Meet Our New Faculty | CCDS NTU Singapore | College of Computing and Data Science

The College of Computing and Data Science (CCDS) at NTU Singapore has welcomed a growing cohort of faculty since 2024, whose work spans artificial intelligence, systems, data science, and the digital economy. Together, they strengthen the College's research depth and expand how computing is taught, studied, and applied.

2026 → 2025 → 2024 →

2025

Jayne Thompson

Quantum Computing Researcher | Quantum Algorithms & Information Theory

Assoc Prof

Research focus

Designs quantum agents and algorithms that outperform classical approaches — sometimes exponentially so
Explores how quantum computing can power sequence models, machine learning, and structured data analysis

Research interests

Quantum Algorithms Quantum Information Theory Quantum Machine Learning

Education

PhD, Theoretical Physics — University of Melbourne, 2012
BSc, Pure Mathematics — University of Melbourne, 2008

Open to collaboration

Interested in all things information theory, statistics, and mathematical learning theory. Also keen to explore classical algorithms that could inspire new quantum methods.

Rob Cornish

Machine Learning Researcher | Generative Models & Uncertainty

Nanyang Asst Prof

Research focus

Builds ML systems with formal mathematical guarantees, specialising in generative models and causal inference
Works on geometric deep learning and uncertainty quantification with applications to healthcare and digital twins

Research interests

Generative Models Geometric Deep Learning Uncertainty Quantification Causal Inference

Education

DPhil, Machine Learning — University of Oxford, 2020
BSc (Hons), Applied Mathematics — Monash University, 2015

Open to collaboration

Open to collaborations on robust and reliable ML, generative models, and causal inference.

Lu Wei

NLP Researcher | Large Language Models

Professor

Research focus

Studies fundamental problems in natural language processing and large language models, with a focus on multilingual systems
Leads a S$4.9M national project developing LLM architectures optimised for regional languages

Research interests

Natural Language Processing Large Language Models Multilingual AI

Education

PhD, Computer Science — NUS (Singapore-MIT Alliance), 2009
MSc — NUS, 2006
BComp (Hons I) — NUS, 2005

Open to collaboration

Keen to collaborate on LLMs, particularly small models, multimodality, agentic systems, interpretability, and responsible AI.

Sean Xuefeng Du

ML Researcher | Reliable & Trustworthy AI

Asst Prof

Research focus

Studies how ML models fail when facing unfamiliar inputs — and designs principled methods to make them more reliable
Works on out-of-distribution detection and hallucination detection for large language models and foundation models

Research interests

Reliable Machine Learning Uncertainty Quantification Foundation Model Safety

Education

PhD, Computer Science — University of Wisconsin-Madison, 2025
BSc, Electrical Engineering — Xi'an Jiaotong University, 2020

Open to collaboration

Interested in collaborations on trustworthy AI, OOD robustness, and safe deployment of foundation models.

Wang Qichen

Database Researcher | Query Optimization & Data Privacy

Asst Prof

Research focus

Designs theoretically optimal algorithms for efficient and scalable database query processing under real-world constraints
Applies rigorous lower-bound theory to guide privacy-preserving and distributed query computation

Research interests

Database Theory Query Optimization Data Privacy Distributed Computation

Education

PhD, Computer Science — HKUST, 2022
BSc, CS — Zhejiang University, 2017

Open to collaboration

Happy to chat about query evaluation, data privacy, or distributed systems — drop by anytime.

Jaehong Yoon

AI Researcher | Multimodal & Continual Learning

Asst Prof

Research focus

Builds trustworthy AI systems that understand video, language, and multiple modalities in dynamic real-world settings
Focuses on AI that can continuously adapt and self-improve over time rather than becoming stale after training

Research interests

Multimodal Video Reasoning Continual & Lifelong Learning Trustworthy AI Embodied AI

Education

PhD, School of Computing — KAIST, 2023
MSc — UNIST, 2018
BSc — UNIST, 2016

Open to collaboration

Interested in collaborations applying multimodal AI, continual learning, or trustworthy AI to real-world problems including medical AI.

Wang Chen

Systems Researcher | High-Performance Computing & Storage

Asst Prof

Research focus

Builds next-generation storage systems and parallel file systems that power supercomputers and large-scale AI training
Develops tools to trace, analyse, and optimise I/O performance in HPC and deep learning workflows

Research interests

High-Performance Computing Parallel Storage Systems HPC for AI Performance Optimization

Education

PhD, Computer Science — UIUC, 2022
MSc — Tianjin University, 2017
BSc — Hainan University & Tianjin University, 2014

Open to collaboration

Extensive experience with application users, domain scientists, and AI researchers — always eager to explore new HPC collaborations.

Pranjal Dutta

Theoretical Computer Scientist | Algorithms & Complexity

Nanyang Asst Prof

Research focus

Investigates fundamental questions at the intersection of mathematics and computation, including polynomial algorithms and coding theory
Works on randomised and algebraic algorithms and their connections to cryptography and computational learning theory

Research interests

Computational Complexity Randomised Algorithms Coding Theory Cryptography

Education

PhD, CS — Chennai Mathematical Institute, 2022 (Google PhD Fellow)
MSc — Chennai Mathematical Institute, 2018
BSc — Chennai Mathematical Institute, 2016

Open to collaboration

Open to collaborations in theoretical CS, algorithms, and the mathematical foundations of computation.

Chloe Gu

Data & Product Leader | AI in Industry

Senior Lecturer

Research focus

Brings 20 years of industry experience in data-driven product development across banking, fintech, and e-commerce
Teaches data science and analytics bridging foundational concepts to real-world production systems

Research interests

Digital Product Management Data Science & ML AI in Product Management Data Analytics

Education

PhD, Computer Science — NUS, 2008
MSc — Zhejiang University, 2002
BSc — Zhejiang University, 1999

Open to collaboration

Open to applied research collaborations bridging industry practice and academic rigour in data science and AI.

Yewen Pu

AI Researcher | Human-AI Collaboration & Code Generation

Nanyang Asst Prof

Research focus

Builds datasets and agents that can follow natural language instructions as reliably and intuitively as a human would
Develops code generation systems and multi-turn communication frameworks for complex design and engineering tasks

Research interests

Human-AI Collaboration Natural Language Grounding Code Generation Embodied Agents

Education

PhD, Computer Science — MIT
MSc — MIT
BSc, Mathematics & CS — UC Berkeley

Open to collaboration

Interested in language instruction to geometry generation, instruction-following agents, dataset curation, and general code generation.

Mengmi Zhang

Computational Neuroscientist | Brain-Inspired AI

Nanyang Asst Prof

Research focus

Studies how the brain processes vision, attention, and memory — and uses these insights to improve AI models
Develops AI tools to support human cognition including attention, generalisation, and continual learning

Research interests

Computational Neuroscience Visual Attention & Eye Movements Out-of-Distribution Generalisation Continual Learning

Education

PhD, Computational Neuroscience & AI — NUS, 2019
PhD (Visiting) — Harvard Medical School, 2018
BEng (1st Class Hons), ECE — NUS, 2015

Open to collaboration

Interested in problems bridging human cognitive processes and machine learning — especially learning from sparse data and dynamic visual scenes.

Alan Chau

Statistician | Uncertainty-Aware Machine Learning

Asst Prof

Research focus

Develops methods that bring genuine uncertainty-awareness into ML systems, drawing on kernel methods and imprecise probability
Applies these techniques to model explainability, sequential experimental design, and group decision-making

Research interests

Uncertainty Quantification Kernel Methods Gaussian Processes Explainability

Education

DPhil, Statistical ML — University of Oxford, 2023
MMath — University of Oxford, 2018
BA, Mathematics & Statistics — University of Oxford, 2017

Open to collaboration

Open to collaborations involving uncertainty quantification, explainability, and decision-making under ambiguity.

Yoonchang Sung

Robotics Researcher | Task Planning & Embodied AI

Asst Prof

Research focus

Designs algorithms that enable robots to plan and execute complex long-horizon tasks by learning from past experience
Works on diffusion-based planning models and multi-robot teamwork, including adapting to unknown agent behaviours

Research interests

Robotics Embodied AI Task & Motion Planning Robot Foundation Models

Education

PhD, Electrical & Computer Engineering — Virginia Tech, 2019
MSc — Korea University, 2013
BSc — Korea University, 2011

Open to collaboration

Keen to build collaborations within CCDS — always interested if your research could connect to robotics.

Yuxuan Du

Quantum-AI Researcher | Quantum Machine Learning

Asst Prof

Research focus

Bridges quantum computing and AI — using quantum resources to enhance learning and AI to advance quantum technologies
Works on quantum learning theory, architecture search, and AI-driven tools for quantum science

Research interests

Quantum Machine Learning Quantum Learning Theory AI for Quantum Science

Education

PhD, Computer Science — University of Sydney, 2021
MSc — University of Sydney, 2018
BSc, Physics — Sichuan University, 2015

Open to collaboration

Excited to collaborate at the intersection of quantum computing and AI — particularly on quantum algorithms, learning theory, and quantum science applications.

Atsushi Nitanda

Machine Learning Theorist | Optimization & Deep Learning Theory

Assoc Prof

Research focus

Develops provably efficient algorithms for training AI systems with rigorous mathematical guarantees
Researches why deep learning works — tackling fundamental questions about convergence, generalisation, and overparameterisation

Research interests

Stochastic Optimization Distribution Optimization Statistical Learning Theory Theory of Post-Training

Education

PhD, Information Science — University of Tokyo, 2018
MSc — University of Tokyo, 2009
BSc, Mathematics — Sophia University, 2007

Open to collaboration

Interested in collaborations on the mathematical foundations of machine learning, deep learning theory, and optimization.

Samantha Chan

HCI Researcher | Cognitive Enhancement & Wearables

Asst Prof

Research focus

Designs digital, wearable, and AI interfaces that support human memory, attention, sleep, and healthy ageing
Develops brain-computer interfaces and extended reality (XR) applications to enhance human cognitive potential

Research interests

Human-Computer Interaction Cognitive Enhancement Wearables Brain-Computer Interfaces

Education

PhD, Bioengineering — University of Auckland, 2022
BEng, Electrical Engineering — SUTD, 2016

Open to collaboration

Open to collaborations on wearable tech, cognitive AI interfaces, and human-centred computing.

Daniel Paulin

Statistician | Monte Carlo Methods & Uncertainty Quantification

Assoc Prof

Research focus

Develops scalable Monte Carlo algorithms for Bayesian inference and uncertainty quantification in AI
Works on rigorous probabilistic bounds and convergence guarantees for sampling methods used in machine learning

Research interests

Monte Carlo Methods Uncertainty Quantification Scalable Algorithms Statistical Machine Learning

Education

PhD, Mathematics — NUS, 2014
MSc, Engineering — Ecole Centrale Paris, 2009
BSc, Physics — Budapest University of Technology, 2009

Open to collaboration

Looking forward to new collaborations in CCDS — particularly in Monte Carlo, uncertainty quantification, and statistical learning.

Quick links

Get in touch

Connect with us