Research Areas
Exploring the frontiers of mathematics and artificial intelligence.
Machine Learning & Deep Learning
Developing novel algorithms for Support Vector Machines, Neural Networks, and Deep Learning architectures with applications in medical imaging and classification.
Key Topics
- Support Vector Machines
- Convolutional Neural Networks
- Variational Autoencoders
- PyTorch & TensorFlow
Optimization Theory
Advanced research in convex optimization, robust optimization, and optimality conditions for complex mathematical programming problems.
Key Topics
- Convex Optimization
- Robust Optimization
- Semidefinite Programming
- Approximation Theory
Fixed Point Theory
Theoretical and computational aspects of fixed point theory with applications to equilibrium problems and variational inequalities.
Key Topics
- Equilibrium Problems
- Variational Inequalities
- Iterative Methods
- CAT(0) Spaces
Computational Methods
Implementation of algorithms and development of computational tools for solving complex optimization and machine learning problems.
Key Topics
- Python Programming
- R Statistical Computing
- Algorithm Development
- Scientific Computing