About
I am a Computer Science Ph.D. researcher at the University of New Mexico working on trustworthy autonomous systems at the intersection of robotics, formal verification, reinforcement learning, and control. My research focuses on developing models, verification methods, and planning/control techniques that provide stronger safety and correctness guarantees for autonomous and cyber-physical systems.
My background spans ROS/ROS 2, distributed robotic systems, stochastic control, reinforcement learning, formal methods, and production software engineering. I also have prior industry experience in robot teleoperation, cloud-connected mobile robotics, backend systems, and secure enterprise software.
Research Interests
Formal Verification for Robotics
Model checking, temporal properties, abstraction, reachability, and verification of robotic software and communication systems.
Safe & Trustworthy Autonomy
Safety-oriented planning and control for autonomous and cyber-physical systems under uncertainty.
Reinforcement Learning & Control
Safe RL, model-based and model-free control, stochastic optimal control, robustness, and performance guarantees.
ROS 2 & Distributed Robotic Systems
Publisher-subscriber semantics, DDS behavior, runtime tracing, queueing, nondeterminism, and communication correctness.
Selected Publications
Current Research Projects
Safe Path Planning for N-CAV
Developing safety-aware planning and abstraction methods for multiple connected and autonomous vehicles using feasible trajectories, backward reachability, partitioning, and compositional reasoning.
Formal Verification of ROS 2 Communication
Modeling ROS 2 publisher-subscriber behavior, including timers, bounded queues, message loss, callback execution, and nondeterministic scheduling, with formal verification of safety and progress properties.
VeriSim
Research on verifiable modeling workflows for neural-network-controlled switched systems, connecting simulation models with formal representations and controller artifacts.
Stochastic Control & Safe Learning
Studying stochastic optimal control, abstraction-based methods, reinforcement learning, robustness under uncertainty, and scalable approaches to safety guarantees.
Research & Professional Experience
Graduate Research Assistant — University of New Mexico
- Conduct research in formal verification, trustworthy autonomy, robotic systems, stochastic control, and learning-based control.
- Develop verification models and analysis tooling for ROS 2 communication and distributed robotic behavior.
- Develop safety-oriented abstraction, reachability, planning, and control methods for autonomous systems.
Graduate Research / Teaching Assistant — Kansas State University
- Conducted research in formal verification, reinforcement learning, and safe robotics.
- Served as a GTA for CIS 200 Programming Fundamentals.
Robotics Developer & Consultant — Northsence
- Developed software infrastructure for remotely operated mobile robots at construction sites.
- Worked on autonomous mobile robots, navigation, simulation, vision-based SLAM, and 3D scene graphs.
- Implemented real-time Internet communication and cloud-connected robot-control infrastructure.
Senior Full-Stack .NET Developer — Part Financial Data Processing Company
- Developed C#/.NET services, REST APIs, and AI-backed services for enterprise banking workflows.
- Designed and implemented public key infrastructure for remote authentication.
- Mentored junior software developers.
Research Assistant — University of Isfahan
- Developed AI systems for authorship attribution and semantic search over historical Persian manuscripts.
- Developed natural-language-processing tools for literature researchers.
Education
Ph.D. in Computer Science — University of New Mexico
Ph.D. Studies in Computer Science — Kansas State University
M.Sc. in Artificial Intelligence & Robotics — University of Isfahan
Thesis: Structured Learning in Markov Random Field for Efficient Inference with Submodular Relaxation Technique.
B.Sc. in Software Engineering — Sajad University of Technology
Technical Skills
Research Notes & Technical Writing
I use this section for technical articles and research notes on robotics, formal methods, reinforcement learning, and trustworthy autonomous systems.
Formal Verification for Robotics
Planned notes on model checking, abstraction, temporal properties, and verification workflows for robotic systems.
Safe Learning-Based Control
Planned notes on robustness, uncertainty, safe reinforcement learning, and connections between formal guarantees and learned controllers.