At Google Cloud, Valerie Hyde (M.S. ’05, Ph.D. ’07, applied mathematics & statistics, and scientific computation) taps into cutting-edge technologies to take business enterprises into the future.
Whether it’s making sure a virtual agent gets a customer’s drive-thru burger order right or helping an online shopper find that flowered dress they’re looking for, Valerie Hyde (M.S. ’05, Ph.D. ’07, applied mathematics & statistics, and scientific computation) is all about problem-solving for businesses—and doing it with next-generation technologies like artificial intelligence (AI).
For the past five years, as head of the North American Artificial Intelligence Customer Engineering team at Google Cloud, Hyde has tapped into the power of technologies like AI and machine learning to tackle big and small challenges for businesses, drawing from her 20 years of experience at companies including Microsoft, SAS and IBM.
It’s not where she thought statistics would take her 20 years ago—it’s better.
“I never could have imagined this. Sometimes I can't believe that I get to do what I'm doing at this time in history at such an innovative company,” Hyde reflected. “For so many years, it seemed like only a small group of people really cared about statistics and data science, but now everybody is doing AI, and it's really people interacting with technology.”
From math to statistics
For as long as Hyde can remember, math and science were always a part of life.
“I was always surrounded by it—both of my parents were professors at state schools in New York—my dad was a chemistry professor, and my mom was a computer science professor,” Hyde explained. “I always liked math the most in school, even more than science, because there were problems that I could solve definitively. That gave me a lot of confidence in my ability to solve problems and think logically.”
As an undergraduate majoring in mathematics and economics at Binghamton University in New York, Hyde discovered that the math classes she liked best focused on statistics. By the time she earned her degree in 1998, she knew that applying math to solve real-world business problems was something she wanted to do.
She landed a job with the antitrust group at the U.S. Department of Justice, where she found herself working on a high-profile case that was getting plenty of attention.
“I used math and programming to help the government quantify its antitrust cases,” she recalled. “The case that people may remember was when the Justice Department sued Microsoft over packaging its Internet Explorer browser with its Windows operating system.”
Though Hyde was working full time, she was still thinking about graduate school—and getting some gentle encouragement from her father.
“Pretty much every call with my dad was, ‘When are you going to go back to school? When are you going to get a higher degree?’ I felt like that was what I was supposed to do,” Hyde recalled. “Both my parents are Ph.D.s, and I think my dad envisioned that I would do that as well. He wanted to make sure that I was always in a stable position, which is possible with advanced degrees in math and science.”
In 2002, Hyde started graduate school at the University of Maryland, not coincidentally, where her father earned his Ph.D. in chemistry in 1969. She soon connected with Mathematics Professor Benjamin Kedem, who quickly became one of her favorite professors.
“Professor Kedem was a mainstay in the Statistics Department. I remember he admitted me into the program because I had an econ background and had solved applied math problems. Another favorite professor was Paul Smith, who taught linear models, which I really enjoyed—it was more applied, doing linear algebra to calculate model parameters,” Hyde said. “I took an independent study with him where we examined advanced statistical and machine learning problems. At the time, using computer vision models to detect handwritten text and numbers was newer; it wasn’t an easily solved problem like it is now.”
Summer internships along the way took Hyde to the U.S. Census Bureau and AT&T.
“It was really neat working at AT&T Research; there were so many smart researchers doing interesting work there,” Hyde recalled. “The project that I remember the most was research on speech-to-text. Even though I didn’t work on that project, I was one of the sample voices used to train their models.”
Challenge after challenge, Hyde worked her way forward.
“I think the biggest thing that I got out of grad school was tenacity. The work was hard for me, and I learned to take it on in small pieces and build accomplishments,” Hyde explained. “I was part of a study group, and we spent the first few years together in one of the rooms on the third floor of the science and engineering library. We each had different strengths and worked together to help get our group through. Sometimes I think I never would have made it through without them and I hope they would say the same thing about me.”
Hyde earned her master’s degree in 2005 along the way to her Ph.D., eventually publishing three papers focusing on price curves, bidding distribution and other aspects of eBay auctions, which were highly popular at the time.
Smarter solutions
After earning her doctorate in 2007, Hyde spent the next several years putting her statistics, modeling and data science skill set to work in various roles, working in marketing analytics at Accenture, and technical sales building proof of concepts at SAS, IBM and Microsoft before joining Google Cloud in 2020. There, she leads a team of customer engineers at Google Cloud, helping clients incorporate technologies like AI and machine learning into smarter solutions to take their businesses into the future.
“We help our customers understand the technology, incorporate it into their business, and troubleshoot as they implement the solution. Hyde said. “I like working with customers to help them solve a problem in a way that they might not have thought about.”
Many of these business clients find that their customers notice this next-generation problem-solving, like adding AI-powered virtual assistants at fast food restaurants that can understand exactly what someone is ordering.
“That used to be very difficult to solve because it would have been speech-to-text models to intents and then a huge decision-tree like conversational architectures to try to understand what somebody wanted—and it was hit or miss whether it would get it right,” Hyde said. “But now, with large language models, you don't have to do that— the models are able to understand different versions of how you would order your burger.”
For retail businesses whose customers are looking for specific products, AI takes searches beyond keywords to semantic search or even visual search to help people find exactly what they’re looking for.
“In just a few years, search results have improved dramatically with the improvement of multi-model models. You can upload a picture with a flower pattern you like and say with text or voice that you want that on a dress, and AI will understand that you’re searching for a dress that has flowers on it.” Hyde said. “And the thing is, consumers are starting to expect all of these things.”
A strong foundation
Though the technology she works with every day is beyond anything she imagined 20 years ago, Hyde still relies on the valuable math and statistics skills she developed at UMD.
“At Maryland, I learned to understand how to solve problems rather than just memorize how to solve problems,” Hyde explained. “I now have the ability to understand and explain what is going on with a speech-to-text model or a computer vision model or a large language model because I have the underlying knowledge of statistics, modeling and the assumptions that you have to make to build the models. UMD really gave me a great foundation.”
For Hyde, it’s all about problem-solving on the cutting edge of technology. And she wouldn’t want to be doing anything else.
“The technology is changing so rapidly that it almost feels old shortly after being introduced because research in AI is flourishing,” she said. “Google is an innovative company with a strong research arm, so they're always at the forefront of what's going on, giving us new ways to solve problems. That’s really exciting.”
Written by Leslie Miller
