Meet Alum Pranav Motarwar – M.S. Computer Science, '25

Before his first semester at NYU Tandon even began, Pranav Motarwar started reaching out to professors and center directors working in fields of interest to him. Most, of course, simply resulted in polite good wishes for his future success. But a response from the team at NYU’s Center for Urban Science and Progress (CUSP) led to an early role that shaped his academic path.

Pranav entered NYU with the intention of contributing to the university’s research and teaching community on a volunteer basis. With a background in computer science and prior experience applying machine learning to real-world problem domains, he pursued opportunities to support student teams, collaborate on applied research, or assist in academic initiatives. “The ecosystem at NYU felt open from day one,” he says. “But you have to be proactive about stepping into those opportunities.” By arriving prepared and taking initiative early, he established himself as an active contributor within the NYU Tandon community from the beginning of his program.

Building Momentum from Semester One

While Pranav had hoped only for a volunteer position that would immerse him in the Tandon community and provide him with some research experience, a better proposition presented itself: CUSP recruited him as a Capstone Assistant for the Urban Science Intensive course, a job that involved mentoring industry-facing teams. What started as a single-semester commitment became a three-semester anchor, grounding Pranav’s coursework in real-world urban challenges.

Simultaneously, he connected with Industry Assistant Professor Anton Rozhkov, who directs NYU’s M.S. in Urban Data Science program at the Center for Urban Science and Progress. "I wanted to combine my background in large language models with CUSP’s work in urban analytics," Pranav explains. He collaborated with Professor Rozhkov on applying LLMs to urban policy challenges and, working closely with faculty, built LLM-based workflows from the ground up to support urban planning and data-driven decision-making.

By his second semester, Pranav expanded his responsibilities to include teaching, serving as a Teaching Assistant for Machine Learning for Cities with Professor Daniel Neill. In that role, he supported graduate students in applying machine learning methods to real-world urban datasets.

Balancing research, teaching, and capstone mentorship was demanding. But managing these parallel responsibilities helped him align his research, teaching, and applied research work into a clear academic and professional direction.

From Research to Industry — and Back

That summer, Pranav joined TikTok's data team as a data engineering intern, building large-scale data pipelines supporting the platform's core application. "The work felt like a direct extension of what I'd been doing at NYU for the past two semesters," he reflects, and before returning for his final semester, he received a full-time offer to continue the work in the AI domain.

Rather than slowing his academic engagement with a job already secured, Pranav accelerated his efforts. He worked on an interdisciplinary research project with Professor Robert Krueger at NYU’s Visualization Imaging and Data Analysis (VIDA) Centeron a project focused on visual analysis tools to make cancer imaging data explorable for biomedical research and diagnosis; co-authored work that was presented at the Association of Collegiate Schools of Planning (ACSP) Conference on LLM applications for urban areas; and began contributing to open-source projects, including releasing Python packages and contributing fixes to Apache projects.

He also began mentoring others, speaking with prospective students through the Tandon Career Hub and the Department of Computer Science and Engineering, where he was invited to share guidance based on his industry experience. He was also invited to be a reviewer for the NYU Entrepreneurs Challenge, evaluating venture proposals for the university’s flagship competitions administered by the NYU Stern Berkley Center for Entrepreneurship.

The Formula: Hard Work Meets Strategic Action

Pranav’s success followed a clear pattern: identify goals, research pathways, make connections, and execute relentlessly.

"Get clarity about what you want to accomplish and research how to get there," he advises incoming students. "Make the connections. NYU opened doors at every stage, but you have to knock first."

Today, Pranav works in the AI domain as an engineer at TikTok, operating in the privacy and security space and building large-scale systems that support production AI agentic workflows. In retrospect, he describes his transition into industry as a continuation of the work he began at NYU. The combination of research, teaching, and research-based learning during his master’s program aligns with the responsibilities he now holds at TikTok.

Learn more about Pranav's work at pranav-motarwar.vercel.app