Research
Questions I might spend years trying to answer.
This is not a finished research profile yet. It is where I keep the questions.
My work is currently moving towards artificial intelligence, machine learning, deep learning, trustworthy AI, traceability, explainability, and human-AI decision support.
I am especially interested in the gap between a model producing an answer and a human being able to trust, verify, and act on it. That gap is not a UX problem. It is a fundamentally hard problem in epistemics, system design, and the relationship between algorithmic reasoning and human judgement.
Research focus areas
Trustworthy AI
How do we design AI systems that can be checked, challenged, and trusted? Not just through performance metrics, but through transparency of process, auditability of decisions, and the ability to fail gracefully.
Traceability
How do we preserve the trail between data, reasoning, output, and decision? I am interested in the chain of provenance: from source to inference, from evidence to conclusion.
Human-AI Collaboration
How do we design systems where AI helps humans think better, rather than replacing judgement with automation? The interface between human cognition and machine output is one of the most underexplored problems in applied AI.
Knowledge Graphs and Memory
How do we structure information so that ideas can be found, connected, and reused over time? This links to Curio Synapse: building systems that preserve the trail of learning.
Deep Learning Foundations
What makes modern neural networks powerful, fragile, interpretable, or opaque? Understanding the mechanisms under the performance numbers matters if we want to build systems we can trust.
Active question
How do we build AI systems that can explain where their answers came from?
Not just with a citation pasted underneath, but with a real trail of reasoning, evidence, uncertainty, and context. The answer sits somewhere between knowledge graphs, natural language reasoning, information retrieval, and the philosophy of evidence.
Research seeds
These are early-stage notes connected to research questions. Some will grow into proper essays or paper notes.
- essay
He Asked for Water. His Son Threw Him in the Sea. This is an AI Problem.
What a Arabic proverb and a drowning man can teach us about how we state problems in AI. The right question is half the answer. The wrong goal is all the danger.
- research-seed
AI Traceability: The Gap Between Answer and Trust
AI systems can produce confident answers with no trail of reasoning behind them. This is not just a UX problem. It is a fundamental problem in epistemics and system design.
- essay
What Start With Why Actually Changed in How I Think
Sinek's book is easy to dismiss as business self-help. But asking why before what changed how I approach problems in ways I did not expect.
Neural Map
See how research seeds, reading notes, and essays connect in the Neural Map.