paper-conference

Traffic Anomaly Detection Via Conditional Normalizing Flow
Traffic congestion anomaly detection is of paramount importance in intelligent traffic systems. The goals of transportation agencies …
Zhuangwei Kang, Ayan Mukhopadhyay, Aniruddha Gokhale, Shijie Wen, Abhishek Dubey
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Deep-RBF Networks for Anomaly Detection in Automotive Cyber-Physical Systems
Deep Neural Networks (DNNs) are popularly used for implementing autonomy related tasks in automotive Cyber-Physical Systems (CPSs). …
Matthew Burruss, Shreyas Ramakrishna, Abhishek Dubey
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Efficient Data Management for Intelligent Urban Mobility Systems
Modern intelligent urban mobility applications are underpinned by large-scale, multivariate, spatiotemporal data streams. Working with …
Michael Wilbur, Philip Pugliese, Aron Laszka, Abhishek Dubey
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Energy and Emission Prediction for Mixed-Vehicle Transit Fleets Using Multi-Task and Inductive Transfer Learning
Public transit agencies are focused on making their fixed-line bus systems more energy efficient by introducing electric (EV) and …
Michael Wilbur, Ayan Mukhopadhyay, Sayyed Vazirizade, Philip Pugliese, Aron Laszka, Abhishek Dubey
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Hierarchical Planning for Resource Allocation in Emergency Response Systems
A classical problem in city-scale cyber-physical systems (CPS) is resource allocation under uncertainty. Spatial-temporal allocation of …
Geoffrey Pettet, Ayan Mukhopadhyay, Mykel Kochenderfer, Abhishek Dubey
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Learning Incident Prediction Models Over Large Geographical Areas for Emergency Response Systems
Principled decision making in emergency response management necessitates the use of statistical models that predict the …
Sayyed Mohsen Vazirizade, Ayan Mukhopadhyay, Geoffrey Pettet, Said El Said, Hiba Baroud, Abhishek Dubey
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Minimizing Energy Use of Mixed-Fleet Public Transit for Fixed-Route Service
Affordable public transit services are crucial for communities since they enable residents to access employment, education, and other …
Amutheezan Sivagnanam, Afiya Ayman, Michael Wilbur, Philip Pugliese, Abhishek Dubey, Aron Laszka
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Poster Abstract: Configuration Tuning for Distributed IoT Message Systems Using Deep Reinforcement Learning
Distributed messaging systems (DMSs) are often equipped with a large number of configurable parameters that enable users to define …
Zhuangwei Kang, Yogesh D. Barve, Shunxing Bao, Abhishek Dubey, Aniruddha Gokhale
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Power-Attack: A comprehensive tool-chain for modeling and simulating attacks in power systems
Due to the increased deployment of novel communication, control and protection functions, the grid has become vulnerable to a variety …
Ajay Chhokra, Carlos Barreto, Abhishek Dubey, Gabor Karsai, Xenofon Koutsoukos
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Practitioner-Centric Approach for Early Incident Detection Using Crowdsourced Data for Emergency Services
Emergency response is highly dependent on the time of incident reporting. Unfortunately, the traditional approach to receiving incident …
Yasas Senarath, Ayan Mukhopadhyay, Sayyed Vazirizade, Hemant Purohit, Saideep Nannapaneni, Abhishek Dubey
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