Latest Work


Get a glimpse of all the projects I have worked on

Time Series Forecasting
This project performs exploratory data analysis on India's Air Quality dataset to understand patterns and trends. It is also using random forests, LSTM, and CNN architectures to forecast future quality levels. This project has the potential to make a significant contribution to the understanding and management of air pollution in India.

India Air Quality Analysis

October 2023

Machine Learning
The aim of this project is to collect and organize data from different sources of job listings. It then conducts a descriptive analysis of the data and identifies the most frequent skills demanded by employers.

Job Statistics Scraper

February 2023

Machine Learning
FeReD is a system that contrasts the performance of cross-device federation using Q-learning. It offers step-by-step guidance for in-DBMS SQLite implementation challenges for both horizontal and vertical data partitioning. FeReD also allows to contrast the Q-learning implementations in SQLite vs a standard Python implementation.

Federated RL in the DBMS

October 2022

Augmented Reality
For the ARVR course of M2 MoSIG, I developed a media controller that uses the device's sensors to interact with different media types. The controller is written in Python and runs on Android devices. It allows the user to control the playback of audio and video files by tilting, shaking or tapping the device.

Sensor Media Control

January 2022

Machine Learning
This Acumen example demonstrates how utilizing machine learning can be used to enhance Cyber-physical systems to achieve intelligent behavior. Creating autonomous agents and utilizing a state-action-reward-state approach, they are capable of learning how to optimize their behavior and react to an unknown environment.

Reinforcement Learning in Acumen

June 2021

Machine Learning
Here you can find a variety of AI techniques and approaches that are designed for different purposes and applications.

A.I Algortihms

April 2021

Optimization
In computation intelligence, PSO is a computational method to optimize an objective function. It is a stochasticsearching method, which in contrast to many other optimization algorithms, it does not compute the gradient. It is also usually used in problems where the variables take uniform values.

Particle Swarm Optimization

May 2020

Compilers
This is a LL(1) Parser which includes an integrated graphical user interface. This application is intended for computer science students and autodidacts studying compilers or parsers.

LL(1) Compiler

June 2017