Noah Zegna Rothenberger

Noah Rothenberger

I'm an ELLIS PhD fellow at the Pioneer Centre for Artificial Intelligence and the University of Copenhagen. My advisors are Prof. Dr. Serge Belongie at the University of Copenhagen and Prof. Dr. Konrad Schindler at ETH Zurich. I obtained both my bachelor's and master's degree from ETH Zurich. Prior to starting my PhD, I worked at NASA's Jet Propulsion Laboratory as a Robotics Engineer in the Robot Ops and V&V group (more info here).

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Research

I'm broadly interested in computer vision, robotics, deep learning, robot perception, remote sensing, and image processing.

Publications & Preprints
	Stitching Illumination-Matched Maps: A LIMA-Based Pipeline for Robust Reference Map Generation Noah Rothenberger, Yang Cheng, Adnan Ansar, Yumi Iwashita AIAA SCITECH 2026 TL;DR Synthesizing illumination-matched reference maps for any target lighting from images captured under different sun angles, solving a critical challenge for upcoming Artemis lunar landings and is broadly applicable to any planetary mission where operational and archival lighting differ.
	Illumination Invariant Image Matching for Lunar TRN Noah Rothenberger, Georgios Georgakis, Yang Cheng, Adnan Ansar AIAA SCITECH 2025 TL;DR Introducing two approaches for robust image matching under illumination variation: 1) A new correlation-based algorithm — the Lighting Invariant Matching Algorithm (LIMA), and 2) a novel application of deep learning for learning illumination invariant features.
	Robotic Operations During Perseverance's First Extended Mission Vandi Verma, Mark Maimone, Kyle Kaplan, Ellen Thiel, Noah Rothenberger, Joseph Carsten, Arturo Rankin, Ethan Schaler, Evan Graser, Nadya Balabanska, Stephen Kuhn, Harel Dor IEEE Aerospace 2025 TL;DR Scaling Perseverance's extended-mission science and sampling through operations and flight-software advances–enabling ~30 km of driving and 28 cached samples by sol 1266, including deployment of the 10-tube Three Forks Sample Depot. The paper highlights the Jezero delta campaign across new terrains, autonomy and wheel-motor constraints, a Global Localization update for longer drives, energy-aware onboard planning, streamlined contact science/sampling, and in-mission arm recalibration plus lifetime checks for the gDRT and drill.
	Lessons From Ingenuity's Climb Up Jezero Crater Delta Joshua Anderson, Travis Brown, Martin Cacan, Gerik Kubiak, Ashkan Jasour, Noah Rothenberger IEEE Aerospace 2024 TL;DR Enabling safe flight across Jezero crater’s rugged delta by upgrading Ingenuity’s flight software with hazard-aware landing and DEM-aided navigation, validated via checkout flights. The paper distills lessons from flights 34+ on rapid, tightly coupled helicopter–rover operations—pushing cadence to under a week while working within limited telecom windows and challenging terrain.

This page design is based on a template from Jon Barron.

Research

Publications & Preprints