USC University of South Carolina

Welcome to my webpage.
My name is Hazhar Rahmani. I am a PhD candidate in computer science at the University of South Carolina. I recieved my M.Sc. degree in computer science from Sharif University of Science and Technology, Iran, 2012, and B.Sc degree in computer (software) engineering from Iran University of Science and Technology, Iran, 2008. My dissertation, which is supervised by Prof. O'Kane, focuses on automata-theoretic approaches to planning in robotics.

Research Interests:

  • Planning in Robotics
  • Formal Methods in Robotics
  • Computational Geometry
  • Machine Learning


  • Hazhar Rahmani, Dylan A. Shell, Jason M. O'Kane. Planning to Chronicle. Workshop on the Algorithmic Foundations of Robotics (WAFR XIV), 2020.

Research Projects

  • State space reduction of combinatorial filters: Combinatorial filters are formal structures used for filtering, reasoning, and planning in systems that deal with discrete sensory data. This project studies the exact and approximate solutions to the NP-hard problem of state space reduction of such kind of filters.
  • Planning to chronicle: This project focuses on the idea of deploying robots to observe a stochastic process in order to capture a sequence of events that meets specifications given by the user. This idea can be used in applications where we want to use robots to autonomously make a video or a documentary of events that happen unpredictably in an environment. The project proposes mathematical modeling for that purpose and solves in that context, several optimization problems, such as the problem of minimizing the expected time to record a desired video.
  • Sensor selection for detecting deviations from a planned itinerary: This project focuses on the problem of choosing an optimal selection from a set of feasible sensors in the environment to ensure that an agent commits to a pre-disclosed itinerary. This problem is useful in security and surveillance applications, and is also applicable in contexts where one wants to test a hypothesis about the behavior of a robot or a system.
  • Temporal logic planning: Temporal logics, which offer high-level, user-friendly languages for specifying complex missions and tasks, have become very useful tools for planning in robotics. This project considers temporal logic planning with soft constraints and in the context of using robots to make chronicle of events that happen unpredictablly in stochastic environments.

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