Vinay Kumar Singh
Here are a few topis for research in Machine Learning:
Mining and Text Classification
Image-Based Applications
Machine Vision
Clustering
Voice Classification
Object detection
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Nipun Shantha Kahatapitiya
Surrogate Modeling: Using ML to create simplified models of complex physical systems for faster simulations and improved understanding. Data-driven Discovery: Employing ML to find patterns and relationships in data to make new scientific discoveries and develop innovative products. Inverse Problems: Solving problems that infer underlying causes from observations using machine learning techniques. Computer-Aided Engineering (CAE): Enhancing accuracy and efficiency in engineering simulations and automating the design process with ML. Healthcare Applications: Utilizing ML in medical image analysis, drug discovery, and personalized medicine for advanced healthcare solutions.
These topics represent some of the exciting frontiers where machine learning is making significant contributions to computational science and engineering research.
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