AZ Hourani

I’m Abdulla Zahi Hourani. Most people call me Hourani or AZ (Azee). I’m a physician in my internship year, a PhD candidate and a self-taught software engineer with professional experience in senior machine learning roles. My clinical interests span internal medicine, particularly internal medicine (all subfields), neuropsychology, immunology, and transplantology.

My path into AI began with a love of maths and physics at school. During medical school, biophysics connected those interests to the human body and gave me another way to think about disease. I began teaching myself statistics, research methods and programming, initially to analyse research data. I wanted to understand the mathematics behind the methods and the assumptions that made an analysis meaningful. I pursued these interests alongside a strong academic record in medicine, clinical teaching and student mentoring.

That curiosity gradually grew into broader engineering work. I learned to build across databases, data pipelines, backend services and user interfaces, following ideas through to working software. My professional experience has included complex multimodal agentic system inferred locally, live prediction pipelines for time-series finance data and language models SFT and RL. My doctoral thesis is titled “Trustworthy artificial intelligence in nephrology: Development and evaluation of predictive and agentic systems.” It brings together my clinical knowledge, mathematics and engineering to investigate how AI might help clinicians anticipate risk and make better decisions. I’m building the data pipelines to normalise databases from various sources, training the models and archetictures, building the software to infer these models, and integrating them in hardware for local inference for final validation.

I also serve as a board member of the European Renal Association’s Artificial Intelligence Committee. I share my work through invited talks and contribute as a peer reviewer for AI research.Through Project Quintessence, a research team, I founded and lead, I bring clinical research and practical engineering together with people I have met through conferences, travel and online communities to produce useful research and AI artifacts. Teaching and mentoring have also been part of that journey, including supervising student research, instructing basic and advanced life support, and delivering workshops on ECG interpretation and point-of-care ultrasound.

I spend so much time on this work because I care about where it will lead, and because I’m happy doing it. I want to help people have more healthy years to enjoy. I also love learning something unfamiliar, making something work and untangling a difficult problem. People who know me well often notice how much I enjoy it; and how hard it can be to pull me away.

Outside work, I enjoy quality time with family and friends, sports, reading, experimenting and travelling. I’m interested in history, economics, linguistics, psychology, art and science.