Research Projects

We introduce a novel safe route planning problem and develop an efficient solution to ensure the travelers' safety on roads. Our approach finds the safest routes within a user-specified distance threshold based on the personalized travel experience of the knowledgeable crowd without involving any centralized computation. Our algorithms for finding the safest route further enhance user privacy by minimizing the exposure of personalized safety scores with others. Our safe route planner can find the safest routes for individuals and groups by considering both a fixed and a set of flexible destination locations.

The popularity of e-commerce has caused the rise of crowdsourced package delivery. In this research, we introduce an efficient approach to find the package delivery route based on the available journey plans of passengers in public transport networks. Our approach allows package transfers between the public transport passengers and thereby increase the success rate of the crowdsourced package delivery.

This work introduces a representative dissimilar path (RDP) query and provides an efficient algorithm for finding a set of most dissimilar routes from sets of representative routes for different features.

In this project, we annotate a target genome using a closely related, well-annotated reference genome using ensemble of RATT, Glimmer and BLAST.

In this project, we detect credit card frauds using Siamese network.