Infocomm Technology (ICT) is characterised by very rapid innovation cycles as well as an increasing divergence into narrow specialisations.

We work with industry at the cutting edge to drive innovation, but also a step back from the edge to research real-world solutions. Our strengths include the industry-proven nature of our research (with a large set of companies), and the ability to rapidly composite multidisciplinary teams to tackle research needs for industry. Our experts are happy to work together to solve challenging real-world problems.

In addition, we have secured substantial amounts of research funding from external parties, which is almost always enhanced by industry contribution. Many of our individual faculty work closely with industry on consultancy projects – something which is encouraged as a way of strengthening and maintaining industry relevance – while others have written textbooks or served as expert witnesses for intellectual property disputes. We deliberately formulate our research activities, where possible, to include students. This not only gives them a taste of applied industrial research but also prepares them for a future career working in related industries.

Research Groups

The ICT cluster maintains expertise across the main Computer Science and Engineering continuum with deep pockets of industry-proven capability in five distinct sub-areas characterised by our research groups:

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  • Systems
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  • Smart Healthcare
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  • Human-Computer Interaction
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  • Future Communications Systems and Networks
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  • Data Science and AI
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  • Cybersecurity
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Consultancy

Many ICT cluster faculty work closely with industry on consultancy projects – something which is encouraged as a way of strengthening and maintaining industry relevance – while others have written textbooks. served as expert witnesses for intellectual property disputes or contribute as members of technical standards committees and industry bodies.

All of our research activities aim to be applied in nature, to deliver maximum impact to companies.  We also try to include students in projects. This helps ready them for their future careers in industry, and expands the pool of high-quality work-ready graduates available to industry – as well as assisting greatly in technology transfer.

Do you have a project in mind? Reach out to our individual faculty (via research group webpages or faculty directory) to discuss the possibility of collaboration and consultancy.

Research Centres

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SIT x NVIDIA AI Centre (SNAIC)

The SIT x NVIDIA AI Centre accelerates AI adoption through expert research and development, customised AI models and advanced applications for both industry and government. The centre specialises in AI education, development and integration of AI solutions for various industries.

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Future Communications Translation Lab (FCT)

The Future Communications Translation Lab (FCTLab) at the Singapore Institute of Technology (SIT) was established to facilitate the innovation and technology translation of 5G and other future communications technologies. Its main services include Testbed-as-a-Service, Modelling & Simulation, and Use-Case Translation.

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Seminars & Conferences

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Differentially Private Publication of Smart Electricity Grid Data

 

Date/Time: 18 December 2025 10:00am
Venue: Singapore Institute of Technology, E2-04-03-SR233 
Speaker: Dr Gabriel Ghinita

Dr Gabriel will share how smart grids are a valuable data source to study consumer behaviour and guide energy policy decision. In recent years, new trends have emerged towards an increase in renewable energy sources and the development of open energy markets.

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Reimagining Tech Through Play: AI as Your Co-Designer

 

Date/Time: 11 November 2025 1:00pm
Venue: Singapore Institute of Technology, E2-02-14 (Lectorial 10)  
Speaker: Professor Lindsay Grace

Prof Lindsay Grace will share how playful design thinking enables humans and AI to co-create in dynamic, non-linear ways, driving creativity and breakthroughs in game design, computation, and human behaviour.

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BGP Anomaly Detection using Machine Learning Open configuration options

 

Date/Time: 16 October 2025 10:00am
Venue: Singapore Institute of Technology, E2-04-03-SR233 
Speaker: Dr Winston Seah

Prof Seah will explore how machine learning can enhance network anomaly detection beyond traditional security threats, addressing issues such as irregular traffic and device faults. Two applied learning approaches will be addressed: a graph-based model for detecting BGP anomalies and a hybrid online-offline framework that adapts to evolving network conditions to ensure accurate detection.