RESEARCH

We work on almost all areas of AI foundations including modeling and representation, reasoning and planning, machine learning and data science, computer vision and natural language processing as well as learning theory.

Embodied AI

A general intelligent agent needs to act effectively in the real world. Embodiment is also arguably necessary for achieving general intelligence. Our research into embodiment include work on mobile robots, autonomous cars, drones, as well as on manipulation in real physical and virtual simulated environments.

Interactive AI

In our vision, AI should work for people, and alongside people. AI should be able to understand people in order to help us achieve our goals. When humans and AI are able to work well together, the effectiveness often multiplies, outperforming what is achievable otherwise.

Trustworthy AI

AI systems are being deployed at an accelerating rate. With deployment, it is our responsibility to ensure that human lives are not adversely affected. Issues such as fairness, transparency, accountability, explainability and robustness are part of our main focus.

Projects

All
Recent Projects
Industry Engagement
Embodied AI
Interactive AI
Trustworthy AI
Intelligent Systems in Balance Sheet Forecasting

Intelligent Systems in Balance Sheet Forecasting

Investigator: Keith Carter. Balance Sheet is one of the vital financial elements which displays the health of any organization and is often called “statement of financial position”.  For this project, […]

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AI Governance

AI Governance

Investigator: Atreyi Kankanhalli. As we race forward into the digital age, and with the increasing capacity of computers to process vast amounts of data for a variety of complex tasks, […]

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AI That Understand Human Emotions and Intentions

AI That Understand Human Emotions and Intentions

Investigator: Desmond Ong. When we think of AI today, we might think of them as cold and “robotic”, and might not be able to imagine them being empathetic, understanding, and […]

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Occupational Impact of AI

Occupational Impact of AI

Investigator: Huang Ke-Wei. With the rapid advances of artificial intelligence (AI), increasingly more job tasks can be automated and all occupations more or less have job tasks being automated by […]

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Smart Cognitive Impairment Screening Tool

Smart Cognitive Impairment Screening Tool

Investigator: Teo Hock Hai.   In this project, we develop a digitalized screening tool sensitive enough to detect early cognitive impairment. The tool incorporates an artificial intelligence pattern recognition algorithm […]

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Integrating Deep Learning, Statistical Models and Structured Representations

Integrating Deep Learning, Statistical Models and Structured Representations

Investigator: Stanley Kok. Deep learning, statistical models and structured representations are cornerstones of artificial intelligence (AI). They each have their unique strengths and weaknesses, and separately, they have found numerous […]

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Transfer Learning in Dynamic Environments

Transfer Learning in Dynamic Environments

Investigator: Leong Tze Yun. How can an AI agent focus attention in a complex, unknown environment for decision making? We investigate the use of context-sensitive transfer learning in hierarchical reinforcement […]

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Rationalizing Deep Learning Model Decisions

Rationalizing Deep Learning Model Decisions

Investigator: Wynne Hsu. Deep learning has remarkable performance in many applications. But can we really trust the decision of deep learning systems? The goal of this project is to build […]

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Neuralizing Algorithms

Neuralizing Algorithms

Investigator: Lee Wee Sun. Most AI problems are computationally intractable in the worst case. The typical or average case could be much easier but is difficult to design for. We […]

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Emotion AI

Emotion AI

Investigator: Stefan Winkler. We analyse emotions from facial expressions and other cues. We provide valence/arousal representation of emotions (continuous, 2D). The system was trained & tested with dataset of 100,000+ […]

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Bayesian Optimization Lower Bounds

Bayesian Optimization Lower Bounds

Investigator: Jonathan Scarlett. Black-box function optimization via expensive noisy samples have diverse applications in problems such as hyperparameter tuning, robotics, and molecular design. Various algorithms have previously been proposed with […]

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Tactile Learning & Perception

Tactile Learning & Perception

Investigator: Harold Soh. The ability of humans to navigate our environment is heavily dependent on the quality and speed of sensing. Tactile sensing, or the sensation of touch and pressure, […]

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Artificial Theories of Mind & Body

Artificial Theories of Mind & Body

Investigator: Harold Soh. The principal aim of this project is to develop core techniques for learning models of other (human) agents: Artificial Theories of Mind and Body (AToM/B). We intend […]

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Decentralized Federated Learning

Decentralized Federated Learning

Investigator: Bryan Low. How can multiple data owners collectively learn and fuse their ML models? We present two approaches. In the first work, we presents a novel Collective Online Learning […]

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Self-Supervised Hand Pose Estimation

Self-Supervised Hand Pose Estimation

Investigator: Angela Yao. We aim to bridge data-driven discriminative hand pose estimation with optimization-based model-fitting.  Using a differentiable hand renderer that aligns estimates by comparing the rendered and input depth […]

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Clinical Data Analytics

Clinical Data Analytics

Investigator: Vaibhav Rajan. The increasing availability of digitized clinical data presents an unprecedented opportunity to study and gain deeper understanding of diseases, develop new treatments and improve healthcare ecosystems, and […]

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Implications of Real-time Competition in Online Markets

Implications of Real-time Competition in Online Markets

Investigator: Chen Nan. In the age of market digitalization, competition becomes increasingly dynamic. Airlines adopt sophisticated revenue management systems that enable real-time price adjustments. Small online sellers have access to […]

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Retina Images for Diabetic Retinopathy and Glaucoma

Retina Images for Diabetic Retinopathy and Glaucoma

Investigators: Wynne Hsu and Lee Mong Li. A deep learning-based screening system that examines retinal fundus photographs for various eye conditions, including diabetic retinopathy, age-related macular degeneration (AMD) and glaucoma. […]

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