Medical Doctor · Medical Computer Scientist

I work at the intersection of medicine, artificial intelligence, and knowledge representation. My research focuses on developing interpretable computational methods for reasoning over imperfect clinical data—data that may be incomplete, noisy, heterogeneous, or temporally inconsistent.

• Knowledge Representation and Reasoning
• Temporal Reasoning and Event Recognition
• Inductive Logic Programming
• Answer Set Programming
• Explainable and Neuro-Symbolic AI
• Clinical Data Integration
• Reasoning under Uncertainty

I develop methods that transform longitudinal medical observations into structured, clinically meaningful knowledge.

My current work includes:

• HEVA, a logic-based framework for identifying high-level temporal events from timestamped medical observations.
• Learning interpretable temporal rules from clinical data using Inductive Logic Programming (ILP) and Answer Set Programming (ASP).
• Developing explainability and provenance mechanisms that connect inferred clinical events to their supporting observations and rules.
• Applying these approaches to clinical domains including acute kidney injury and lung cancer.
• Exploring neuro-symbolic approaches that combine logical reasoning, statistical learning, and uncertainty modelling.

As a physician, I bring a clinical perspective to the design of medical AI systems. My experience in medicine motivates me to develop methods that are not only computationally effective, but also transparent, verifiable, and meaningful to healthcare professionals.

As a medical computer scientist, I investigate how symbolic and neuro-symbolic approaches can help machines represent medical knowledge, reason over time, and remain useful when clinical information is imperfect.

I am interested in collaborating with researchers, healthcare professionals, and engineers working on:

• Explainable and trustworthy medical AI
• Temporal and longitudinal clinical data
• Logic-based and neuro-symbolic learning
• Knowledge representation in medicine
• Clinical decision-support systems

📧 yvon.awuklu@gmail.com
🔗 LinkedIn

Turning imperfect medical data into interpretable knowledge for better care.