Hi, I’m Abdullah!

Sr. ML Engineer at Atlassian | Ex-Meta | PhD

RL & multi-Agentic AI for Confluence/Jira Search. On the Central AI team, I’m building and improving SMART Answer generation using RL-based fine-tuned LLMs and multi-Agent AI architecture. Previously at Meta on Ads Ranking, fine-tuning LLaMA 3 for large-scale suggestive ad generation.

I write about RecSys, agentic AI, RL fine-tuning, and what actually ships at scale.

The Evaluation of RecSys, Part 3: The Deep Learning Era (NCF, Wide & Deep, DeepFM, DIN, DLRM, AdaTT)

Part 3 of the series: how DNNs transformed RecSys from 2016 onward. NCF, Wide & Deep, DeepFM, DIN, DLRM, and AdaTT. Architectures, intuition, and where each shines.

The Evaluation of RecSys, Part 2: Factorization Machines and XGBoost

Part 2 of the series: how Factorization Machines generalized MF to arbitrary features, how XGBoost handled non-linear ranking, and the limitations that pushed the field toward deep neural networks.

The Evaluation of RecSys, Part 1: From Content-Based Filtering to Matrix Factorization

Part 1 of a 4-part series tracing how RecSys evolved from content-based filtering through collaborative filtering to matrix factorization, and where each technique falls short, setting up the next breakthrough.