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Dr. Serena Huang

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Dr. Serena Huang

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Analytics Executive Data With Serena

Dr. Serena H. Huang works with F500 companies to drive meaningful GenAI transformation by focusing on strategic adoption, workforce readiness, and human-centered implementation. A Wiley author of “The Inclusion Equation: Leveraging Data & AI For Organizational Diversity and Well-being', she also regularly guest lectures at top MBA programs including Kellogg, Wharton, and Haas. Her GenAI expertise has been featured in Fast Company, Barron’s, MarketWatch, Yahoo Tech, CNET, and the Chicago Tribune in 2025, and her keynote talks inspire thousands of leaders around the world each year. Prior to founding Data With Serena, Dr. Huang led sizable analytics teams at prominent organizations including PayPal, Kraft Heinz, GE, and Koch Industries. She pioneered the applications of machine learning algorithms to predict absenteeism and turnover and led corporate councils for Ethical AI in these global organizations.

Bio from: Big Data LDN 2025

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As populations age and healthcare systems strain under growing demand, AI is emerging as a vital force for innovation. From predictive health models to AI-powered caregiver assistants and conversational companions, data-driven tools are increasingly supporting elder care. But the rise of the “AI nurse” presents a profound challenge: How do we innovate responsibly while preserving human dignity and empathy?

In this session, Dr. Serena Huang explores the practical and ethical dimensions of applying AI in elder care. This talk bridges the gap between technical development and compassionate delivery, highlighting the critical role data professionals play in building trustworthy, equitable systems for vulnerable populations.

In this session, you will learn:

- How AI and predictive models can address workforce shortages and rising care needs in aging populations.

- How to design systems where AI handles data-heavy tasks while freeing up human caregivers for high-touch, empathetic care.

- Key principles for developing ethical, inclusive, and transparent AI systems that protect privacy and reduce bias.