Conducting High Impact Research


The Department is committed to conducting impactful multi-disciplinary research through recognising our strategic strengths and pooling talents. To further advance our research and spearhead innovative across disciplines, an array of initiatives which include strengthening international exposure and pursing international scholarly recognition, fostering a more open and supportive research culture, increasing engagement of multi-disciplinary research, recruiting and retaining high-caliber staff are well introduced.


The Department is proud to count among our faculty and they contribute fundamentally to our success.



Subject Rankings

#3

CS Citations in Hong Kong


#23

CS in Asia


#101-125

CS in World




Source: CSRankings

Aritifical Intelligence (2018-2020)

#3

Hong Kong


#25

Asia


#60

World


Databases* (2018-2020)

#3

Hong Kong


#10

Asia


#43

World


*including SIGMOD/VLDB/ICDE/PODS

Funding (2017-2020)

The Department has secured significant amount of research funds in the past 4 years. The funding solidifies our research strengths and recognises our efforts in creating impactful innovative research.



Funding Schemes
No. of Funded Project(s)
Collaborative Research Fund (CRF) 1
General Research Fund (GRF) 17
Early Career Scheme (ECS) 4
Research Impact Fund (RIF) 3
Innovation and Technology Fund (ITF) 1
National Natural Science Foundation of China (NSFC) 5
Others 7
Total   38

Editorships

IEEE Access

Prof. CHU, Xiaowen
Associate Editor

Machine Learning

Dr. Bo Han
Leading Guest Editor

Pattern Recognition

Prof. CHEUNG, Yiu MingProf. YUEN, Pong Chi
Editorial Board MemberEditorial Board Member


Information as at 11 August 2021


Supportive Research Facilities

The Department strongly believes that the significance of up-to-date research facilities as a pre-requisite for top research and teaching.  High-performance computing facilities, like FAT CPU, FAT GPU servers and GPU clusters are well equipped to enhance our research capabilities and meet ever-expanding research need on artificial intelligence and big data.




List of high-performance computing facilities:


4 FAT CPU servers

4 FAT GPU servers, each with 4 Nvidia V100 GPUs and 1TB RAM

Four GPU clusters:
Cluster 1: 8 GPU nodes, each with two Nvidia Tesla K80
Cluster 2: 4 GPU nodes, each with two Nvidia Tesla P40
Cluster 3: 5 GPU nodes, each with four Nvidia Tesla V100
Cluster 4: 6 GPU nodes, each with four Nvidia Tesla V100

One big-data cluster: 10 servers, each with dual 6-core Intel Xeon CPUs