Information Systems

Information Systems is about data-intensive computing for information processing and intelligence extraction to enable better decision-making and execution for complex systems in our changing society.

In order to leverage today’s rapidly-advancing technology, new generations of algorithms and technologies are applied. Systems engineers are well-trained with solid computer-related and programming knowledge for analysing and mining data, building large-scale analytic models, both stochastic and deterministic, creating algorithms for solving problems, executing large-scale simulation models, and allowing users to easily visualize and manipulate the data.

AI for Digital Health

H. Meng We are developing AI-based speech and language processing technologies for early detection of neurocognitive disorder (NCD, also known as dementia). The use of speech and language in NCD detection offers an accessible and affordable alternative...

Audio Search Engines

H. Meng Audio search engines enable us to search through the mass of audio information that is available on the internet, e.g. audio tracks of video, radio broadcasts, meeting recordings, etc. This project combines speech processing and information...

Complex Question Answering Via Reasoning Across Multiple Text Passages

W. Lam Automatic answering natural language queries or questions issued by users can facilitate the development of a wide range of intelligent applications. We intend to investigate a practical setting in which there exists a large collection of...

Computer-Aided Second Language Learning through Speech-based Human-Computer Interactions

H. Meng This initiative aims to develop speech and language technologies to support second language learning, especially for Chinese learners of English. We are developing an automatic speech recognizer that can detect and diagnose the learners’ p...

Effcient Deep Learning Algorithms For Human Language Big Data

X. Liu Human languages are natural forms of big data. Statistical language models form key components of many human language technology applications including speech recognition, machine translation, natural language processing, human computer...

Efficient Random Walk Based Query Processing on Massive Graphs

S. Wang Random walk based queries on graphs find extensive applications in search engines, social recommendations, community detection, spam detections, and so on. In the era of big data, one big challenge is how to handle the random walk based queries...

Graph Algorithms and Systems

J. Yu Graph has been widely used as a data structure to abstract complex relationships among entities. There exist many large graphs, for example, online bibliographic networks (DBLP, PubMed), online social networks (Facebook, Twitter, Flickr, LinkedIn),...

Graph data modeling and inference

H.-T. Wai Inferring graph structure from (behavioral) data is an important topic in data science as the relationship between nodes are often unknown. In this research, we develop novel graph signal processing model and inference methods with improved,...

Highly Natural Chinese Speech Synthesis with a Talking Avatar

H. Meng We are developing text-to-audiovisual-speech synthesizer that can automatically generate a synthetic speech, together with a talking avatar based on textual input. This avatar can speak in Cantonese or Putonghua. We are working on improving...

Information Mining and Discovery from Text Data

W. Lam Massive amount of information is stored in the form of texts. They can be in the form of unrestricted natural language and in different domains. Some texts are in semi-structured form such as Web pages. This project aims at developing new...

Integration of Classification and Pattern Mining: A Discriminative and Frequent Pattern-based Approach

H. Cheng Many existing classification methods assume the input data is in a feature vector representation. However, in many tasks, the predefined feature space is not discriminative enough to distinguish different classes. More seriously, in many...

Multi-modal and Trilingual Spoken Dialog Systems

H. Meng We are developing distributed spoken dialog systems that support the languages of Hong Kong (Cantonese, Mandarin and English) as well as human-computer interactions using portable PDAs and smart phones connected over a wireless network. Our...

Network Informal Language Processing

K.F. Wong Network Informal Language (NIL) refers to the language commonly used on the Internet for real-time information exchange, such as over ICQ, MSN, etc. NIL is very different from natural language. It is dynamic and anomalous in nature. We...

Social Media and e-Community Analysis

K.F. Wong Facebook, Twitter, LinkedIn, etc. are popular social media. Today, they are widely used for sharing opinions on different targets, e.g. services, products, politics etc. Social media is becoming an indispensable way of communication in our...

Temporal Information Extraction and Processing

K.F. Wong Temporal information carries information about changes and time of the changes. It is regarded as an equally, if not more, important piece of information in applications like extracting and tracking information over time or planning and evaluating...

To Support Machine Learning by Database System

J. Yu In the big data era, machine learning techniques have been extensively studied to learn new things from a huge amount of data, instead of find new things by programming. Given the goal of machine learning is to learn from data, it becomes a...