Meet Our CEO
The person behind Abdora.ai
Alaa Suliman, PhD
Chief Executive Officer & Co-Founder
Alaa founded Abdora.ai because he saw a gap in how AI was being used in healthcare. Most tools just flag abnormalities without any explanation. He wanted to build something different: an AI that actually shows its reasoning, so patients can understand their results and doctors can trust what they see.
He holds a PhD in Artificial Intelligence from the National University of Malaysia (UKM), with a focus on medical image analysis and computational pathology. His doctoral work developed AI-driven methods for analyzing medical images and pathology data, laying the foundation for the clinical AI systems he builds today at Abdora.
His published research spans medical image segmentation, transformer architectures for clinical imaging, and AI-based gene selection for cancer diagnosis — with work appearing in peer-reviewed journals and conferences including Medical Image Analysis, MICCAI, and Heliyon (Cell Press).
At Abdora, he leads the technical vision and is hands-on with everything from the core reasoning engine to product decisions and clinical partnerships. He believes that if you can't explain why an AI reached a conclusion, it shouldn't be used in medicine.
Education & Research
PhD in Artificial Intelligence
National University of Malaysia (Universiti Kebangsaan Malaysia — UKM)
2014 – 2020
Specialization in AI, medical image analysis, and computational pathology. Research focused on developing AI models for clinical imaging and pathology-based diagnosis, with applications in cancer detection, cell segmentation, and clinically deployable AI systems.
Artificial Intelligence
Deep learning, explainable AI, and machine learning for healthcare applications
Medical Image Analysis
Segmentation, classification, and AI-driven interpretation of clinical imaging
Computational Pathology
AI models for pathology diagnosis, cell segmentation, and clinical decision support
Selected Publications
Peer-reviewed work at the intersection of AI and medicine
A hybrid of an automated multi-filter with a spatial bound particle swarm optimization for gene selection and cancer classification
Heliyon (Cell Press) · 2025
Developed a hybrid AI method combining multi-filter feature selection with swarm intelligence for identifying cancer-related genes from high-dimensional microarray data.
Unlocking Fine-Grained Details with Wavelet-Based High-Frequency Enhancement in Transformers
MICCAI 2023 Workshop (MLMI) — Springer · 2023
Proposed a novel wavelet-based transformer architecture for medical image segmentation, improving accuracy on multi-organ and skin lesion benchmarks by preserving fine-grained anatomical details.
SegPC-2021: A challenge & dataset on segmentation of Multiple Myeloma plasma cells from microscopic images
Medical Image Analysis (Elsevier) · 2022
Co-authored a benchmark dataset and challenge for AI-driven segmentation of cancer cells from microscopic bone marrow images, advancing automated diagnosis of Multiple Myeloma.
Why we started Abdora
“When someone gets an AI report on their scan, they should be able to understand why the AI said what it said. And when a doctor uses AI for a second opinion, they need to see the full reasoning, not just a label. That's the whole point of what we're doing at Abdora.”
Alaa Suliman, PhD
Focus areas
Vision & Strategy
Setting the direction for Abdora and making sure we build something that actually helps people
AI & Machine Learning
Hands-on with the models, especially explainable AI and reasoning for medical imaging
Medical Imaging
Working across X-ray, CT, and MRI to build real diagnostic tools
Healthcare Innovation
Turning AI research into products that doctors and patients can use today
See what we're building
Try Abdora's reasoning AI for medical imaging