Teaching Assistant
Arizona State University- Teaching assistant for EEE 480 – Feedback Systems in Fall 2026
- Teaching assistant for EEE 304 – Signals and Systems II in Spring 2025
- Grader for EEE 511 – Artificial Neural Computation in Fall 2025
About Me
I am a PhD student in the School of Electrical, Computer and Energy Engineering at Arizona State University, where I work under the supervision of Prof. Jennie Si.
My research focuses on bridging the gap between classical control and reinforcement learning, with broader interests in control, reinforcement learning, real-time embedded systems, and optimization. I am particularly interested in applying these methods to challenging problems in aerospace and motorsports.
Prior to joining ASU, I spent a year as a placement student with the Oracle Red Bull Racing Formula 1 Team, working in the Energy Recovery System Control group. At ASU, I was also part of the Data Acquisition team for Sun Devil Motorsports, ASU's Formula SAE team. Alongside my research, I am currently a teaching assistant for EEE 480 – Feedback Systems and have previously served as a teaching assistant for EEE 304 – Signals and Systems II and as a grader for EEE 511 – Artificial Neural Computation.
Experience
August 2025 – Present
Data Acquisition Engineer
Sun Devil Motorsports- Designed and implemented the embedded software for the Inertial Measurement Unit (IMU) for the Formula SAE car on an ESP32-S3 microcontroller
- Implemented an asynchronous sensor fusion algorithm to estimate vehicle state using IMU and GPS data
Energy Recovery System Control – Student Placement
Oracle Red Bull Racing- Developed and tested Hardware-in-the-Loop (HIL) models for the Energy Recovery System using Simulink Real-Time and HDL Coder
- Developed embedded software for NXP S32K1 and S32K3 microcontrollers in C
- Developed standalone MATLAB applications for automated testing of electric powertrain components
- Supported the battery production testing software
- Worked with protocols including CAN, SPI, I2C, TCP, UDP, Modbus and SCPI
Research and Development Engineer
dox Technologies Inc.- Led the research on lithium-ion battery modeling and battery management algorithms
- Created a research database with over 40 state-of-the-art papers studying State-of-Charge and State-of-Health estimation, power and energy limits, and battery test planning
- Implemented a lithium-ion battery simulation library in Python for cloud simulations with less than 2% Mean Absolute Error
Projects
Trajectory Optimization and MPC for Fuel-Optimal Rocket Landing
Developed a hierarchical guidance framework for the fuel-optimal landing of a reusable rocket. A nonlinear trajectory optimization problem was solved using successive convexification to generate a fuel-optimal reference trajectory, which was then tracked in real time using Model Predictive Control. The framework was implemented in Python with CVXPY and validated in simulation.
GPS-Aided 2D Inertial Navigation System for Formula SAE Car
Developed a GPS-aided Inertial Navigation System for vehicle state estimation, designed as a foundation for the ASU Formula SAE car. The system fuses high-rate IMU measurements with lower-rate GPS data asynchronously, using a bank of Linear and Extended Kalman Filters to estimate vehicle position, velocity, acceleration, heading, and gyroscope bias.
Model Predictive Control for F1TENTH Autonomous Car
Developed a Model Predictive Controller for autonomous racing with an F1TENTH RC car. The controller follows a reference racing line to navigate the track, with the control algorithm implemented as a ROS 2 node and tested in the F1TENTH Gym simulation environment. The project also integrates a Docker-based ROS 2 simulation stack and data logging using Foxglove.
Education
Ph.D. in Electrical Engineering
Arizona State University
2026 – PresentGPA: 4.00 / 4.00
M.S. in Electrical Engineering
Arizona State University
2025 – 2026GPA: 4.00 / 4.00
B.E. in Electrical Engineering
Lebanese American University
2019 – 2024GPA: 3.99 / 4.00
Courses
Arizona State University
Graduate- Optimal Control
- Adaptive Control
- Reinforcement Learning in Robotics
- Real-Time Embedded Systems
- Convex Optimization
- Data-Driven Dynamical Systems Analysis and Control
- AI-Based Decision Making in Dynamic Systems
- Sensors and Machine Learning
- Probability and Random Processes
- Multidimensional Signal Processing
Lebanese American University
Undergraduate- Intelligent Engineering Algorithms
- Control Systems
- Embedded Systems
- Microprocessors
- Energy Storage Systems
- Simulation of Electronic Circuits
- Objects and Data Abstraction
- Computer Networks
- Power Systems
- Smart Grids
- Communication Systems
- Electromechanics
- Electromagnetic Waves
- Electromagnetic Fields
- Signals and Systems
- Electrical Circuits
- Differential Equations
- Calculus
- Discrete Structures
- Probability and Statistics
Independent Coursework
Online & Open Courses- Advanced Robotics – UC Berkeley
- F1TENTH Autonomous Racing – University of Pennsylvania