adityakunar / infovis-final-project

Visualized open data about crime and policing in England, Wales and Northern Ireland to reveal patterns in criminal activity across the UK utilizing tableau. Created visually appealing, user‑friendly dashboards to let end‑users explore the data easily and effectively. Applied theoretical concepts of visualising geospatial, multi-dimensional categorical and continuous variables in the data.

• 👋 Hi, I’m @adityakunar. A M.Sc Data Scientist from TU Delft

• 🌱 I’m currently working towards bettering synthetic tabular data generation methods via GANs, read more here->Blog

• 💞️ I’m looking to collaborate on investigating and evaluating privacy and memorization risks associated with training differential private GANs. Read more about my work on differential privacy here->Blog

• 👀 I’m passionate about A.I, machine learning and deep learning. I've worked on the following projects:
  - Fast and Effective Image Classification using MobileNet+SSD: To achieve a fast and effective image classifier, studied the integration of the MobileNet architecture into the Single Shot Detector (SSD) framework in pytorch, check out our work here -> Blog
  - Processing GDelt Dataset in Apache Spark and AWS: Analysed how to optimally extract insights from the GDELT dataset using Apache Spark and AWS, read more here->Blog
  - A Reproduction of Dropout for Deep Neural Networks: For effectively preventing overfitting in deep neural networks, studied dropout as a regularizer for deep neural networks using pytorch, read more about our work-> Blog
  - Cyber Data Analytics: Executed effective class imbalance learning and anomoly detection for static and time-series data using python
  - Multivariate Data Analysis: Worked on MAP estimation for classifying healthy and diseases samples in ECG data, as well as assignments related to Bayesian regression, generalised linear models, Gibbs sampling and Gaussian process classification
  - Data Visualization in Tableau: Created visually appealing, user‑friendly dashboards to let end‑users explore open data about crime and policing in the UK easily and effectively
  - Research Methodology for Data Science: Worked on linear/logistic regression models and scientifically tested hypotheses in R; examined optimizing dimensionality reduction techniques like PCA for high dimensional datasets in MATLAB
  - Natural Language Processing: Built a fake news detector using python by implementing the techniques of the paper, "Emergent: a novel data-set for stance classification"
  

• 📫 You may reach me at [email protected]