COM2-02-65
651 63165
Daren LER
Senior Lecturer (Educator Track)Deputy Director, Centre for Nurturing Computing Excellence (CeNCE)
Director of Studies, Acacia College
Core Member, University-level Workgroup for X + AI Courses and Programmes
Vice-Chair, National Olympiad in Informatics
- PGDE (Education, National Institute of Education, Nanyang Technological University, Singapore)
- Ph.D. (Computer Science, University of Sydney, Australia)
- B.CST (Computer Science, First Class Honours, University of Sydney, Australia)
Daren Ler is a Senior Lecturer (Educator Track) in the Department of Computer Science at the National University of Singapore. His teaching and educational leadership focus on the design and evaluation of structured instructional interventions that develop student self‑efficacy and problem‑solving competence in foundational computing and artificial intelligence courses. Prior to joining NUS, he served as a Computing Teacher with Singapore’s Ministry of Education, teaching H2 Computing at National Junior College, and was awarded the Outstanding Computing Teacher Award in 2019. He is currently Vice‑Chair of the Singapore National Olympiad in Informatics, contributing to national‑level informatics education and talent development. At NUS, he has led evidence‑based pedagogical innovations, curriculum development, and educator communities through his roles as Director of Studies at Acacia College, Deputy Director (and Co-Founder) of the Centre for Nurturing Computing Excellence (CeNCE), and core member of the university‑level X+AI Workgroup. His contributions have been recognised through multiple Faculty Teaching Excellence Awards and the Annual Teaching Excellence Award.
RESEARCH AREAS
Artificial Intelligence
- Machine Learning
RESEARCH INTERESTS
Meta-learning for Algorithm Selection
Automated Machine Learning
Computing Education
Computational Thinking in Mathematics Education
RESEARCH PROJECTS
RESEARCH GROUPS
TEACHING INNOVATIONS
SELECTED PUBLICATIONS
- A. D. Dandekar, N. Lakshmanan, D. Ler, A. Y. S. Prabawa and S. Rasnayaka. (2025). Scaffolding the Problem-Solving Process for Introductory Computing Students. In IEEE Frontiers in Education Conference, 1-5.
- Chen, H., Liu, Y., Ahuja, J. K., & Ler, D. (2020). A Distance-Weighted Class-Homogeneous Neighbourhood Ratio for Algorithm Selection. In Proceedings of the 12th Asian Conference on Machine Learning, 1-16.
- Ler, D., Teng, H., He, Y., & Gidijala, R. (2018). Algorithm Selection for Classification Problems via Cluster-based Meta-features. In Proceedings of the 2018 IEEE International Conference on Big Data, Workshop on Automated Machine Learning, 4952-4960.
- Ler, D., Koprinska, I., & Chawla, S. (2005). A Hill-Climbing Landmarker Generation Algorithm Based on Efficiency and Correlativity Criteria. In Proceedings of the 18th International Florida Artificial Intelligence Research Society Conference, 418-423.
- Ler, D., Koprinska, I., & Chawla, S. (2004). A landmarker selection algorithm based on correlation and efficiency criteria. In Australasian Joint Conference on Artificial Intelligence, 296-306.
- Munro, R., Ler, D., & Patrick, J. (2003). Meta-learning orthographic and contextual models for language independent named entity recognition. In Proceedings of the Seventh Conference on Natural Language Learning, 192-195.
AWARDS & HONOURS
Faculty Teaching Excellence Award Honour Roll, 2026
Annual Teaching Excellence Award, 2025
Faculty Teaching Excellence Award 2025
Faculty Teaching Excellence Award 2024
COURSES TAUGHT
CS3243
Introduction to Artificial Intelligence
TT1003
Introduction to Computational Thinking and Problem Solving (CTPS)
UTC2851
Problem Solving for Computing and AI