Building collaborative autonomy that works in the real world.

I design and deploy AI systems for safety-critical, multi-agent environments, from city-scale drone traffic to real-time human-autonomy coordination, bridging research, infrastructure, and execution.

WHAT I BUILD

Infrastructure

I architect real-time, distributed simulation and validation platforms for safety-critical autonomy, designed to operate under degraded networks, asynchronous agents, and human intervention.

Cooperative Autonomy

I develop decentralized coordination, tactical deconfliction, and cooperative perception mechanisms that enable safe multi-agent behavior under uncertainty.

Deployment Pathways

I design systems to support safety cases, FAA-aligned evaluation, and transition from research prototypes to operational infrastructure.

My research focus

My PhD research focuses on learning-based multi-agent coordination for collaborative autonomous systems, enabling agents to cooperate under partial observability, uncertainty, and dynamic interaction with humans and other autonomous actors.

Rather than studying coordination in isolation, my work emphasizes how these models behave when embedded in real operational systems.

From coordination models to operational systems

Through a NASA-funded project, I translated my research on multi-agent coordination to AI-enabled Unmanned Traffic Management (UTM) for Advanced Air Mobility and public safety operations.

This work translated coordination and learning models into:

City-scale, multi-agent simulation environments
Real-time, distributed systems operating under latency and network degradation
Hardware-in-the-loop testing with real autonomous aerial vehicles

The goal was not performance demos, but understanding how coordination strategies hold up under real-world constraints.

Case study: Large-scale validation of multi-agent coordination

Problem

Learning-based coordination methods are rarely evaluated under the conditions they will face in deployment.

What I built

To address this, I designed and implemented:

A real-time, distributed simulation platform supporting city-scale multi-agent operations
Integrated hardware-in-the-loop testing with autonomous drones
Coordination and deconfliction under latency, packet loss, and dynamic occlusion
Scenario-based evaluation informed by real safety-critical incidents

The system was designed to support city-scale, multi-agent operations under real-time constraints.

Why it matters

This work enables deployment-informed evaluation of collaborative autonomy, supporting research, public-sector stakeholders, and future autonomous operations.

Explore More

Technical leadership and execution

Alongside research, I have led complex technical programs end-to-end, from system architecture and model development to field deployment and cross-sector collaboration.

/ Principal Investigator on a NASA-funded project

/ Led interdisciplinary teams spanning AI, robotics, and systems engineering

/ Conducted extensive field testing and operational evaluation

/ Cornell Engineering Commercialization Fellow

/ NSF I-Corps National awardee, validating real-world needs through customer discovery

National impact and service

/ Federally competitive research funding (NASA, NSF, NAIRR)

/ 8+ strategic partners and additional external support to expand national testing and evaluation activities.

/ Participation in standards-adjacent and government working groups

/ Invited talks across government, industry, and academia

/ Independent media coverage of applied research impact

Partners & Ongoing Engagement

As my work has matured, it has expanded beyond a single research effort into sustained collaboration with government, industry, and national initiatives focused on the future of autonomous systems. Through my NASA-funded project, I have led partnership expansion supporting FAA-aligned test site activities, public safety autonomy research, and deployment-informed validation of cooperative airspace systems.

This ongoing work includes technical collaboration and engagement with partners across communications, standards, and infrastructure, including Qualcomm, NIST, CAAMCI, and national workforce development initiatives, and has resulted in the formation of multiple strategic partnerships and additional external support to extend testing, validation, and real-world impact.

Selected Media Coverage

Looking Ahead

Looking ahead, my long-term direction is toward building infrastructure that enables collaborative autonomous systems to be evaluated, trusted, and deployed responsibly at scale.