is required - by invitation)

Description:
Graph representation learning research has grown at an incredible pace in data mining and machine learning communities. This lecture series will cover recent core techniques and advances in graph representation research for modeling a variety of real-world applications and problems, including graph representation, heterogeneous graph mining, graph neural networks, recommendation with graphs, graph-based spatial-temporal learning, and others.

About the Speaker:
Dr. Chao Huang, Assistant Professor, Musketeers Foundation Institute of Data Science (HKU-IDS) and Department of Computer Science, HKU. His research focuses on developing novel machine learning frameworks to tackle various challenges in Data Mining, Information Retrieval, Spatial-Temporal Data Analytics, User Behavior Modeling, Recommendation, Graph Mining, and Deep Representation Learning. Prior to that, he received his Ph.D. in Computer Science from the University of Notre Dame in USA.

Schedule and topics:

Lecture 1:
February 23, 2022 (Wed)
Introduction of graph mining;
Core concepts of graph representation learning/network embedding;
Heterogeneous graph analysis

Lecture 2:
March 2, 2022 (Wed)
Graph neural networks (GNN)/GNN-based applications/self-supervised graph learning

Lecture 3:
March 23, 2022 (Wed)
Recommendation with graphs I;
Social and knowledge-aware recommender systems/user personalization

Lecture 4:
March 30, 2022 (Wed)
Recommendation with graphs II;
Recommendation with behavior heterogeneity and diversity

Lecture 5:
April 6, 2022 (Wed)
Graph-based spatial-temporal learning for smart cities

Title: HKU-SCF High School Student Workshop Series - Digital Asset and Non-Fungible Token

Time: 02:30pm 

Venue: Online (ZOOM)

Speaker(s): Dr. Allen Au, Dept of Computer Science, HKU & Dr. John Yuen, Dept of Computer Science, HKU

Remark(s): 

Title: Mysteries of NFTs and how they shape the Metaverse

Time: 03:30pm 

Venue: Online via Zoom (Registration is required)

Speaker(s): Dr. John Yuen, Assistant Professor, Department of Computer Science, HKU

Remark(s): 

Title: Advanced Topics in Graph Representation Learning

Time: 02:00pm 

Venue: Online via Zoom (Registration is required - by invitation)

Speaker(s): Dr. Chao Huang, Assistant Professor, Musketeers Foundation Institute of Data Science (HKU-IDS) and Dept. of CS, HKU

Remark(s): 

The Department of Computer Science is pleased to announce the following interesting mini lecture series to be given by Dr. Chao Huang in February - April 2022. All CS RPg students and senior undergraduate students are welcome to join.

Title: Advanced Topics in Graph Representation Learning
Speaker: Dr. Chao Huang, Assistant Professor, Musketeers Foundation Institute of Data Science (HKU-IDS) and Department of Computer Science, HKU
Period: February 23 - April 6, 2022 (Wednesday) (total 5 lectures, see detailed schedule below)
Time: 2:00 pm - 3:00 pm
Venue: Online via Zoom (Registration is required - by invitation)

Description:
Graph representation learning research has grown at an incredible pace in data mining and machine learning communities. This lecture series will cover recent core techniques and advances in graph representation research for modeling a variety of real-world applications and problems, including graph representation, heterogeneous graph mining, graph neural networks, recommendation with graphs, graph-based spatial-temporal learning, and others.

About the Speaker:
Dr. Chao Huang, Assistant Professor, Musketeers Foundation Institute of Data Science (HKU-IDS) and Department of Computer Science, HKU. His research focuses on developing novel machine learning frameworks to tackle various challenges in Data Mining, Information Retrieval, Spatial-Temporal Data Analytics, User Behavior Modeling, Recommendation, Graph Mining, and Deep Representation Learning. Prior to that, he received his Ph.D. in Computer Science from the University of Notre Dame in USA.

Schedule and topics:

Lecture 1:
February 23, 2022 (Wed)
Introduction of graph mining;
Core concepts of graph representation learning/network embedding;
Heterogeneous graph analysis

Lecture 2:
March 2, 2022 (Wed)
Graph neural networks (GNN)/GNN-based applications/self-supervised graph learning

Lecture 3:
March 23, 2022 (Wed)
Recommendation with graphs I;
Social and knowledge-aware recommender systems/user personalization

Lecture 4:
March 30, 2022 (Wed)
Recommendation with graphs II;
Recommendation with behavior heterogeneity and diversity

Lecture 5:
April 6, 2022 (Wed)
Graph-based spatial-temporal learning for smart cities

Title: Advanced Topics in Graph Representation Learning

Time: 02:00pm 

Venue: Online via Zoom (Registration is required - by invitation)

Speaker(s): Dr. Chao Huang, Assistant Professor, Musketeers Foundation Institute of Data Science (HKU-IDS) and Dept. of CS, HKU

Remark(s): 

The Department of Computer Science is pleased to announce the following interesting mini lecture series to be given by Dr. Chao Huang in February - April 2022. All CS RPg students and senior undergraduate students are welcome to join.

Title: Advanced Topics in Graph Representation Learning
Speaker: Dr. Chao Huang, Assistant Professor, Musketeers Foundation Institute of Data Science (HKU-IDS) and Department of Computer Science, HKU
Period: February 23 - April 6, 2022 (Wednesday) (total 5 lectures, see detailed schedule below)
Time: 2:00 pm - 3:00 pm
Venue: Online via Zoom (Registration is required - by invitation)

Description:
Graph representation learning research has grown at an incredible pace in data mining and machine learning communities. This lecture series will cover recent core techniques and advances in graph representation research for modeling a variety of real-world applications and problems, including graph representation, heterogeneous graph mining, graph neural networks, recommendation with graphs, graph-based spatial-temporal learning, and others.

About the Speaker:
Dr. Chao Huang, Assistant Professor, Musketeers Foundation Institute of Data Science (HKU-IDS) and Department of Computer Science, HKU. His research focuses on developing novel machine learning frameworks to tackle various challenges in Data Mining, Information Retrieval, Spatial-Temporal Data Analytics, User Behavior Modeling, Recommendation, Graph Mining, and Deep Representation Learning. Prior to that, he received his Ph.D. in Computer Science from the University of Notre Dame in USA.

Schedule and topics:

Lecture 1:
February 23, 2022 (Wed)
Introduction of graph mining;
Core concepts of graph representation learning/network embedding;
Heterogeneous graph analysis

Lecture 2:
March 2, 2022 (Wed)
Graph neural networks (GNN)/GNN-based applications/self-supervised graph learning

Lecture 3:
March 23, 2022 (Wed)
Recommendation with graphs I;
Social and knowledge-aware recommender systems/user personalization

Lecture 4:
March 30, 2022 (Wed)
Recommendation with graphs II;
Recommendation with behavior heterogeneity and diversity

Lecture 5:
April 6, 2022 (Wed)
Graph-based spatial-temporal learning for smart cities

Title: Career Talk: How to build up your career in a digital era?

Time: 05:30pm 

Venue: Via Zoom (Registration is required - by invitation)

Speaker(s): Mr. John Li, Vice President (Member Services), Hong Kong Computer Society

Remark(s): 

Title: A Secondary Partitioning Technique for Indexing Multidimensional Ranges

Time: 02:00pm 

Venue: Via Zoom (Registration is required)

Speaker(s): Professor Nikos Mamoulis, Dept of Computer Science and Engineering, University of Ioannina

Remark(s): 

Title: Advanced Topics in Graph Representation Learning

Time: 02:00pm 

Venue: Online via Zoom (Registration is required - by invitation)

Speaker(s): Dr. Chao Huang, Assistant Professor, Musketeers Foundation Institute of Data Science (HKU-IDS) and Dept. of CS, HKU

Remark(s): 

The Department of Computer Science is pleased to announce the following interesting mini lecture series to be given by Dr. Chao Huang in February - April 2022. All CS RPg students and senior undergraduate students are welcome to join.

Title: Advanced Topics in Graph Representation Learning
Speaker: Dr. Chao Huang, Assistant Professor, Musketeers Foundation Institute of Data Science (HKU-IDS) and Department of Computer Science, HKU
Period: February 23 - April 6, 2022 (Wednesday) (total 5 lectures, see detailed schedule below)
Time: 2:00 pm - 3:00 pm
Venue: Online via Zoom (Registration is required - by invitation)

Description:
Graph representation learning research has grown at an incredible pace in data mining and machine learning communities. This lecture series will cover recent core techniques and advances in graph representation research for modeling a variety of real-world applications and problems, including graph representation, heterogeneous graph mining, graph neural networks, recommendation with graphs, graph-based spatial-temporal learning, and others.

About the Speaker:
Dr. Chao Huang, Assistant Professor, Musketeers Foundation Institute of Data Science (HKU-IDS) and Department of Computer Science, HKU. His research focuses on developing novel machine learning frameworks to tackle various challenges in Data Mining, Information Retrieval, Spatial-Temporal Data Analytics, User Behavior Modeling, Recommendation, Graph Mining, and Deep Representation Learning. Prior to that, he received his Ph.D. in Computer Science from the University of Notre Dame in USA.

Schedule and topics:

Lecture 1:
February 23, 2022 (Wed)
Introduction of graph mining;
Core concepts of graph representation learning/network embedding;
Heterogeneous graph analysis

Lecture 2:
March 2, 2022 (Wed)
Graph neural networks (GNN)/GNN-based applications/self-supervised graph learning

Lecture 3:
March 23, 2022 (Wed)
Recommendation with graphs I;
Social and knowledge-aware recommender systems/user personalization

Lecture 4:
March 30, 2022 (Wed)
Recommendation with graphs II;
Recommendation with behavior heterogeneity and diversity

Lecture 5:
April 6, 2022 (Wed)
Graph-based spatial-temporal learning for smart cities