Welcome to my Page
I have worked in the fields of research, data analytics, programming, artificial intelligence, and business intelligence with renowned research groups and international projects. Motivated to work on impactful and meaningful projects.
Freiheit (English: 'Freedom') is an initiative designed to assist blind and visually impaired individuals with their daily tasks, fostering greater independence. Freiheit incorporates various use cases from daily life, which are identified by exploring different sources.
We model database in three different plateforms (SQL, NOSQL, Cloud) for a fictitious startup called Sparkify (new music streaming app) to analyse user behaviour. A complete implementation of dataset cleaning, analysis, data modelling, ETL pipelines design in PostgreSQL (psycopg2), NOSQL (Apache Cassandra), and Amazon RedShift (boto3) to find insights with SQL queries.
We will help the management team track their KPIs like sales, revenue, profit and returns, compare performance across regions, analyze product-level trends, and identify high-value customers. we will use Power BI desktop to connect and transform raw data, build a relational data model, create calculated columns and measures with DAX, and finally, design an interactive dashboard to help visualize and analyze the data.
Most of us have thought once about building our own an iOS or Android app. In this work, we will do a comprehensive analysis of the Android app market by comparing thousands of apps in the Google Play store.
The goal of this project, as part of DengAI competition, is to develop a predictive model that accurately forecasts the total number of dengue fever cases in San Juan and Iquitos based on historical, climatic, and environmental data.
We investigate the use of Graph NN's to predict atomisation energy at 0K for molecules with the QM9 dataset so to bypass the use of network input descriptors so called "symmetry functions" without providing the explicit atomic positions. For this purpose, we have used graph convolutional network (GCN) and relational graph convolutional networks (RGCN)
Analysis and visualisation, finding optimal number of clusters using elbow method and clustering using k-means on molecular simulation datasets.
A user-friendly and robust package giving user an ability to plot stationary levels with the user-defined parameters, so that one is not bounded to predefined inputs. It also gives user to save diagram in any format and user-defined dpi and size.
Analysis and visualisation of digit dataset and decision boundary via implementing principal componant analysis in 2 subspace and linear regression
Visualisation of eigenfaces with implementation of Principal component analysis in Python