Developing the foundations of Safe, and Agile A.I. and Autonomous Systems
Bio:
Dr. Madhur Behl is an Associate Professor in the departments of Computer Science, and Systems and Information Engineering, and a member of the Cyber-Physical Systems Link Lab at the University of Virginia.
He received his Ph.D. (2015) and M.S. (2012), in Electrical and Systems Engineering, both from the University of Pennsylvania; and his bachelor's degree (2009) in ECE from PEC University of Technology in India.
He is the team principal of the Cavalier Autonomous Racing team. Behl is also the co-founder, organizer, and the race director for the F1/10 (F1tenth) International Autonomous Racing Competitions. He is an associate editor for the SAE Journal on Connected and Autonomous Vehciles, and a guest editor for the Journal of Field Robotics. He also serves on the on the Academic Advisory Council of the Partners for Automated Vehicle Education (PAVE) campaign, to help promote public understanding about autonomous vehicles and their potential benefits. Dr. Behl is an IEEE Senior Member and the recipient of the NSF CAREER Award (2021).
I am looking for PhD students and postdocs with a strong background and publication record in robotics, autonomous systems, and cyber-physical systems.
If you are a student at UVA and are interested in autonomous racing research, please consider joining the Cavalier Autonomous Racing Club autonomousracing.dev/
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Research
I conduct research at the confluence of Machine Learning, Predictive Control, and Artificial Intelligence with applications in Cyber-Physical Systems, Autonomous Systems, Robotics, and Smart Cities.
Examples include: fully autonomous racing at the limits of control (Agile Autonomy), safety of autonomous vehicles (Safe Autonomy), data predictive control for flooding in coastal cities, and AI for building energy optimization.
DeepRacing
Safe and Agile Autonomous Vehicles
Scenario2Vector
Automated Embeddings for Traffic Scenarios
dMIST
Data-driven Stormwater and Transportation management
Data Predictive Control (DPC)
Bridging the gap between machine learning and predicitve control synthesis.
F1/10 Autonomous Racing
Build, drive, and race 1/10 scale autonomus cars at the limits of control.
Interactive analytics (IAX)
Answering open-eneded queries using procedural generation and interpretable models.
Model-IQ
Uncertainity propagation from sensor placement to data quality to modeling to control.
MLE+
An open integerated toolbox for cosimulation between MATLAB and EnergyPlus
Green Scheduling
A scalable and lightweight scheduling approach for peak power reduction in buildings.
Enroute
An energy router for peak power reduction in buildings.
mRK OS
NanoRK real time operating system on the mbed (ARM) microcontroller
Gesture Control
Controlling DICOM (medical imaging) viewers with hand gestures.
Get in Touch
Contact:
Office: Link Lab Room 265
Phone: +1 (434) 924-1021
Email: madhur.behl@virginia.edu
Encrypted: madhurbehl@protonmail.com
Office hours: By appointment only
Mailing Address:
Madhur Behl
Link Lab Room 265 , Olsson Hall,
151 Engineers Way,
University of Virginia
Charlottesville, VA 22903
