About Me

Hi. My name is Ibrahim. I’m on the fun side of my PhD, and the not-so-fun side of a job search. I went to Vanderbilt University for my PhD and undergraduate studies.

I am exploring full-time opportunities in research & applied science roles, with a focus on machine learning and controls. See my resume for more details.

I have a hobbyist’s interest in electronics, web-development, and technical writing for a broad audience.

I have a professional interest in electrical engineering, machine learning, reinforcement learning, and all manners of quantitative pursuits.


My PhD thesis was on Adaptive Fault-tolerant Control Using Reinforcement Learning. You can read it here. I investigated how to make data-driven control methods more efficient in resource constrained situations where fast adaptation was needed. Specifically, I researched reinforcement learning for fault-tolerant control in unmanned aerial vehicles. I also dabbled in machine learning for control of smart buildings. I was part of the Modeling and Analysis of Complex Systems(MACS) group at Vanderbilt University’s Institute for Software Integrated Systems.

At a couple of internships, I worked with privacy-preserving machine learning, and with digital signal processing for machine learning-based prognostics.

In my undergraduate career, I worked in astrophysics, on dark matter simulations. I also did some research on radiation hardening experiments for electronics in space.

Here are some short videos about some of my work. This is a 60-second description of my current research work:

Here’s a video I made on my previous research project. The video was for my fellowship with the Vanderbilt Institute of Digital Learning where I explored new ways of teaching using digital media.

Out of the lab

I like running, bouldering, playing tennis, and the occasional video game. My favorite genres are sci-fi and epic fantasy. I love to cook. I approach potlucks extremely competitively :)


Thursday, May 25, 2023 | 1 min read
News 2023-11: Public release of multirotor 0.5: a python library for simulating drones. 2023-10: I finished a course on using Langchain for function-calling agents on Deeplearning.ai. 2023-09: I gave an invited talk on demystifying the AI hype at Tennessee State University. 2023-06: I am doing a summer research contract on Genetic Algorithms for robotic path planning. 2023-05: I successfully defended my thesis on Fault-tolerant control using reinforcement learning. 2023-05: Our paper titled “Model-based adaptation for sample efficient transfer in reinforcement learning control of parameter-varying systems” was accepted to IEEE CoDIT 2023.