Asmit Nayak

Asmit Nayak

Computer Science PhD Student at UW-Madison

Posts by Collection

projects

Hack 500

Written in: PHP, JavaScript, CSS
Designed a website for a hackathon as a course project

Two-Layered Neural Network

Written in: Python
A from scratch Neural Network to classify and predict the labels for the MNIST dataset
Github Repo: Two Layered Neural Network

Hierarchical Clustering Algorithm

Written in: Python
Engineered from scratch a clustering algorithm to cluster countries based on their COVID-19 death rate
Github Repo: Hierarchical Clustering Algorithm

Convolution Neural Network

Written in: Python
Created a Neural Network using Tensorflow Keras to classify animal images (cats vs dogs)
Github Repo: Convolution Neural Network

Markhov Model based Sentence generator

Written in: Python
A sentence generator that uses Markhov model to learn from a movie script and then create a sentence given a starting word
Github Repo: Markhov Model based Sentence generator

Decision Tree

Written in: Python
A decision tree model that predicts the likelihood of cancer give certain diagnostics for a patient.
Github Repo: Decision Tree
Database used: Wisconsin Breast Cancer

2048

Written in: Python
A Neural Network utilizing Genetic Algorithm to play the game of 2048

publications

Surfacing Privacy Settings using Semantic Matching

Published in Proceedings of the Second Workshop on Privacy in NLP, 2020

Online services utilize privacy settings to provide users with control over their data. However, these privacy settings are often hard to locate, causing the user to rely on provider-chosen default values. In this work, we train privacy settings centric encoders and leverage them to create an interface that allows users to search for privacy settings using free-form queries.

Recommended citation: Rishabh Khandelwal, Asmit Nayak*, Yao Yao*, Kassem Fawaz. (2020). "Surfacing Privacy Settings Using Semantic Matching" Proceedings of the Second Workshop on Privacy in NLP. https://www.aclweb.org/anthology/2020.privatenlp-1.4.pdf

talks

teaching