Desert Financial teams up with InStride to provide its employees with an ASU education


November 12, 2020

Desert Financial’s InvestED program follows the Starbucks College Achievement Plan, the first-of-its-kind program offered in partnership between Arizona State University and Starbucks, to provide its employees with an opportunity to learn and grow while working with the company. 

The Arizona credit union recognized how quickly the world and jobs are changing, and it decided to adapt by implementing a world-class program through ASU and InStride.  InvestED student Greg Schaffran works from home with his son. Schaffran is pursuing a dual degree in business administration and physics. Download Full Image

Desert Financial employees pursuing higher education have the support of the company to keep learning and acquiring new skills as adult learners. Desert Financial hopes to build loyalty, engagement and retention with the company as Desert Financial CEO Jeff Meshey believes in “lifelong learning and continuous education.” 

InStride works with companies to provide exclusive learning experiences to its employees and is excited to work with Desert Financial. 

“We are proud to partner with a company like Desert Financial Credit Union that prioritizes its people and encourages them to pursue career advancement through education,” said Vivek Sharma, CEO of InStride. “InvestED is a meaningful program that will contribute to the company’s reputation as an employer of choice and will drive even further employee engagement.” 

The InvestED program allows employees to earn a bachelor’s degree, master’s degree, certificates, and more. This fall during its first cohort,100 students enrolled in classes. One of those students, Greg Schaffran, jumped at the opportunity to go back to school at ASU. 

When Schaffran was 19 years old, his plans to pursue a bachelor’s degree at ASU quickly shifted when his son was born. By word of mouth and several recommendations, Schaffran applied to Desert Financial’s call center. He’s moved up quickly and now holds a quality analyst position. At his job he values giving back to his customers. 

“It’s always been a passion of mine to get a degree as a way to move forward in my career and give back,” Schaffran said. He says he can already see the difference in his education, and he's excited he doesn’t have to leave his son or the same desk he works from every day, to pursue his passion.  

Schaffran is pursuing a dual degree in business administration and physics, his first love. So far in his education journey with ASU and InvestED, he’s noticed how in-depth his classes are from the explanations, assistance and application of the content. He appreciates how dedicated each person and organization is through this three-way partnership. A piece of advice he received from an academic adviser was, “It doesn’t matter where you start, as long as you get started.” Schraffan and other Desert Financial employees have the chance to get started and continue learning at ASU.  

Desert Financial Executive Vice President Cathy Graham hopes that more students will join Schraffan and participate in at least one course. “One day we’ll have 100% participation from all of our employees because ASU education is the crown jewel to employees with dependents and families.”

Get more information about InvestED.

Elon Graves

Student worker, Media Relations and Strategic Communications

ASU student creates machine-learning model to identify neighborhoods most at risk for COVID-19

New research combines mobility patterns, social distancing data and social vulnerability data


November 12, 2020

While health experts and government agencies across the globe continue to learn more about COVID-19 transmission and implement policies to curb its spread, a critical part of managing the disease is understanding with granularity which populations are at most risk and where these most vulnerable live. 

New research led by Avipsa Roy, a graduate student in Arizona State University's School of Geographical Sciences and Urban Planning, quantifies this phenomenon using machine learning to identify the most at-risk populations down to the census block group level in Los Angeles.  New research identifies the most at-risk populations down to the census block group level in Los Angeles. Photo courtesy of depositphotos.com

In her paper titled “Characterizing the Spread of COVID-19 from Human Mobility Patterns and SocioDemographic Indicators,” co-authored by Bandana Kar from Oak Ridge National Laboratory, Roy leveraged anonymized human movement data from mobile phones and combined it with social distancing data and social vulnerability indicators to examine the overall spread of COVID-19 at local spatial scales.

Roy and Kar built a new machine learning model that analyzed all the data and predicted which census block groups would have the highest risk of COVID-19 cases based on new patterns teased out from their analysis.

“If people have less access to cars or health care, or if they are unable to visit hospitals to get tested, or if their neighborhood is in bad conditions, these are vulnerabilities that underlie certain population groups,” said Roy, who completed this research as part of an internship appointment with the National Science Foundation Mathematical Sciences Graduate Internship (NSF-MSGI) program. “We approximated these kinds of vulnerabilities through mobility and social vulnerability indices, and it helped our model predict the risk factors around COVID.”

“We predict whether the risk in each census block group is high, medium or low based on sociodemographic indicators along with mobility patterns of its residents before, during and after lockdown in LA.”

Roy says that understanding the COVID-19 pandemic at local scales is important for authorities to perform targeted testing and prevent and control the future spread of COVID-19. 

“We developed a census block group level map indicator for local authorities to see and highlight which are the areas that need attention,” Roy said. “When COVID-19 first spread, no one knew where to test, how to test, or how much to test. This (research) can be used as an example map for authorities to plan ahead. When the third or fourth wave comes, what happens? Where do we go first?”

According to Roy, there are broader impacts of this model and it could be tailored for cities like Phoenix and beyond. 

“We would like to extend this study to multiple cities especially those which are a global hot spot for informing local authorities on mitigation strategies for any future spread,” Roy said. 

David Rozul

Communications Program Coordinator, School of Geographical Sciences and Urban Planning

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