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 →

2026

Yeshwanth Cherapanamjeri

Algorithms & Statistics | Robust Machine Learning

Nanyang Asst Prof

Research focus

Designs efficient algorithms that work reliably even when data is noisy, biased, or heterogeneous
Bridges classical statistical theory with modern ML challenges like diffusion model training and language model personalisation

Research interests

Algorithmic Statistics Learning Theory Machine Learning Optimization

Education

PhD, Computer Science — UC Berkeley, 2023
B.Tech, Computer Science — IIT Bombay, 2015

Open to collaboration

Keen to collaborate across theory and practice of ML and statistics, particularly connections between statistical theory, algorithm design, and applications in the natural sciences.

Stefano Albrecht

AI Researcher | Reinforcement Learning & Multi-Agent Systems

Assoc Prof

Research focus

Develops algorithms for autonomous agents that interact robustly with humans and other agents in complex environments
Applies multi-agent RL to real-world deployments including autonomous driving and multi-robot warehouse systems

Research interests

Reinforcement Learning Multi-Agent Interaction Game Theory LLM-based Agents

Education

PhD, AI — University of Edinburgh, 2015
MSc, AI — University of Edinburgh, 2011
BSc, CS — TU Darmstadt, 2010

Open to collaboration

Open to collaborations across RL, multi-agent systems, and LLM-based agentic workflows.

Joel Quek

Educator & Researcher | AI for Finance and Education

Lecturer

Research focus

Teaches applied machine learning and data science with a strong industry lens in finance
Researches how large language models can improve industry classification and learning outcomes in CS/DS education

Research interests

AI in Education AI for Finance Learning Analytics

Education

PhD (in progress), Information Systems & Analytics — NUS
M.Comp, CS — NUS, 2019
B.Eng CS & B.Business — NTU, 2015

Open to collaboration

Happy to connect on research related to LLMs for education, finance applications, or data-driven teaching.

Hai-Dang Dau

Applied Mathematician | Bayesian Computation & Generative Modelling

Nanyang Asst Prof

Research focus

Works on sampling from complex probability distributions — the core of Bayesian inference and inverse problems
Combines classical Monte Carlo methods with modern generative modelling techniques like diffusion models

Research interests

Monte Carlo / MCMC Sequential Monte Carlo Diffusion Models Bayesian Computation

Education

PhD, Applied Mathematics — ENSAE Paris, 2022
MSc, Applied Mathematics — Ecole Polytechnique, 2019

Open to collaboration

Actively looking for collaborators in MCMC, diffusion models, Bayesian computation, and inverse problems — including protein modelling and complex physical systems.

Arne Leitert

Computer Scientist | Algorithms & Graph Theory

Senior Lecturer

Research focus

Specialises in algorithmic graph and hypergraph theory, including algorithms for huge-scale networks
Investigates how generative AI is reshaping what rigorous CS education needs to look like

Research interests

Algorithmic Graph Theory Discrete Algorithms Algorithms for Large-Scale Networks

Education

PhD, Computer Science — Kent State University, 2017
MSc, Computer Science — University of Rostock, 2012

Open to collaboration

Open to collaborations in graph algorithms and discussions on the future of CS education in the age of generative AI.

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