Anand Rangarajan

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Professor

University of Florida

United States

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About

Professor Anand Rangarajan is a faculty member at the University of Florida in the United States. His research areas encompass data compression, traffic simulation, remote sensing, and machine learning, as evidenced by his recent publications. His work includes developing unified frameworks for scientific data compression and enhancing traffic intersection safety through video analytics. Professor Rangarajan is committed to advancing knowledge in the fields of computational science and engineering.

Recent Grants

Grant: Close

Research on Artificial-Intelligence for Data Integration with State Highways

Open Date: 2022-06-15

Close Date: 2024-03-20

Grant: Close

Hybrid learning techniques for scientific data reduction with performance guarantees

Open Date: 2021-09-01

Close Date: 2024-08-31

Grant: Close

Video Analytics Systems Testing

Open Date: 2021-02-21

Close Date: 2023-03-31

Grant: Close

CAMPUS EXECUTIVE LDRD Domain Informed Artificial Intelligence/Machine Learning

Open Date: 2020-10-01

Close Date: 2021-09-30

Grant: Close

RAPIDS2: A SciDAC Institute for Computer Science, Data, and Artificial Intelligence

Open Date: 2020-09-23

Close Date: 2023-09-22

Articles (16)

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2025

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2023

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2023

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2022

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2022

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2022

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2022

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2022

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2021

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2021

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2020

Collaborators (3)

Pan He

Assistant Professor

Auburn University

UNITED STATES

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Tania Banerjee

University of Florida

UNITED STATES

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Sanjay Ranka

University of Florida

UNITED STATES

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Anand Rangarajan

Research Interests

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About

Recent Grants

Articles (16)

CAESAR: A Unified Framework for Foundation and Generative Models for Efficient Compression of Scientific Data

Graph Attention Network for Lane-Wise and Topology-Invariant Intersection Traffic Simulation

Toward Improving the Generation Quality of Autoregressive Slot VAEs

An Efficient Semi-Automated Scheme for Infrastructure LiDAR Annotation

Computing Arterial Travel Time Distributions From Loop Detector and Probe Datasets

Learning Canonical Embeddings for Unsupervised Shape Correspondence With Locally Linear Transformations

In-season crop phenology using remote sensing and model-guided machine learning

MGARD: A multigrid framework for high-performance, error-controlled data compression and refactoring

Using Video Analytics to Improve Traffic Intersection Safety and Performance

Error-Bounded Learned Scientific Data Compression with Preservation of Derived Quantities

Machine-Learning-Based Real-Time Multi-Camera Vehicle Tracking and Travel-Time Estimation

Subcycle Waveform Modeling of Traffic Intersections Using Recurrent Attention Networks

Machine Learning-Based Highway Truck Commodity Classification Using Logo Data

Truck and Trailer Classification With Deep Learning Based Geometric Features

Domain-Guided Machine Learning for Remotely Sensed In-Season Crop Growth Estimation

An Integrated Approach to Registration and Fusion of Hyperspectral and Multispectral Images

Collaborators (3)

Pan He

Tania Banerjee

Sanjay Ranka

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