Notable Projects
Denoising images with Convolutional Autoencoder.
This Project demonstrates the implementation of a deep convolutional autoencoder for image denoising, mapping noisy digits images from the MNIST dataset to clean digits images.
Project Link: Github Repository
Computational-Statistical Tradeoffs in learning Graphical models
In this project we explore the computational statistical tradeoffs in structure learning of graphical models.
Project Report: Pdf
Structure Learning in Gaussian Graphical Models
In this project, I breifly discussed some popular structure learning algorithms for Gaussian graphical models and their theoretical guarantees.
Project Report: Pdf
Tensor SVD: Statistical and Computational Limits
Singular value decomposition (SVD) and principal component analysis has been an important tool in multivariate and high dimensional data analysis and have been thoroughly studied in the case of matrices, however they only capture first order interactions and ignore higher order ones. In this project we explore the statistical and computational limits for the Tensor SVD problem.
Project Report: Pdf
An Information-Theoretic Approach towards Understanding the Utility-privacy Tradeoffs in Databases.
Project Report: Pdf
Implementing Recurrent Neural Network (RNN) and Long Short Term Memory (LSTM) for Electric Vehicle charging demand prediction.
In this project I used RNN and LSTM to predict time series demand for a electric vehcile chargins station. charging station.
Project Link: Github Repository
Finding optimal policy using Policy Iteration for Electric Vehicle charging demand prediction.
Increasing growing of electricity demand and environmental issues bring huge incentives to electric vehicles (EVs) market. EVs will improve the functionalities of present power system. On the other hand, unscheduled high penetration of EVs may have detrimental effects on power system performance. This project studies the electric EV charging scheduling problem under a charging station scenario, aiming to offer an optimal policy to optimize the battery configuration based on load prediction.
Project Link: Github Repository
Support Vector Machine classifier
Project Link: Github Repository
Implementing the tabular Q-learning algorithm for three standard control problem mountain car, cart pole, and acrobat.
Brief description required
Project Link: Github Repository
Balancing between Electric Vehicle Charging Station Income and Users Cost using Reinforcement Learning
Increasing growing of electricity demand and environmental issues bring huge incentives to electric vehicles (EVs) market. EVs will improve the functionalities of present power system. On the other hand, unscheduled high penetration of EVs may have detrimental effects on power system performance. This project studies the electric EV charging scheduling problem under a charging station scenario, aiming to offer an optimal policy to optimize the battery configuration based on load prediction.
Project Report: Pdf