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Pranav Kuchibhotla (AI 4th Year) quickly noticed that the wide range of topics that courses in �㽶��ý’s B.S. in Artificial Intelligence covers—from core algorithms and data structures to deep learning and natural language processing—prepared him to work on data science projects using real datasets.

“The AI program here is very hands-on, so you cannot just coast through assignments,” he says. “You must understand what you are doing. These experiences basically convinced me that I want my future to stay centered around AI and machine learning.”

Pranav says that his participation in research projects and competitions is helping to prepare him to achieve his career goals, which includes using AI and data science to build tools that quietly make life better for people.

“I did research with [Associate Professor of Biomedical Engineering Keigo] Kawaji for a semester in my second year at �㽶��ý, and that experience really sparked my deeper interest in machine learning and applied AI,” Pranav says. “Research with Professor Kawaji was my first taste of doing real machine learning work instead of just homework, and it hooked me.”

After a taste of research, Pranav says he joined Ocean’s Four-vArI, a team of student researchers, to vie for the Grainger Computing Innovation Prize. The competition asks student researchers to tackle projects that address real-world problems in education, health, energy, public safety, transportation, economic development, sustainable smart infrastructure, climate change, and more. This year’s theme was “Computing with Data and AI for Social Good.”

Ocean’s Four-vArI is a volunteer computing platform that runs ocean-drift simulations on users’ devices. It aggregates thousands of lightweight AI-informed trajectories to predict plastic hotspots, nearly in real time, without supercomputers. The project earned the team third place and a $5,000 prize.

“That was the first time I saw an idea go all the way from a rough sketch on a whiteboard to a working tool with real impact,” he says. “Standing with my teammates and explaining our work to judges and guests made me realize that I really enjoy building AI systems that solve concrete problems.”

Pranav says this hands-on experience has complemented his coursework and helped prepare him for a future, either as a machine learning engineer or by pursuing graduate studies.

“�㽶��ý has given me a strong mix of theory and real projects in AI and data science, which makes me feel comfortable working on open-ended problems,” he says. “Competitions, research, and internships have forced me to learn how to explain technical work to different audiences and work in teams.”

Pranav says he feels genuinely supported as an �㽶��ý student. The professors are approachable and invested in student success. He says his adviser, Assistant Teaching Professor of Computer Science Jacek Dzikowski, has had a huge impact on his growth as well.

“�㽶��ý has been there for me during both difficult moments and big wins, and that sense of support and community really makes me feel proud to call myself a Scarlet Hawk,” he says.