My research focuses on the intersection of Machine Learning, Biocomputing, and Engineering. Key areas of interest include:
- Efficient AI: Low-Rank Adaptation (LoRA) and efficient model training techniques.
- Explainable AI (XAI): Developing interpretable models for complex industrial and medical data.
- Biocomputing & Healthcare: Machine learning applications in gastric cancer detection, Parkinson's diagnosis, and biomaterials.
- Predictive Modeling: Time series prediction and chaotic systems using Recurrent Fuzzy Neural Networks.
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