Curriculum vitae

Background & experience.

Download full CV ↗

Education

PhD, Electrical and Computer Engineering — UCSB, Jan 2026–Present. Thesis: Probabilistic Approximate Optimization; GPA 4.0/4.0.
MSc, Electrical and Computer Engineering — UCSB, Sep 2023–Dec 2025; GPA 4.0/4.0.
BSc, Electrical and Electronics Engineering — KFUPM, Sep 2017–May 2022; ranked 1st, GPA 3.99/4.0.

Technical skills

Python, C++, MATLAB, PyTorch, NumPy
Monte Carlo methods, stochastic optimization, probabilistic modeling
FPGA, HPC, parallel and hardware-accelerated computing

Experience

May 2026–Present

Handshake AI Fellow — Trainer and Reviewer

Completed 20+ graduate-level STEM benchmark problems, each rated 5/5 across three review stages. Developed long-form AI evaluations for electrical and computer engineering workflows.

Sep 2023–Present

Graduate Student Researcher, OPUS Lab, UCSB

Research and paper stories ↗

OPUS profile ↗

Aug 2022–Sep 2023

Data Scientist, Computer Vision, Wakeb

Deployed computer vision systems ↗

Aug 2020–Sep 2022

Researcher, Neurotronics Lab, KFUPM

Lab profile ↗

Jun 2020–Sep 2020

Research Intern, Information Science Lab, KAUST

KAUST profile ↗

Awards and service

International Doctoral Recruitment Fellowship, UCSB.
Ranked 3rd in a poster competition at the Future of Semiconductor Forum, KAUST, 2026. Poster note.
Best Senior Design Project, KFUPM, 2022. Manuscript and code.
Referee activity for Science Advances and IEEE Journal on Exploratory Solid-State Computational Devices and Circuits.

Invited talks

Sep 1, 2026 · UCSB

Is Quantum Advantage Overhyped? A Probabilistic Analogue to QAOA

Jun 15, 2026 · UCSB

Accelerated Convergence in Glassy Energy Landscapes via Variational Learning

Recording

Nov 21, 2025

Learning the Sampler: The Probabilistic Approximate Optimization Algorithm

Video Slides

Oct 31, 2025

Bypassing Non-differentiability Straight-Through and Applications

Slides

Dec 3, 2024

ADAM Optimizer: History, Convergence, and Practical Insights

Video Slides