17 - 19 November, 2026
Bangkok, Thailand
David Low
Director of AI and Machine Learning
Singtel
David Low is Director of AI and Machine Learning at Singtel, where he leads a centralized AI team delivering large-scale transformation across consumer, enterprise, and network domains. Recently recognised as a Top AI Leader to Watch in 2026, he combines hands-on technical depth with organisational leadership as he shapes enterprise AI strategy.
David's career spans over 15 years across applied AI, fintech, and edtech. He co-founded Pand.ai, where he led the technical team to build NLP solutions for leading financial institutions across the region, and served as Head of Data Science at CardsPal (StanChart Ventures). He is also Chief AI Officer at HeyHi, a personalized education platform. Earlier, he held data science roles at IDA/GovTech Singapore and research positions at the Living Analytics Research Centre, a collaboration between SMU and Carnegie Mellon University.
An NUS Outstanding Young Alumni awardee (2021), David pursued PhD studies at NTU under the Alibaba-NTU Talent Program, with published work at ACL '21 on adapter-based tuning for pretrained language models. He has taught as an Adjunct Lecturer at NUS, covering deep reinforcement learning and computer vision, and served as a technical reviewer for Manning Publications.
David is a regular speaker at international conferences including Spark+AI Summit (San Francisco), PyCon Japan (Tokyo), Strata Conference (London), and AI Conference (Beijing).
Core Expertise: Machine Learning (Regression / Classification / Unsupervised learning), Deep Learning (CNN, RNN, Transformer architectures etc), Graph Analytics, Anomaly detection, Search and Recommender system, Time Series Forecasting, Statistical Analysis, Data Analytics / visualization and optimization methods.
Highly proficient and experienced in Python, R, SQL, NoSQL, Docker, Pandas, Scikit-Learn and deep learning libraries (Pytorch & Tensorflow). Hands-on experience in handling large and distributed datasets using Hive, Elasticsearch, Airflow and Spark. Familiar with interactive data visualisation tools such as Tableau, Qlikview, Plot.ly and D3.js.
Recent wins in competitions:
• 1st place in Glencore’s Zinc Recovery Optimisation Challenge
• 1st place in Alibaba-Tianchi Gridlock Prediction Challenge (re KDD Cup 2017 Task 1)
• 2nd place in OZ Minerals Explorer Challenge - Data Science Stream
David's career spans over 15 years across applied AI, fintech, and edtech. He co-founded Pand.ai, where he led the technical team to build NLP solutions for leading financial institutions across the region, and served as Head of Data Science at CardsPal (StanChart Ventures). He is also Chief AI Officer at HeyHi, a personalized education platform. Earlier, he held data science roles at IDA/GovTech Singapore and research positions at the Living Analytics Research Centre, a collaboration between SMU and Carnegie Mellon University.
An NUS Outstanding Young Alumni awardee (2021), David pursued PhD studies at NTU under the Alibaba-NTU Talent Program, with published work at ACL '21 on adapter-based tuning for pretrained language models. He has taught as an Adjunct Lecturer at NUS, covering deep reinforcement learning and computer vision, and served as a technical reviewer for Manning Publications.
David is a regular speaker at international conferences including Spark+AI Summit (San Francisco), PyCon Japan (Tokyo), Strata Conference (London), and AI Conference (Beijing).
Core Expertise: Machine Learning (Regression / Classification / Unsupervised learning), Deep Learning (CNN, RNN, Transformer architectures etc), Graph Analytics, Anomaly detection, Search and Recommender system, Time Series Forecasting, Statistical Analysis, Data Analytics / visualization and optimization methods.
Highly proficient and experienced in Python, R, SQL, NoSQL, Docker, Pandas, Scikit-Learn and deep learning libraries (Pytorch & Tensorflow). Hands-on experience in handling large and distributed datasets using Hive, Elasticsearch, Airflow and Spark. Familiar with interactive data visualisation tools such as Tableau, Qlikview, Plot.ly and D3.js.
Recent wins in competitions:
• 1st place in Glencore’s Zinc Recovery Optimisation Challenge
• 1st place in Alibaba-Tianchi Gridlock Prediction Challenge (re KDD Cup 2017 Task 1)
• 2nd place in OZ Minerals Explorer Challenge - Data Science Stream
