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I am an assistant professor at the University of Maryland, College Park, with a joint appointment at the Institute for Systems Research and Aerospace Engineering. Browse around for more information.


I received my Ph.D. in Mechanical Engineering from the California Institute of Technology in June 2013. Before that, I graduated from Harvard University with my S.B. in Mechanical Engineering and Material Science in 2007. My dissertation focused on using formal methods and specification languages in the design and analysis of large-scale, complex, distributed sensing, actuation, and control systems with an emphasis on correct-by-construction control synthesis.

Curriculum Vitae available here.

Dissertation available here.

My research interests comprise the areas of control and dynamical systems, optimization, and formal methods with applications in autonomy, planning, and system identification. In particular, I am interested in developing and designing robust cyber-physical systems that are capable of performing high-level, complex goals while reacting to dynamic and possibly adversarial environments. The overall research goal is to provide provably correct results through the use of three key aspects from my research: (1) rigorous theory drawn from mathematics, controls, and computer science (e.g., graph theory and formal methods); (2) computational tractability and how complexity may be overcome through decompositions and interface contracts; and (3) applications to real-world/industry problems (e.g., smart-grid, autonomous vehicles, security of cyber-physical systems).

Distributed Sense and Control

Distributed sense and control systems combining large numbers of heterogeneous components have wide-reaching applications, from energy management (power grid monitoring and traffic control) to autonomous vehicles and aircraft. The unexpected interactions of a large number of interdependent subsystems in the design of such large-scale applications means a greater emphasis must be made on design methodologies that can provide guarantees on behavior and execution. My dissertation research revolves around the design and analysis of large-scale, complex, distributed sensing, actuation, and control systems with an emphasis on correct-by-construction control synthesis from formal specifications. Using an aircraft electric power system as a case example, I have demonstrated how a complete design methodology can be used from beginning optimal design of base topologies to formalization of requirements to automatic synthesis of reactive control protocols.

Temporal Logic Planning

Temporal logic planning is at the intersection of formal methods, automata theory, and control theory. It provides a hierarchical framework for synthesizing controllers based on a system’s intended behavior requirements. Reactive discrete planners are implemented at the high-level while continuous controllers, which implement the discrete plan, are used at the low-level. In my recent work, I have extended the temporal logic planning framework in two ways and applied these ideas to the application domain of aircraft vehicle management systems. The first extension has been the conversion of high-level system requirements into a formal specification language. I have created an aircraft electric power system domain-specific language that can be used, in conjunction with its associated program code, to automatically convert common domain-specific requirements into a formal specification language compatible with current synthesis solvers. The second extension has been developing a formalism for synthesizing correct-by-construction timed and untimed protocols from temporal logic specifications for aircraft electric power systems. I have proposed a framework for writing specifications in a compact manner. Furthermore, I have utilized previous work on distributed synthesis to reduce computational complexity and enhance design modularity for these large-scale, complex systems.

Current Projects

Mission planning for autonomous systems in dynamic environments using open-source autopilots/NAVAIR

This project investigates the integration and certification of open source autopilots in unmanned aerial vehicles using motion planning as a formal framework. The objective is for UMD to develop autopilot architectures and mission planning algorithms using open-source software and off-the-shelf autopilots (e.g., Navio2).

Non-Cooperative Detect and Avoid Capabilities for UAS Platforms/Lockheed Martin

This project leverages University of Maryland research in the areas of UAS detection for counter-UAS applications and autonomous vehicle path and trajectory planning to address non-cooperative detect and avoid capability for UAS systems.

Real-Time Flight Planning Simulation Software for Unmanned Aircraft Systems/Millennium Engineering and Integration

This project aims to develop and demonstrate a real-time flight simulation tool that integrates mission planning, ground command/control, onboard situational awareness, and onboard re-planning for unmanned aircraft vehicles (UAV). The tool will aid in the assessment of potential flight-safety hardware subsystems and embedded algorithmic solutions to enable operation of UAVs within the National Airspace (NAS) and uncontrolled urban airspace.

Cybersecurity Detection for UAVs/MITRE

The main goal of this project is to provide theoretical guarantees on the ability to estimate and recover from security threats to cyberphysical systems. We aim to develop a simulation and hardware testbed in which the proposed mathematical framework can be used to detect, assess, and recover from threats (both internal and external).

AUVSI SUAS Competition

The Student Unmanned Aircraft Systems (SUAS) Competition, aimed at stimulating and fostering interest in unmanned air systems, technologies and careers, focuses on engaging students in a challenging mission. It requires the design, integration, and demonstration of a system capable of conducting air operations, which include autonomous flight, navigation of a specified course, and use of onboard payload sensors.


Journal Publications

  • Specification and Synthesis for Aircraft Electric Power Distribution. H. Xu, U. Topcu, and R. M. Murray. In: IEEE Transactions on Networked Control Systems. 2015. Accepted

  • Control Software Synthesis for A Vehicular Electric Power Distribution Testbed. R. Rogersten, H. Xu, N. Ozay, U. Topcu, and R. M. Murray. In: Journal of Aerospace Information Systems. 11:10, 665-678 2015. Accepted [Link]

  • A Contract-Based Methodology for Aircraft Electric Power System Design. P. Nuzzo, H. Xu, N. Ozay, R. M. Murray, A. Sangiovanni-Vincentelli, et al. In: IEEE Access. 2013. [Link]

  • A Domain-Specific Language for Aircraft Electric Power Systems. H. Xu, N. Ozay, and R. M. Murray. In: INCOSE Journal of Systems Engineering. 2013. in prep

  • Peer-Reviewed Conference Publications

  • Broadcasting the Voices of Women in STEM. H. Xu and L. Claiborn. In: IEEE Women in Engineering Summit East, Philadelphia, PA. 2015. [Preprint]

  • Dynamic State Estimation in Distributed Aircraft Electric Control Systems via Adaptive Submodularity. Q. Maillet, H. Xu, N. Ozay, and R. M. Murray. In: IEEE Conference on Decision and Control, 2013. [Link]

  • From Formal Specifications to Software Models and Hardware Implementation of Reactive Protocols: An Aircraft Electric Power Testbed. R. Rogersten, N. Ozay, U. Topcu, H. Xu, and R. M. Murray. In: International Conference on Hybrid Systems: Computation and Control, 2013. [Link]

  • A Case Study on Reactive Protocols for Aircraft Electric Power Distribution H. Xu, U. Topcu, and R. M. Murray. In: IEEE Conference on Decision and Control, 2012.[Link]

  • TuLiP: A Software Toolbox for Receding Horizon Temporal Logic Planning. T. Wongpiromsarn, U. Topcu, N. Ozay, H. Xu and R. M. Murray. In: International Conference on Hybrid Systems: Computation and Control, 2011. [Link]

  • Load-shedding Probabilities of Power Systems with Renewable Power Generation and Energy Storage. H. Xu, U. Topcu, S. Low, C. Clarke, and K. M. Chandy. In: Allerton Conference on Communication, Control, and Computing, 2010. [Link]

  • A Simple Optimal Power Flow Model with Energy Storage. H. Xu, U. Topcu, S. Low, and K. M. Chandy. In: IEEE Conference on Decision and Control, 2010. [Link]

  • The Effect of Pre-Stress Assumptions on Dip-Slip Fault Nucleation. H. Xu, Z. Fang, G. Xu, and D.D. Oglesby In: American Geophysical Union Conference, 2006.

  • Please feel free to email about preprints.


    FALL: ENAE 380 Flight Software Systems

    Avionics using advanced sensor and computing technologies are at the heart of every modern aerospace vehicle. Advanced software systems improve cockpit safety and enable unmanned and deep-space missions. Object-oriented programming and software engineering concepts required to design and build complex flight software systems will be discussed. Other discussions include software validation, verification, real-time performance analysis to assess flight software system reliability and robustness; human-machine interfaces designed for piloted systems; automatic onboard data acquisition and decision-making for unmanned air and space vehicles.

    SPRING: ENES489p Special Topics in Engineering (Hands-On Systems Engineering Projects)

    This hands-on design projects course will expose senior-level undergraduate and graduate-level students from all areas of engineering to exciting career opportunities in the systems engineering field. Students will be introduced to the technical aspects of systems engineering practice through team-based project development and a systematic step-by-step procedure for product development that includes working with a real-world customer to define operations concepts, requirements gathering and organization, synthesis of models of system behavior and system structure, functional allocation to create system design alternatives, formal assessment of design alternatives through tradeoff analysis, and established approaches to testing and validation/verification.


    3180 Glenn L. Martin Building
    College Park, MD 20742
    Phone: +1 301 405 1133