Publications
Research contributions in machine learning, computer vision, and medical AI. Focus on practical applications and reproducible methodologies.
LMMs for Histopathology
ICAIP 2025
Evaluation of commercial multimodal systems for patch-level classification across multiple datasets. Focus on prompt strategy and transfer behavior.
Key Contributions:
- GPT models consistently outperformed Gemini across datasets
- Few-shot fine-tuning with limited samples achieved strong performance
- Cross-domain transfer learning insights for medical imaging
Mycobacteria Detection Models
ICAIP 2025
Comparative study of CNNs and ViTs with augmentation and ensembles for Ziehl–Neelsen detection.
Key Contributions:
- Comprehensive benchmark of modern architectures
- Ensemble methods achieving state-of-the-art performance
- Systematic analysis of augmentation strategies
Research Philosophy
Research should bridge theory and practice. Every project emphasizes reproducibility, careful validation, and real-world applicability. Focus on methodologies that can scale from academic benchmarks to production systems.