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International Student Seun Johnson Earns Master’s Degree and New Career at Intuit

Oluwaseun “Seun” Johnson is graduating this month from UA Little Rock with a master’s degree in information science and a new career at Intuit, Inc.
Oluwaseun “Seun” Johnson is graduating this month from UA Little Rock with a master’s degree in information science and a new career at Intuit, Inc.

After traveling from Nigeria to earn a graduate degree at the University of Arkansas at Little Rock, Oluwaseun “Seun” Johnson is graduating this month with a master’s degree in information science and a new career at Intuit, Inc. 

Johnson will begin his new job as a software engineer with Intuit in June and will be moving to Mountain View, California, where the company’s headquarters are located, later this year.

“I feel happy that I am graduating,” Johnson said. “When I look back to when I first came to UA Little Rock, I feel like I’ve achieved a lot. I have a good portfolio and a new job, and I am happy.”

A native of Lagos, Nigeria, Johnson received his bachelor’s degree in industrial physics and applied geophysics from Covenant University in Nigeria. He learned about UA Little Rock through a friend who was studying abroad. At the time, Johnson was working as a data scientist for Petrodata Management Services Limited in Lagos and has a background in data mining, data visualization, and software development.

“My friend told me about UA Little Rock and all the opportunities here, and I thought I could be a good fit for the Information Science Program,” Johnson said. “I found Dr. Nitin Agarwal in the Information Science department, and I told him about my interests and showed him what I was working on.”

Johnson moved to Little Rock in 2019 and has put his skills to work at COSMOS (Collaboratorium for Social Media and Online Behavioral Studies) with Dr. Agarwal, Maulden-Entergy Endowed Chair and Distinguished Professor of Information Science, who said he is extremely proud of Johnson’s accomplishments.

“Despite the unique challenges presented by COVID-19, our students continue to demonstrate resolve and resilience,” Agarwal said. “Our students come from different parts of the world. Many belong to minority and underrepresented groups in STEM disciplines – a cause that COSMOS champions and celebrates. They join COSMOS to hone their skills, develop solutions for real-world problems that contribute to social good and innovation, and transform into thought leaders.”

At COSMOS, Johnson worked as one of the lead developers of the Blogtrackers tool that helps COSMOS conduct discourse analysis and event analysis on blogs, including assessment of misinformation and fake news.

“The COSMOS team gave me the opportunity to learn new things and to build myself as a software engineer,” he said. “I enjoyed meeting new people in Little Rock and learning things from new people all over the world.” 

Last year, Johnson was one of three students selected for the third annual Grad Cohort for Underrepresented Minorities and Persons with Disabilities Workshop by the Computing Research Association. The prestigious workshop brings together students and industry professionals from around the country to prepare graduate students for careers in the computer science industry.

During summer 2020, Johnson worked as a data science intern at Windstream Holdings. He created an automated workflow for text mapping/cross referencing for data migration and created an automated workflow for tracking and updating projects using Python.

Johnson recently completed his master’s project, “Optimizing Data Ingestion and Retrieval for Narrative Analysis Using Parallel Pools and Elastic Research.” The project solves the problem of slow data ingestion and retrieval for the narrative analysis page on the Blogtrackers web application. 

“When storing big data on any storage platform, it is not unusual to encounter performance issues as the ingested data can dramatically impact the performance and usefulness of a data lake,” he said. “A proper data ingestion mechanism should optimize storage for analytic performance, which is often best done upon ingestion. This process will also avoid data loss and redundancies when processing streams of data.”