Distributed Machine Learning
Research
Publications and academic work
My published research is in medical AI and 3D vision (4 papers, 2 in Q1 journals) through a collaboration between North South University and the University of Adelaide. My core interests lie in distributed machine learning, edge computing, and AI systems — the infrastructure that makes ML workloads run reliably.
Interests
What I work on
Federated and Decentralized Learning
AI Systems
Edge and Cloud Computing
Resource-Efficient AI
Publications
Peer-reviewed work
Unsupervised tooth segmentation from three dimensional scans of the dental arch using domain adaptation of synthetic data
PointNet++ domain adaptation work showing how synthetic-to-real transfer can enable 3D dental scan segmentation without labeled real-world data.
Read PaperApplication of 3D neural networks and explainable AI to classify ICDAS detection system on mandibular molars
3D CNN-based classification combined with explainability to study caries detection on mandibular molar scans.
Read PaperAn application of 3D vision transformers and explainable AI in prosthetic dentistry
Vision transformer work on 3D point cloud representations of dental prosthetics with explainability analysis.
Read PaperDental Loop Chatbot: A prototype large language model framework for dentistry
RAG-oriented work for domain-specific clinical information retrieval and LLM-assisted decision support.
Read PaperResearch Experience
Collaboration and execution
North South University × University of Adelaide
- Implemented PointNet++ domain adaptation for unsupervised segmentation of 3D intraoral CBCT scans.
- Developed Vision Transformer pipelines for 3D point-cloud prosthetic classification with explainability.
- Designed RAG-based clinical retrieval systems for domain-specific dental information access.
- Worked across all four resulting publications with Adelaide collaborators.
Education
Academic base
North South University
Relevant coursework includes machine learning, operating systems, database systems, algorithms, probability and statistics, and pattern recognition.
Thesis / capstone focus: applied deep learning methods for medical image analysis under the supervision of Dr. Nabeel Mohammed.
What's Next
Graduate research
I'm interested in graduate research on the systems side of machine learning — where network constraints, compute limits, and coordination complexity are first-order design problems. Distributed ML, federated learning, edge inference, and resource-aware model execution are the problems I want to work on.