Arin M.

Background

About Arin M.

Experienced researcher with a demonstrated history of research work in academia and related industry. Skilled in data analysis, machine learning, mathematical modelling and optimization, and computer programming. Strong research background with a Doctor of Philosophy (Ph.D.) focused in communications engineering, machine learning and signal processing from University of Toronto. Experienced with- Supervised learning methods: Linear Discriminant Methods, Support Vector Machines, Neural Networks and deep learning (CNNs, MLPs)- Reinforcement learning methods : Deep-reinforcement learning, Markov decision processes, TD learning, Monte-Carlo tree search- Unsupervised learning methods: Principle Component Analysis, Kernel Density Estimation, Manifold Learning, Diffusion Maps and Data Clustering- Model estimation: Mixture Gaussian Modelling and Expectation Maximization, Maximum Likelihood, Least Squares and Minimum Mean Squares Error Estimation- Time series analysis and forecasting: Box-Jenkins method, SARIMA model, Exponential Smoothing, and CNNs- Numerical optimization : Convex and Non-convex Optimization, Simulated Annealing, Particle Swarm Optimization.