Affan Dhankwala

Embedded Systems Engineer

Software Engineer at Raytheon with an MS in Artificial Intelligence from Johns Hopkins and a BS in Computer Engineering from the University of Washington. I work on embedded aerospace systems — low-level C/C++, Linux drivers, and FPGA-backed hardware — and explore machine learning, reinforcement learning, and computer vision. Off the clock, I build and program FPV drones.

Experience

Raytheon

Software Engineer — Sept 2023 – Present

Modernizing the legacy aerospace PATRIOT missile-borne computer, aligning it with modern software designs and FPGA-based hardware. I develop and debug C/C++ software and Linux device drivers on Polarfire SoC, simulate memory-mapped firmware I/O to unblock development in hardware-limited environments, and own the downlink component end-to-end — from architecture and stories through PR validation. I also build and maintain CI/CD pipelines that enforce code quality and design correctness, partnering with firmware, FPGA, quality, and safety teams to deliver safety-critical embedded software.

Microsoft

Software Engineer Intern — May 2018 – Aug 2018

On the Worldwide Learning team, I designed, built, and demoed a Kendo UI video and text highlighting plugin for MOOCs to deepen content interaction and learner engagement. I implemented global and local databases enabling collaborative user annotations, ran user interviews to refine usability, and delivered a fully documented solution with 95% unit-test coverage — reviewed and demoed to senior engineers and management while driving work through agile sprints from planning to deployment.

Languages

C
C++
Python

Machine Learning & AI

PyTorch
Reinforcement Learning
Neural Networks
Computer Vision

Embedded & Systems

Linux Device Drivers
FPGA
PolarFire SoC
Memory-mapped I/O
RTOS Concepts

Tooling & Practice

Git
CI/CD
Agile
Unit Testing

Education

Johns Hopkins University

MS, Artificial Intelligence — Dec 2025

Master of Science in Artificial Intelligence, with coursework and projects spanning machine learning, reinforcement learning, retrieval systems, and computer vision.

University of Washington

BS, Computer Engineering (Minor in Mathematics) — June 2023

Bachelor of Science in Computer Engineering with a minor in Mathematics, focused on embedded systems, hardware/software co-design, and the math foundations behind them.

Projects

Image Classification via PyTorch
Compares fully-connected vs. convolutional networks for image classification on the Intel dataset.
Neural Network Course Project
A feed-forward backprop neural network built from scratch in Python for binary classification.
RL-based Racecar
RL racecar learning optimal driving policies via Value Iteration, Q-Learning, and SARSA.
RL-based Gold Explorer (SARSA vs Q-Learning)
Q-Learning and SARSA agents compete on an 8×8 grid-world gold-hunting task.
RL-based Battleship Game
An RL agent that learns to efficiently locate and sink randomly placed ships on a grid.
Tower-Defense
Tower-defense game where players control Martians placing towers against advancing humans.
FPV Drones
Building and programming custom FPV drones from the ground up — assembling the hardware and writing the flight software myself. A hands-on outlet for the same embedded, controls, and aerospace work I do professionally.