Software engineering lead for ROAMM, a customizable framework for real time online assessment and mobility monitoring. Supports real time…
Unsupervised Summarization and Descriptive Modelling of City Traffic Data: Developed machine learning algorithms focused on modelling spatio…
The arrival (or departure) information of each vehicle on a detector can be thought of as a time series waveform . Given the high…
Our deep learning approach (called InterTwin as a short form for Intersection Twin) uses a large amount of data from different intersection…
Coordination involves synchronizing multiple intersections to enhance the operation of directional movements in a system. Typically, the…
The focus of our work is on using data just from loop detectors placed at intersections, for estimating queue lengths. Such loop detector…
Turn movement counts (TMCs) are used for a wide variety of applications related to intersection analyses, intersection design, and transport…
Implemented a ensemble gradient boosting regression model to predict movie revenue given its meta data. Also did exploratory analysis of the…
Implemented a scalable system to find the popular keywords that appear on a search engine, used max fibonacci heap, hash maps for efficient…
Implemented Gossip and Push-Sum algorithms through a simulator based on actors written in Elixir. The goal is to determine convergence in…
Developed a deep learning stack for genre classification using MFCC features of the audio. Designed an architecture with inception…
Designed an implemented a distributed system to simulate twitter with functionalities - add/remove user, broadcast/subscribe a tweet, search…
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Our goal in this paper is to use large scale loop detector data for detecting traffic interruptions. With the advent of new systems, loop…
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Our goal in this paper is to find the best mapping of detectors to phases and to classify detectors as stop bar detectors or advance…
Pervasive computing is changing the monitoring landscape for patients to communicate their healthcare information in real-time to clinicians…
We describe a system that leverages machine learning methodologies for data collected from a large number of intersections to derive key…
This work presents a novel framework that combines processing of high resolution controller log data pertaining to certain performance…
Our goal in this paper is to use loop detector data for detecting traffic interruptions. Loop detector data are now widely available to…