I am an Assistant Professor in the Department of Mechanical Engineering at the University of Maryland Baltimore County, where I direct the Estimation, Control, and Learning Laboratory (ECLL). My research is focused on developing data-driven, learning-based control and estimation techniques for mechanical and aerospace engineering problems. Specifically, we use tools from linear and nonlinear system theory, linear and nonlinear control theory, optimization, and learning theory to design and develop novel algorithms for control and estimation problems in complex dynamic systems, including applications in robotics, autonomous systems, and UAVs. Current research in our group is focused on the following areas:

Control of Cyber-physical Systems

  • We develop control techniques using theoretical tools, simulation-based numerical experiments, and machine learning techniques for complex cyber-physical systems operating in uncertain and unknown environments.
  • Current research is focused on developing learning autopilot for aircraft and multicopters that can learn using measured data in real-time, expands the operational envelope, and reduce failure in the event of sudden dynamic changes in the environment.
  • Applications include Autonomous vehicles, industrial robots, and autopilots.

Learning in Complex Systems

  • We develop computationally efficient, data-driven, learning-based techniques for estimating states and parameters of complex dynamic systems such as atmospheric and flow models.
  • Current research is focused on developing computationally inexpensive methods that will improve prediction accuracy and enable the implementation of complex control systems in real time to improve system performance.

 

Core research focus areas

Education

Ph.D., Aerospace Engineering, University of Michigan, Ann Arbor, 2019.

M.S., Aerospace Engineering, University of Michigan, Ann Arbor, 2014.

B.E., Mechanical Engineering, Delhi College of Engineering, Delhi, 2009.

Teaching

  • University of Maryland, Baltimore County
    • ENME 303 Computational Methods for Engineers (Fall 2024, Fall 2023).
    • ENME 403 Automatic Controls (Spring 2025, Spring 2024, Spring 2023, Fall 2021).
    • ENME 664 Advanced Dynamics (Fall 2022).
    • ENME 605 Advanced Control Systems (Fall 2024, Fall 2023, Spring 2022).
  • The University of Michigan, Ann Arbor
    • Guest lectures in AEROSP 584 Guidance and Navigation for Aerospace Applications (Fall 2020).
    • Guest lectures in AEROSP 566 System Identification (Fall 2018).

Publications

The most up-to-date list of my publications can be found on Google Scholar.

2024 Highlights

  • We added 6 new members to ECLL:
    • Mohammad (January)
    • Conor(January)
    • Alex (April)
    • Juan (August)
    • Faith (November)
    • Aiden (December)
  • Parham successfully defended his Masters thesis!!
  • Our group presented several papers at the most prestigious control conferences
    • 3 papers at AIAA Scitech 2024 Forum in January
    • 5 papers at 2024 American Control Conference in July
    • 2 papers at ICMLA’24 in December
    • will present 2 papers in the upcoming AIAA Scitech 2025 Forum in January
  • Our group submitted 7 papers to 2025 American Control Conference and 1 paper to 2025 IEEE International Conference on Robotics & Automation
  • Our group got funded to start Quantum Control in July 2024 and we initiated three new research proposals in 2024
  • Our group submitted 3 journal papers in 2024