Meta Reality Labs Research

Overview

Reality Labs Research is where Meta explores the interaction paradigms that might define computing a decade out — haptics, sensing, multimodal input, AI-driven interaction. I led a multidisciplinary team of designers and prototypers working at that frontier, and a large part of my job was translation: taking exploratory research and turning it into platform direction that product and engineering leadership could actually invest in.

The Challenge

Deep R&D has a peculiar problem. The work is genuinely novel — haptic gloves, sensory perception, future input — but novelty isn't the same as direction. Research can generate endless fascinating possibilities; what it often lacks is a frame for deciding which possibilities are worth building toward and why. The challenge wasn't producing more ideas. It was imposing enough structure on an ambiguous research space that leadership could make real prioritization and investment decisions.

My Role

As Research Design Manager, I led multidisciplinary teams exploring next-generation human-computer interaction for spatial computing — building and running design-and-prototyping groups inside a highly ambiguous research environment, and partnering across research, engineering, and product to turn exploratory technology into roadmap-ready direction.

Approach

Frame the questions, not just the artifacts. I led a cross-functional group of scientists, researchers, and designers exploring how humans and animals sense and perceive — and how AI and machine learning could interpret a person's actions in a virtual environment and drive haptics to render texture, weight, and contact convincingly. The goal was to map the real possibility space of future input, not chase isolated demos.

Build bridges out of the lab. To give the haptics research a vision and strategy, I started a collaboration program with first-party platforms, third-party developers, and industry partners — exploring how future capabilities would change communication, creation, and productivity, and feeding those answers back into product strategy and technology investment.

Make ambiguity decidable. I helped define evaluation frameworks and quality thresholds for next-generation interaction systems, giving leadership a basis to compare and prioritize work that would otherwise have been impossible to weigh against each other.

Key Contributions

• Built and led multidisciplinary design and prototyping teams operating in a frontier research environment

• Led exploration of emerging interaction paradigms spanning sensing, multimodal input, and AI-driven interaction

• Stood up a partner collaboration program to pressure-test future haptics capabilities against real creator and developer needs

• Defined evaluation frameworks and quality thresholds that shaped research prioritization

• Influenced cross-functional investment decisions across research, engineering, and product leadership

Outcomes

The frameworks and partner programs gave the haptics research pillar a clearer strategic direction and a basis for investment decisions — turning open-ended exploration into roadmap-ready platform thinking. The work fed long-horizon strategy for immersive and next-generation interaction at Reality Labs.

Reflection

Frontier research taught me that the scarce skill in R&D isn't generating possibilities — it's giving an ambiguous space enough structure that an organization can act on it. The most valuable thing I brought wasn't another idea; it was a way to decide between ideas. That translation problem — from "what's possible" to "what should we build and why" — is the same one I've worked on in every environment, just at the most uncertain end of the spectrum.