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Neha Balamurugan

Neha Balamurugan

AI/VR/ML researcher, entrepreneur, and student at Stanford and ASU

Palo Alto, California
Joined August 2025
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Summary

Neha Balamurugan is a highly accomplished computer science student with a strong academic background from Arizona State University and Stanford University, specializing in Artificial Intelligence. Her academic journey includes graduating Summa Cum Laude from ASU's Barrett, The Honors College, and pursuing a Master's at Stanford. nehabalamurugan+1
She demonstrates a keen interest in VR/AR, Machine Learning, and entrepreneurship, actively engaging in research at Stanford's Causality in Cognition Lab and having previously developed VR tools at ASU's Meteor Studio. Her entrepreneurial spirit is evident through co-founding "Break Digital Divide" and "Sharpening Minds Math Tutoring," as well as her role as co-host of the "Second Order Podcast." nehabalamurugan+3
Neha is also a published researcher, with contributions to papers on visual social inference and evaluating LLMs' emotional alignments, showcasing her deep engagement with cutting-edge AI research. Her work frequently bridges the gap between human cognition and AI system development. arxiv+2
Her commitment to social impact is highlighted by projects like the "YouCare" app, which addresses PCOS awareness, and her involvement in the Grand Challenges Scholars Program, focusing on complex societal problems. She has also received recognition through awards like a Grand Prize at Hacks for Humanity and a best solution prize at HackMIT. asu+1
As an Accel Leadership Fellow and a co-host of an entrepreneurship podcast, Neha is actively developing her leadership and venture-building skills, indicating a strong trajectory toward future innovation and impactful contributions in the technology and startup ecosystems. stanford+1

Work

Education

Projects

Writing

Spot the Ball: A Benchmark for Visual Social Inference

November 1, 2025

First author on a paper that introduces a challenging benchmark for evaluating visual social inference in vision-language models (VLMs) using sports as a test domain. The study found a persistent human-model gap in visual social reasoning.

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Apathetic or Empathetic? Evaluating LLMs' Emotional Alignments with Humans

January 1, 2024

Co-authored a paper that investigates how large language models (LLMs) internally represent emotion by analyzing the geometry of their hidden-state space, revealing a consistent and manipulable affective geometry.

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Hobbies

Enjoys playing tennis, coding, weightlifting, and has interests in otters and cacti. nehabalamurugan