Arti Ramesh

Orcid: 0000-0001-8840-8163

Affiliations:
  • Binghamton University, NY, USA


According to our database1, Arti Ramesh authored at least 41 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

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Bibliography

2024
Multimodal, Multi-Class Bias Mitigation for Predicting Speaker Confidence.
Proceedings of the 17th International Conference on Educational Data Mining, 2024

2021
A Structured and Linguistic Approach to Understanding Recovery and Relapse in AA.
ACM Trans. Web, 2021

SWIFT: A non-emergency response prediction system using sparse Gaussian Conditional Random Fields.
Pervasive Mob. Comput., 2021

Understanding the Societal Disruption due to COVID-19 via User Tweets.
Proceedings of the IEEE International Conference on Smart Computing, 2021

Poster: Understanding Human Mobility during COVID-19 using Cellular Network Traffic.
Proceedings of the IFIP Networking Conference, 2021

Poster: COVID-19 Case Prediction using Cellular Network Traffic.
Proceedings of the IFIP Networking Conference, 2021

Hierarchical Models for Detecting Mobility Clusters during COVID-19.
Proceedings of the MobiWac '21: Proceedings of the 19th ACM International Symposium on Mobility Management and Wireless Access, Alicante, Spain, November 22, 2021

Characterizing Human Mobility Patterns During COVID-19 using Cellular Network Data.
Proceedings of the 46th IEEE Conference on Local Computer Networks, 2021

Mobility-aware COVID-19 Case Prediction using Cellular Network Logs.
Proceedings of the 46th IEEE Conference on Local Computer Networks, 2021

Understanding the Issues Surrounding COVID-19 Vaccine Roll Out via User Tweets.
Proceedings of the Computational Data and Social Networks - 10th International Conference, 2021

Wireless Channel Quality Prediction using Sparse Gaussian Conditional Random Fields.
Proceedings of the 18th IEEE Annual Consumer Communications & Networking Conference, 2021

RelEx: A Model-Agnostic Relational Model Explainer.
Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

Analyzing Aggregate User Behavior on a Large Multi-platform Content Distribution Service.
Proceedings of the Ad Hoc Networks and Tools for IT - 13th EAI International Conference, 2021

2020
DeepChannel: Wireless Channel Quality Prediction Using Deep Learning.
IEEE Trans. Veh. Technol., 2020

Interpretable Engagement Models for MOOCs Using Hinge-Loss Markov Random Fields.
IEEE Trans. Learn. Technol., 2020

Understanding the Socio-Economic Disruption in the United States during COVID-19's Early Days.
CoRR, 2020

DeepER: A Deep Learning based Emergency Resolution Time Prediction System.
Proceedings of the 2020 International Conferences on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, 2020

Analyzing Societal Impact of COVID-19: A Study During the Early Days of the Pandemic.
Proceedings of the IEEE International Conference on Parallel & Distributed Processing with Applications, 2020

Learning Fairness-Aware Relational Structures.
Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

Struct-MMSB: Mixed Membership Stochastic Blockmodels with Interpretable Structured Priors.
Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

2019
Adversarial Model Extraction on Graph Neural Networks.
CoRR, 2019

SWaP: Probabilistic Graphical and Deep Learning Models for Water Consumption Prediction.
Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, 2019

DeepFit: deep learning based fitness center equipment use modeling and prediction.
Proceedings of the MobiQuitous 2019, 2019

Learning Interpretable Relational Structures of Hinge-loss Markov Random Fields.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

A Deep Learning Model for Wireless Channel Quality Prediction.
Proceedings of the 2019 IEEE International Conference on Communications, 2019

Deep Latent Generative Models for Energy Disaggregation.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
On the goodput of flows in heterogeneous mobile networks.
Comput. Networks, 2018

A Structured Approach to Understanding Recovery and Relapse in AA.
Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

Understanding Types of Cyberbullying in an Anonymous Messaging Application.
Proceedings of the Companion of the The Web Conference 2018 on The Web Conference 2018, 2018

Topic Evolution Models for Long-Running MOOCs.
Proceedings of the Web Information Systems Engineering - WISE 2018, 2018

GreenPeaks: Employing Renewables to Effectively Cut Load in Electric Grids.
Proceedings of the 2018 IEEE International Conference on Smart Computing, 2018

Predictive Analytics for Smart Water Management in Developing Regions.
Proceedings of the 2018 IEEE International Conference on Smart Computing, 2018

NYCER: A Non-Emergency Response Predictor for NYC using Sparse Gaussian Conditional Random Fields.
Proceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, 2018

Fine-Grained Analysis of Cyberbullying Using Weakly-Supervised Topic Models.
Proceedings of the 5th IEEE International Conference on Data Science and Advanced Analytics, 2018

2017
Multi-relational influence models for online professional networks.
Proceedings of the International Conference on Web Intelligence, 2017

2016
A Probabilistic Approach to Modeling Socio-Behavioral Interactions.
PhD thesis, 2016

Predicting Post-Test Performance from Student Behavior: A High School MOOC Case Study.
Proceedings of the 9th International Conference on Educational Data Mining, 2016

2015
Weakly Supervised Models of Aspect-Sentiment for Online Course Discussion Forums.
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, 2015

2014
Uncovering hidden engagement patterns for predicting learner performance in MOOCs.
Proceedings of the First (2014) ACM Conference on Learning @ Scale, 2014

Understanding MOOC Discussion Forums using Seeded LDA.
Proceedings of the Ninth Workshop on Innovative Use of NLP for Building Educational Applications, 2014

Learning Latent Engagement Patterns of Students in Online Courses.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014


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