ACM Scholar Spotlights: Naomi Pitzer
Welcome to ACM Scholar Spotlights, a series where we shine a light on the inspiring paths of women in computing who received the 2025 ACM-W scholarship. Through their own words, we hear how they found their place in tech, what motivates them, and how they’re making an impact. These stories reflect not only technical achievement, but also courage, curiosity, and community.
In this feature, we highlight the story of Naomi Pitzer, a Computer Science graduate from the University of Southampton whose passions span machine learning, multi-agent communication, and robotic perception. From founding a community for women and non-binary students to finding inspiration at her first womENcourage, Naomi shares how her academic journey, research, and personal reflections on AI and human behaviour continue to shape her path in technology.
Introduction
Hello everyone! My name is Naomi, and I am a Computer Science graduate from the University of Southampton, where I specialised in machine learning and multi-agent communication. I am soon to begin my PhD specialising in AI for robotic perception. My technical interests lie at the intersection of cognitive science and AI, particularly in understanding how we can design systems that perceive, act, and learn in complex real-world environments.
One of my proudest achievements has been co-founding and leading a society for women and non-binary people in the School of Electronics and Computer Science. Through hosting events and discussions, we were able to open up much-needed conversations and create a stronger sense of community.
My womENcourage ’25 Experience
This was my very first womENcourage experience. My favourite moments included building a study-cycle tracking Chrome extension during the hackathon and listening to Adriana Wilde’s keynote on her non-linear path in technology and the “failures” that ultimately shaped her career. Her story encouraged me to enjoy the journey rather than focusing solely on the destination, reminding me that a pivot is not a setback but a valid path filled with lessons and opportunities.
It was also incredibly inspiring to meet brilliant researchers who have made outstanding contributions to the field and who are working to create a more inclusive path for the next generation of women in tech.
Lessons from Computer Science That Extend Beyond Technology
Computer Science has taught me a great deal about human behaviour, with the most significant insights emerging from studying Machine Learning. A friend once told me she stopped feeling hurt by others’ unfair actions because the fact that she couldn’t understand such behaviour meant she was already operating from a kinder place. This idea resonated with me, but it truly made sense only when I began studying the mathematics of representation learning in AI.
Through working with artificial agents that develop communication protocols despite differing perceptual realities, I saw how each model constructs its own internal map of the world, shaped entirely by the data it has seen. While artificial and biological neural networks differ greatly, a similar principle applies to people: our fundamental view of reality and therefore our reactions to new information are built from our experiences and environments.
Realising this has reframed how I interpret conflict, unconscious bias, and the confusion of learning something brand new. I no longer internalise either as a personal failure or as a reflection of my worth, but see them as mismatches in representation. This understanding has also made me more resilient when learning difficult concepts, reminding me that with enough time, I can adapt my worldview to comprehend and excel in them.