Two NYU hackathon winners didn’t just take home laptops with Snapdragon X Elite as prizes—they made them their primary dev machines. Discover how these NYU students are pushing the limits of edge AI with faster local inferencing and NPU-powered performance.
At our NYU hackathon last December, innovation wasn’t just in the code – it was in the tools that brought that code to life. Among the standout teams were two students whose projects not only impressed the judges but also earned them each a brand-new Copilot+ PC powered by a Snapdragon X Elite processor. But what’s even more exciting? They didn’t just take their prizes home – they made them their daily drivers.
Meet the Innovators
Abhishek Kumar and Nirmal Boghara, both grad students at NYU, entered the hackathon with curiosity and big ideas.
Abhishek is a Master’s student in Applied Urban Science and Informatics at NYU’s Center for Urban Science and Progress. With a background in urban planning and software development, Abhishek’s interests lie in building solutions for complex urban challenges. You can explore some of his recent work on Github.
Nirmal is pursuing a Master’s degree in Computer Science at NYU Tandon School of Engineering. His academic interests include AI, ML, and software development, with a focus on building applications for a social cause. Check out his projects on GitHub.
Hackathon Experience
Both students first heard about the hackathon through announcements at NYU Tandon School of Engineering. For Abhishek, it was his first hackathon, driven by a desire to learn and build something cool. Nirmal, on the other hand, was drawn to the idea of deploying AI models locally, a concept he had not explored before.
Over the course of 24 intense hours, Abhishek developed “REDACT”, a desktop application that helps redact personally identifiable information, leveraging the Snapdragon X Elite ability to process data locally and efficiently.
Nirmal built «Tutor AI,» an application designed to provide intelligent learning assistance and curriculum for tutors and teachers in rural areas. Both faced challenges during the event, such as memory and runtime performance, which were mitigated by the Snapdragon X Elite integrated NPU and battery optimization.
Their work earned them a top spot in the competition – and a laptop with Snapdragon X Elite.
Transition to Snapdragon X Elite
While many hackathon prizes go unused after an event, this one didn’t collect dust. The students quickly discovered the efficiency, power consumption, and ability to run large models locally without lag made it ideal for their everyday development work.
After the hackathon, both students gradually transitioned to laptops with the Snapdragon X Elite as their primary development machine. Abhishek was particularly impressed by the device’s battery life, which allowed him to go through the entire 24+ hour hackathon and demo without needing to plug it in. Nirmal appreciated the dedicated NPU and thermal consistency, which provided stable performance without any fan noise or throttling.
Empowering More Students
The hackathon experience motivated both students to participate in additional hackathons with Qualcomm Technologies. Abhishek saw it as an opportunity to contribute to the growing use cases of AI and catalyze new developments. Nirmal was driven by the need to bridge the awareness gap among students about the power and efficiency of local AI.
They provided mentoring and support to other students at subsequent hackathons. Abhishek focused on replicating the organized and supportive environment he experienced at the NYU hackathon, speaking to each team and sharing insights. Nirmal helped students understand the Qualcomm AI Stack and encouraged them to use local LLMs with Qualcomm AI Hub.
Nirmal was particularly impressed with the Qualcomm AI Hub, a comprehensive platform designed to streamline and accelerate the development of AI applications on devices with Qualcomm Technologies processors.
«Qualcomm AI Hub became my go-to resource after the hackathon. It allows you to skip a lot of the overhead when optimizing models, you don’t have to optimize for good outputs. Qualcomm AI Hub does that for you – saves lots of trial and error.» – Nirmal
Impact on Workflow and Projects
Switching to laptops with the Snapdragon X Elite has significantly impacted the student’s workflow and the types of projects they are working on. Abhishek now runs LLMs and inference offline, experimenting with AI capabilities without relying on cloud APIs. Nirmal has shifted his mindset to prioritize privacy and efficiency, running models locally first and reducing energy consumption in AI data centers.
Both students have noticed performance improvements when building or testing AI models. Abhishek highlighted the speed of inference during demos.
Abhishek and Nirmal highly recommend laptops with the Snapdragon X Elite to other developers working on AI or edge projects emphasizing the ability to experiment on-device. Additionally, Nirmal praised the device’s efficiency, privacy, and security, likening it to a mini data center.
“Imagine if your laptop could do what a server does without melting or dying on battery, that’s my laptop with the Snapdragon X Elite. It’s a mini data center.” – Nirmal
What’s next?
For these NYU students, the laptop with the Snapdragon X Elite wasn’t just a prize – it became a turning point. By choosing to adopt Snapdragon X Elite laptops as their main development machine, developers proved that the right tools can fuel not just one great idea, but an ongoing journey of innovation.
Their story is a reminder that when we put powerful technology into the hands of bold thinkers, we don’t just enable projects – we unlock potential.
This is just the beginning. We can’t wait to see what they build next!
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