| Modeling learner engagement in MOOCs using probabilistic soft logic A Ramesh, D Goldwasser, B Huang, H Daumé III, L Getoor NIPS workshop on data driven education 21, 62, 2013 | 211 | 2013 |
| Learning latent engagement patterns of students in online courses A Ramesh, D Goldwasser, B Huang, H Daume III, L Getoor Proceedings of the AAAI Conference on Artificial Intelligence 28 (1), 2014 | 168 | 2014 |
| Understanding MOOC Discussion Forums using Seeded LDA A Ramesh, D Goldwasser, B Huang, H Daume III, L Getoor ACL Workshop on Innovative Use of NLP for Building Educational Applications, 2014 | 130 | 2014 |
| Relex: A model-agnostic relational model explainer Y Zhang, D Defazio, A Ramesh Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 1042 …, 2021 | 111 | 2021 |
| Deepchannel: Wireless channel quality prediction using deep learning A Kulkarni, A Seetharam, A Ramesh, JD Herath IEEE Transactions on Vehicular Technology 69 (1), 443-456, 2019 | 90 | 2019 |
| Weakly supervised models of aspect-sentiment for online course discussion forums A Ramesh, SH Kumar, J Foulds, L Getoor Proceedings of the 53rd Annual Meeting of the Association for Computational …, 2015 | 88 | 2015 |
| Uncovering hidden engagement patterns for predicting learner performance in MOOCs A Ramesh, D Goldwasser, B Huang, H Daume III, L Getoor Proceedings of the first ACM conference on Learning@ scale conference, 157-158, 2014 | 61 | 2014 |
| Predicting Post-Test Performance from Online Student Behavior: A High School MOOC Case Study S Tomkins, A Ramesh, L Getoor 9th International Conference on Educational Data Mining, 2016 | 45 | 2016 |
| Deep latent generative models for energy disaggregation G Bejarano, D DeFazio, A Ramesh Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 850-857, 2019 | 38 | 2019 |
| A deep learning model for wireless channel quality prediction JD Herath, A Seetharam, A Ramesh ICC 2019-2019 IEEE International Conference on Communications (ICC), 1-6, 2019 | 35 | 2019 |
| Adversarial model extraction on graph neural networks D DeFazio, A Ramesh arXiv preprint arXiv:1912.07721, 2019 | 21 | 2019 |
| Interpretable engagement models for MOOCs using Hinge-loss markov random fields A Ramesh, D Goldwasser, B Huang, H Daume, L Getoor IEEE Transactions on Learning Technologies 13 (1), 107-122, 2018 | 18 | 2018 |
| Understanding the socio-economic disruption in the United States during COVID-19's early days SG Shanthakumar, A Seetharam, A Ramesh arXiv preprint arXiv:2004.05451, 2020 | 17 | 2020 |
| Predictive analytics for smart water management in developing regions G Bejarano, M Jain, A Ramesh, A Seetharam, A Mishra 2018 IEEE International Conference on Smart Computing (SMARTCOMP), 464-469, 2018 | 16 | 2018 |
| A structured approach to understanding recovery and relapse in AA Y Zhang, A Ramesh, J Golbeck, D Sridhar, L Getoor Proceedings of the 2018 World Wide Web Conference, 1205-1214, 2018 | 15 | 2018 |
| Multi-relational influence models for online professional networks A Ramesh, M Rodriguez, L Getoor Proceedings of the International Conference on Web Intelligence, 291-298, 2017 | 14 | 2017 |
| Learning fairness-aware relational structures Y Zhang, A Ramesh ECAI 2020, 2543-2550, 2020 | 13 | 2020 |
| Fine-grained analysis of cyberbullying using weakly-supervised topic models Y Zhang, A Ramesh 2018 IEEE 5th International Conference on Data Science and Advanced …, 2018 | 13 | 2018 |
| Swap: Probabilistic graphical and deep learning models for water consumption prediction G Bejarano, A Kulkarni, R Raushan, A Seetharam, A Ramesh Proceedings of the 6th ACM International Conference on Systems for Energy …, 2019 | 12 | 2019 |
| Understanding types of cyberbullying in an anonymous messaging application A Chakraborty, Y Zhang, A Ramesh Companion Proceedings of the The Web Conference 2018, 1001-1005, 2018 | 11 | 2018 |
Anand SeetharamSenior Data Scientist, Cognitive SpaceVerified email at cognitivespace.com
