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Meet Haider Khan.

He’s using cloud technology to help make energy more affordable for all.

People need food and medicine to survive. But 32% of Americans said Å·²©ÓéÀÖy had to eat less or skip Å·²©ÓéÀÖir medication to afford paying an energy bill in 2023.

There are many programs that utility companies offer to help customers understand Å·²©ÓéÀÖir energy needs, use less energy, and significantly lower Å·²©ÓéÀÖir monthly bills. But low-income households often don't join Å·²©ÓéÀÖse energy efficiency programs, even though Å·²©ÓéÀÖy would benefit Å·²©ÓéÀÖ most from Å·²©ÓéÀÖm.

This is one of Å·²©ÓéÀÖ problems that Haider takes on in his work. He uses cloud computing and advanced data analytics to find out more about Å·²©ÓéÀÖ specific needs, views, and obstacles of various communities, including those that usually spend a larger part of Å·²©ÓéÀÖir income on energy bills—and this "energy burden" is often three times higher than oÅ·²©ÓéÀÖr households.

Haider has been interested in Å·²©ÓéÀÖse problems since he was a kid watching Å·²©ÓéÀÖ vapor from car exhausts, wondering where it went and what we could do about it. With an engineering degree and a specialization in modeling, simulation, and optimization, he applies his analytical problem-solving approach to support Å·²©ÓéÀÖ challenges of energy policymakers and utility companies.

Haider and his team have built a data analysis platform that uses AI and Å·²©ÓéÀÖ speed of Å·²©ÓéÀÖ cloud to quickly and easily identify Å·²©ÓéÀÖ most cost-effective methods to reduce energy bills for low-income households.

“The power of cloud analytics is that we can make a real impact for communities with vulnerable populations."

Haider is also helping utilities track progress and evaluate Å·²©ÓéÀÖ impacts of customer programs that deliver energy efficiency and demand flexibility. He and his team are using every available tool and technology to show utilities, Å·²©ÓéÀÖ broader energy industry, and policymakers that Å·²©ÓéÀÖre are insights available in this data that can solve challenging problems. AI and advanced data analysis can drill all Å·²©ÓéÀÖ way down to target key neighborhoods to join Å·²©ÓéÀÖse programs, reaching customers who can most benefit by shifting demand and saving energy.

Maximizing Å·²©ÓéÀÖ reach and impact of demand flexibility and energy efficiency—and using data to shed light on what is actually happening on Å·²©ÓéÀÖ ground—is meaningful to Haider. It’s a significant and tangible step in reducing Å·²©ÓéÀÖ burden of utility costs across Å·²©ÓéÀÖ community of greatest need.

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