ASU’s data science dream team turns big data into big futures
Data science student Dhruv Modi (left) with Rong Pan, a professor of industrial engineering and data science in the School of Computing and Augmented Intelligence, part of the Ira A. Fulton Schools of Engineering. Modi, who successfully defended his master’s thesis, “Foundation Time Series Models,” will graduate in May as part of the inaugural cohort of 47 graduates of the data science master's program. Photo courtesy of Dhruv Modi
People are overwhelmed. By too many choices when shopping. By too much information at work. By too much parenting advice. And even by too many passwords.
The task of helping us sort out what information we really need to make good decisions is the job of a data scientist — an increasingly important specialty of computer science.
“In a world saturated with information, data science is not just valuable — it is indispensable,” Rong Pan says.
Pan is a professor of industrial engineering and data science in the Ira A. Fulton Schools of Engineering at Arizona State University. He has played a pivotal role in shaping the school’s graduate-level data science programs, which are designed to train advanced students for challenging roles.
At the Fulton School’s graduate convocation in May, the first cohort of data science master’s degree students will be awarded their degrees. The program is a collaboration between multiple engineering schools, including the School of Computing and Augmented Intelligence, the School of Electrical, Computer and Energy Engineering, the School of Sustainable Engineering and the Built Environment, the School for Engineering of Matter, Transport and Energy and the School of Mathematical and Statistical Sciences.
The goal is to combine the mathematical modeling, computing and engineering expertise of globally recognized faculty members with critical research opportunities.
Pan notes that the inaugural cohort is exceptionally well-equipped for data-driven careers and leadership positions.
“We designed this master’s program with a focused mission: to train advanced data scientists capable of navigating complexity and uncovering insights from noisy, high-dimensional and multimodal data,” Pan says.
Meet some of the cohort
Sudeeksha Vandrangi, one of the 47 students who began the program in 2023, seized internship opportunities to create real-world forecasting models and mentored fellow students through programs like Stanford University’s Code in Place. She says she is proud of the cohort and the legacy they are leaving for future students.
“We didn’t just follow a path; we helped lay it down,” Vandrangi says. “From navigating a brand-new curriculum to building community traditions from scratch, this experience has taught me adaptability, resilience and initiative. It’s been rewarding to contribute to shaping the identity of the program and to see our projects and placements reflect the potential of what this program can grow into.”
Dhruv Modi joined the program to spur career advancement after spending several years in the engineering workforce.
“Coming in with four years of industry experience, I joined not just to study, but to deepen my understanding, challenge my thinking, and connect academic work with real-world data problems I’ve seen firsthand,” Modi says.
Working under Pan’s supervision, he authored the master’s thesis “Foundation Time Series Models” — research that combines leading-edge artificial intelligence models with traditional statistical techniques to better leverage data for accurate predictions.
“The topic aligns closely with my professional background and personal interest in time series forecasting,” Modi says. “The research process was intense, but it taught me how to approach problems with both depth and flexibility.”
After graduation, Shreyas Hingmire, who completed the program with a 4.0 GPA, will begin a full-time position as a senior data scientist at American Express. He says his internships, upcoming career opportunities and personal growth have been especially meaningful. He encourages others to check out the program.
“With the right mindset, this program can open up a world of exciting opportunities,” Hingmire says. “Focus on mastering core concepts early, stay curious, and keep exploring new tools and techniques.”
Nayan Bhiwapurkar is looking forward to a career where he makes a lasting impact in applied research. He says that classes in data visualization and deep machine learning — along with internship, teaching and research opportunities — sharpened his technical skills and provided rich opportunities for collaboration with faculty members and students across a variety of fields.
“The faculty is exceptional and genuinely cares about your growth,” Bhiwapurkar says. “It’s a program where you can take initiative, pursue interdisciplinary projects and dive deep into areas that interest you.”
Shraddha Pandey, who plans to step into a data scientist or analyst role after graduation, gained valuable experience through work on her capstone project, which she completed over two semesters.
“It’s surreal and exciting to be part of the first-ever cohort,” Pandey says. “There was a sense of building something new together — from course offerings to capstone projects — and that made the experience feel even more collaborative and memorable.”
Deepakshi Mathur, who is planning on a data science or software engineering role, says that the program’s hands-on work helped her increase her skills and her confidence.
“I’ve learned to build impactful, data-driven solutions,” Mathur says. “I’m excited to keep growing professionally and contributing to innovative projects.”
Pan says he’s thrilled to send the cohort out into the world to deal with the data deluge and make real-world impact.
“This first cohort is graduating with expertise that is both timely and critically needed,” he says.
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