Highlights

(For a full list see below or go to Google Scholar)

Understanding Types of Cyberbullying in an Anonymous Messaging Application

In this paper, we present a case study of the different types of bullying present in a recent online anonymous web/mobile application, Sarahah. Sarahah can be added to existing social networking sites/applications, thereby allowing the users' friends in the social network to send anonymous messages to the user. Since Sarahah data is private, we show how to collect this data using the Twitter social network. We categorize Sarahah messages into different topics using topic modeling and identify the bullying topics present in them. Our analysis is helpful in understanding the different types of bullying present in online interactions, especially in a setting where the sender is anonymous and is part of the recipient's social network.

Arpita Chakraborty, Yue Zhang, and Arti Ramesh

WWW Workshop on Cybersafety, 2018

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A Structured Approach to Understanding Recovery and Relapse in AA

In this paper, we introduce a structured approach to understanding recovery and relapse in Twitter users attending AA. We use a recently developed structured prediction framework to represent the structural relationship among these users, users and their friends, based on their Twitter exchanges and use that to reason about their recovery/relapse. Our model helps in modeling the different kinds of structural relationships and their corresponding contribution to predicting recovery/relapse. We also perform an extensive linguistic analysis to evaluate the contribution of the individual and combined contribution of the different features. Our experiments show that features derived from only structural relationships achieve a high prediction performance, emphasizing their importance in understanding recovery.

Yue Zhang, Arti Ramesh, Jennifer Golbeck, Dhanya Sridhar, and Lise Getoor

WWW, 2018

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Full List

Yue Zhang and Arti Ramesh
Learning Fairness-aware Relational Structures
European Conference on Artificial Intelligence (ECAI), 2020

Yue Zhang and Arti Ramesh
Struct-MMSB: Mixed Membership Stochastic Blockmodels with Interpretable Structured Priors
European Conference on Artificial Intelligence (ECAI), 2020

David DeFazio and Arti Ramesh
Adversarial Model Extraction of Graph Neural Networks
AAAI Workshop on Deep Learning on Graphs: Methodologies and Applications (DLGMA), 2020

Adita Kulkarni, Anand Seetharam, Arti Ramesh, Dinal Herath
DeepChannel - Wireless Channel Quality Prediction using Deep Learning
IEEE Transactions on Vehicular Technology, 2020

Adita Kulkarni, Anand Seetharam, and Arti Ramesh
DeepFit - Deep Learning based Fitness Center Equipment Use Modeling and Prediction
Mobiquitous, 2019

Gissella Bejarano, Adita Kulkarni, Raushan Raushan, Anand Seetharam, and Arti Ramesh ( equal contribution)
SWaP: Probabilistic Graphical and Deep Learning Models for Water Consumption Prediction
BuildSys, 2019

Yue Zhang and Arti Ramesh
Learning Interpretable Relational Structures of Hinge-loss Markov Random Fields
International Joint Conference on Artificial Intelligence (IJCAI), 2019

J. Dinal Herath, Anand Seetharam, and Arti Ramesh
A Deep Learning Model for Wireless Channel Quality Prediction
IEEE International Conference on Communications (ICC), 2019

Arti Ramesh, Dan Goldwasser, Bert Huang, Hal Daume III, and Lise Getoor
Interpretable Engagement Models for MOOCs using Hinge-loss Markov Random Fields
IEEE Transactions on Learning Technologies (TLT), 2019

Gissella Bejarano, David Defazio, and Arti Ramesh
Deep Latent Generative Models for Energy Disaggregation
AAAI Conference on Artificial Intelligence, 2019

David Defazio, Arti Ramesh, and Anand Seetharam
NYCER: A Non-Emergency Response Predictor for NYC using Sparse Gaussian Conditional Random Fields
International Conference on Mobile and Ubiquitous Systems (Mobiquitous), 2018

Yue Zhang and Arti Ramesh
Fine-grained Analysis of Cyberbullying using Weakly-Supervised Topic Models
Data Science and Advanced Analytics (DSAA), 2018

Arti Ramesh and Lise Getoor
Topic Evolution Models for Long-running MOOCs
Web Information Science and Engineering (WISE), 2018

Gissella Bejarano, Mayank Jain, Arti Ramesh, Anand Seetharam, and Aditya Mishra
Predictive Analytics for Smart Water Management in Developing Regions
SMARTCOMP, Smart Industries Workshop, 2018

Raphael Luciano de Pontes, Aditya Mishra, Anand Seetharam and Arti Ramesh
GreenPeaks: Employing Renewables to Effectively Cut Load in Electric Grids
SMARTCOMP, 2018

Arpita Chakraborty, Yue Zhang, and Arti Ramesh
Understanding Types of Cyberbullying in an Anonymous Messaging Application
WWW Workshop on Cybersafety, 2018

Yue Zhang, Arti Ramesh, Jennifer Golbeck, Dhanya Sridhar, and Lise Getoor
A Structured Approach to Understanding Recovery and Relapse in AA
WWW, 2018

Anand Seetharam and Arti Ramesh
On the Goodput of Flows in Heterogeneous Mobile Networks
Elsevier Computer Networks Journal, 2018

Arti Ramesh, Mario Rodriguez, and Lise Getoor
Multi-relational Influence Models for Online Professional Networks
Web Intelligence (WI), 2018

Sabina Tomkins, Arti Ramesh, and Lise Getoor
Predicting Post-Test Performance from Online Student Behavior: A High School MOOC Case Study
Educational Data Mining (EDM), 2016

Arti Ramesh, Mario Rodriguez, and Lise Getoor
Understanding Influence in Online Professional Networks
NIPS Workshop on Networks, 2015

Arti Ramesh, Shachi H. Kumar, James Foulds, and Lise Getoor
Weakly Supervised Models of Aspect-Sentiment for Online Course Discussion Forums
Annual meeting of Association of Computational Linguistics (ACL), 2015

Arti Ramesh, Dan Goldwasser, Bert Huang, Hal Daume III, Lise Getoor
Understanding Student Engagement using Latent Variable Methods
Learning with MOOCs: A Practitioner’s Workshop

Arti Ramesh, Dan Goldwasser, Bert Huang, Hal Daume III, and Lise Getoor
Learning Latent Engagement Patterns of Students in Online Courses
AAAI Conference on Artificial Intelligence (AAAI), 2014

Arti Ramesh, Dan Goldwasser, Bert Huang, Hal Daume III, and Lise Getoor
Understanding MOOC Discussion Forums using Seeded LDA
9th ACL Workshop on Innovative Use of NLP for Building Educational Applications (BEA), 2014

Arti Ramesh, Dan Goldwasser, Bert Huang, Hal Daume III, and Lise Getoor
Uncovering Hidden Engagement Patterns for Predicting Learner Performance in MOOCs
ACM Conference on Learning at Scale (L@S’14), 2014

Arti Ramesh, Dan Goldwasser, Bert Huang, Hal Daume III, and Lise Getoor
Modeling Learner Engagement in MOOCs using Probabilistic Soft Logic
NIPS Workshop on Data Driven Education (NIPS), 2013

Arti Ramesh, Jaebong Yoo, Lise Getoor and Jihie Kim
User Role Prediction in Online Discussion Forums using Probabilistic Soft Logic
NIPS Workshop on Personalizing Education with Machine Learning (NIPS), 2013