Health.AI Leadership Executive (HALE) Masterclass

Overview

The Health.AI Leadership Executive (HALE) Masterclass offers an exceptional learning journey designed for executives at the forefront of healthcare, MedTech, policy and beyond. This programme uniquely bridges the rapidly evolving fields of artificial intelligence and health innovation with the critical skills of strategic leadership. Tailored for a diverse audience, HALE equips professionals with the knowledge and frameworks necessary to not only understand the transformative potential of AI but also to effectively implement it within their organizations and across the broader health ecosystem, driving meaningful impact.

Participants in the HALE Masterclass will delve into the strategic applications of AI within healthcare and related sectors through carefully structured modules. Beyond the technical aspects, the program places significant emphasis on the ethical considerations and essential leadership capabilities required to navigate the complexities of AI integration in healthcare environments. By focusing on real-world implementation and strategic decision-making, HALE empowers executives to lead AI initiatives with confidence, drive impactful outcomes, and position their organizations as leaders in healthcare innovation.

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Core Focus

By the end of the workshop, you will be able to -

Lead with Confidence in AI Transformation: Learn to lead AI initiatives with confidence, guided by exclusive insights from top AI strategists and healthcare innovators.

Drive Strategic Outcomes: Walk away with actionable AI strategies tailored for decision-makers, covering Generative AI, Predictive Health, diagnostics, and operational efficiency.

Stay Ahead of the Curve: Equip yourself with the latest knowledge on LLMs, automation, and AI-driven risk assessment — built for real-world digital health applications.

Forge High-Impact Connections: Connect with AI pioneers, forward-thinking investors, and a cross-sector network of decision-makers and policymakers.

Reimagine Healthcare with AI: Discover how AI can transform healthcare delivery, enable smarter decisions, and drive measurable outcomes — positioning your organisation as a leader in innovation.

Learn Through Experience: Enjoy a curated learning journey that blends strategic depth with practical, real-world application.

By joining HALE, participants will gain not only the technical insights to drive AI transformation but also the strategic acumen needed to elevate their organisations in an increasingly digital health landscape.

Speakers / Professors

Name

Designation

Biography

Adjunct Professor Ngiam Kee Yuan

Head, Division of Biomedical Informatics, NUS Medicine

Head, AI Office, NUHS

Adjunct Professor, Department of Surgery, NUS Medicine

Adj Prof Ngiam is a Senior Consultant at the Division of General Surgery (Thyroid & Endocrine Surgery) at the National University Hospital, specialising in Thyroid and Endocrine surgical disorders. Following the completion of his Advanced Specialist Training in General Surgery, he was awarded a fellowship from the Royal College of Surgeons of Edinburgh and was accredited as a surgical specialist by the Specialist Accreditation Board, Singapore in 2012. He received the Higher Manpower Development Program Award in 2012 to complete a Fellowship in Metabolic and Endocrine Surgery in Taiwan. He received further training in robotic thyroid surgery at the Seoul National University Hospital, South Korea.

Adj Prof Ngiam’s special interests are in thyroid and endocrine surgery, robotic thyroid surgery, bariatric and metabolic surgery, advanced endoscopy and laparoscopic surgery. He was awarded the ExxonMobil-NUS Research Fellowship for Clinicians in 2007 and his research interests include parathyroid surgery, robotic thyroid surgery, obesity surgery for type 2 diabetes and thyroid cancer surgery.

Professor Dean Ho

Head, Department of Biomedical Engineering

Prof Dean Ho is currently Provost’s Chair Professor and Head of the Department of Biomedical Engineering in the College of Design and Engineering, Director of The Institute for Digital Medicine (WisDM) at the Yong Loo Lin School of Medicine, and Director of The N.1 Institute for Health (N.1) at the National University of Singapore.

He and collaborators successfully developed and validated CURATE.AI, a powerful artificial intelligence platform that personalizes human treatment for a broad spectrum of indications ranging from oncology, to digital therapeutics and infectious diseases, among others. His team also developed IDentif.AI to optimise combination therapy design against SARS-CoV-2 and to address antimicrobial resistance. Recently, his team unveiled WisDM Green, a technology platform to sustainably address food security and optimise yield while preserving nutritional content.

Ban Hon Kim, Kenneth

Associate Professor Kenneth Ban

Associate Professor, Department of Biochemistry, NUS Yong Loo Lin School of Medicine

Assoc Prof Kenneth obtained his BSc (Hons) in Biochemistry and MBBS degrees from the National University of Singapore (NUS) and a PhD in Cancer Biology from Stanford University. He completed his postdoctoral training in mouse cancer genetics at the Institute of Molecular and Cell Biology (IMCB) Singapore before joining the Department of Biochemistry at NUS.

He also serves as the Program Director for Health/Biomedical and Life Sciences at the National Supercomputing Centre (NSCC) Singapore. His research and education interests are in cancer genetics, high-performance computing for precision medicine, and the development of technology-enhanced learning platforms for medical and health/bioinformatics education.

Associate Professor Feng Mengling

Associate Professor and Director, AI for Public Health (AI4PH), Saw Swee Hock School of Public Health

Assoc Prof Feng is currently a faculty member at Saw Swee Hock School of Public Health and also the Assistant Director of Research at Institute for Data Science at NUS. He is also the Senior Assistant Director of National University Hospital, championing big data analytics and healthcare AI initiatives.

His research is in the development of machine learning algorithms to extract actionable knowledge from large amount of data to enable better quality of healthcare. This research brings together concepts and tools across deep learning, optimization, signal processing, statistical causal inference and big data management.

Prof Feng’s work was recognized by both well-established journals, such as Science Translational Medicine, JAMA and top international conferences, such as KDD, AAAI and AMIA.

Past Editions

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2025

Over three transformative days, healthcare, MedTech, and policy leaders from across Asia came together to explore how AI can enable smarter, more ethical, and strategic healthcare systems.

From digital transformation and data-driven strategies to real-world AI applications and ethical decision-making, HALE 2025 was a convergence of insights, innovation, and leadership. Check out the video recap for highlights of the latest edition of HALE.

2022

2021

2020