Mark Campbell

Mark Campbell is a robotics and aerospace researcher whose work develops perception and control for autonomous systems. He earned engineering degrees at Carnegie Mellon and MIT, contributed to MACE control experiments aboard Space Shuttle Endeavour, and joined Cornell in 2001 after a faculty post at the University of Washington. At Cornell, he advised its team in the 2007 DARPA Urban Challenge and led a 2009 NSF project on vehicle intelligence, then directed the Sibley School from 2011 to 2019 and became an IEEE Fellow in 2018. In 2025, he coauthored work on learning for robotic swimming, and in 2026 he coauthored a call for shared autonomous-driving data. He holds the Mellowes ’60 professorship in Cornell’s Sibley School of Mechanical and Aerospace Engineering, a role he began in 2015.

Now at: Cornell University
Works: 316
Citations: 6,803
h-index: 40
Badges: Loyal

Publication numbers from OpenAlex, as of 27 October 2026.

Timeline

1990–1993

Engineering degrees

He earns a B.S. in mechanical engineering at Carnegie Mellon in 1990 and an M.S. at MIT in 1993.
1995–1996

MACE on Endeavour

He works on MACE, a dynamics and control laboratory flown aboard Space Shuttle Endeavour in 1995, designing many of its 500 multivariable control experiments. He earns an MIT Ph.D. in control and estimation in 1996.
1997–2001

Professor at Washington

He joins the University of Washington as an assistant professor in 1997 and serves through 2001.
2001

Joining Cornell

At Cornell, he joins the Sibley School faculty in 2001.
2007–2009

DARPA and vehicle intelligence

In 2007, he advises Cornell's team in the DARPA Urban Challenge as an associate professor and faculty adviser; the team's result comes down to time. In 2009, he leads a $1,473,121 three-year NSF Cyber-Physical Systems grant to advance vehicle intelligence.
2011–2019

Sibley director and IEEE Fellow

He serves as S.C. Thomas Sze Director of the Sibley School from 2011 to 2019. In 2018, the IEEE Control Systems Society names him an IEEE Fellow for contributions to control and estimation theory for autonomous systems.
2025

Robotic swimming research

In 2025, he coauthors “Robust Robotic Swimming via Drop-out Learning” for the IEEE International Conference on Robotics and Automation.
2026

Data paradigm for autonomy

In 2026, he coauthors “Autonomous Driving Research Requires a Community-Driven Data Paradigm,” which calls for shared data to support autonomous systems that can operate robustly across places and scenarios.
Since 2015

Professor at Cornell

He holds the John A. Mellowes ’60 professorship in Cornell's Sibley School of Mechanical and Aerospace Engineering. His research covers estimation and control for autonomous systems, sensor fusion and probabilistic perception, with emphasis on robotics and aerospace applications.