Kshitij Goel Robotics Researcher
Kshitij Goel

Kshitij Goel

Project Scientist, Robotics Institute, Carnegie Mellon University, USA

I am building large-scale robot teams that operate reliably for days to months in environments too harsh or unpredictable for today's systems.

I develop algorithms, data structures, and data-driven models for multi-robot systems that scale to thousands of agents and sustain long-duration autonomy in uncertain, contested, and adversarial settings, with applications from search and rescue to security, household assistance, and low-cost manufacturing.

I earned my Ph.D. in Robotics from Carnegie Mellon University, where I developed a scalable, memory- and communication-efficient, multi-modal perception framework for large teams of mobile robots.

I am actively seeking faculty roles in robotics.

Research

Interactive, Affordable, and Resilient Multi-Robot Systems with Thousands of Robots

My work spans algorithms, data structures, and data-driven models for multi-robot systems. I deploy these systems in challenging environments like caves, tunnels, forests, and deserts.

Learning Robot Control from Simulated Experience

Training control policies in high-throughput differentiable simulators and deploying them zero-shot sim-to-real.

Distributed Decision-Making for Robot Teams

Decentralized coordination that keeps robot teams effective in uncertain, contested, and adversarial environments.

Continuous World Models

Modeling the world as continuous probability distributions; compact generative maps that enable several downstream robotic tasks.

Flying Fast through Cluttered Environments

Planning, control, and learned policies for aerial robot navigation through cluttered environments without maps.

Shared Autonomy for Human-Robot Teams

Implicit coordination and wearable sensing that let humans and robots share information without explicit commands.
News

Recent updates

Selected publications

Recent work

Filter by research area. Author of this page in bold. Full list on Google Scholar.

Decentralized Uncertainty-Aware Active Search with a Team of Aerial Robots

Decentralized Uncertainty-Aware Active Search with a Team of Aerial Robots

Wennie Tabib, John Stecklein, Caleb McDowell, Kshitij Goel, Felix Jonathan, Abhishek Rathod, Meghan Kokoski, Edsel Burkholder, Brian Wallace, Luis Ernesto-Navarro-Serment, Nikhil Angad Bakshi, Tejus Gupta, Norman Papernick, David Guttendorf, Erik E. Kahn, Jessica Kasemer, Jesse Holdaway, and Jeff Schneider

ISER 2025
Open Toolkits

Open-source software for robotics

Toolkit

gira3d

An open-source, GPU-accelerated C++/CUDA toolkit for Gaussian Mixture Models in robot perception and autonomy — unified reconstruction, registration, occupancy modeling, and collision queries from a single compact representation.

Explore
Honors

Awards & recognition

2024

Alan J. Perlis SCS Graduate Student Teaching Award

Carnegie Mellon University

2024

Best Paper Award

IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)

2022

Best Paper Award

IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)

2022

King-Sun Fu Memorial Best Paper Award (Honorable Mention)

IEEE Transactions on Robotics

2021

National Science Foundation (NSF) Ph.D. Student Travel Award

International Symposium on Experimental Robotics (ISER)

2021

Uber Carnegie Mellon Presidential Fellowship

Carnegie Mellon University

Teaching & writing

Learning resources

Courses and materials for learning robotics.

Course · CMU · 2023

16-362: Mobile Robot Algorithms Laboratory

Co-designed and co-instructed with Prof. Wennie Tabib, this undergraduate-level laboratory course focuses on the implementation of state estimation, mapping, planning, and control algorithms for mobile robots.

Open
Course · CMU · 2022

16-720: Computer Vision

Teaching Assistant for Prof. Deva Ramanan.

Course · CMU · 2022

16-831: Statistical Techniques in Robotics

Teaching Assistant for Prof. Kris Kitani.