| 2026 | LAK | Understanding and Modeling Math Strategy Use in Intelligent Tutoring Systems. | Abisha Thapa Magar, Asad Uzzaman, Tali Zacks, Stephen Fancsali, Vasile Rus, April Murphy, Ethan Shafran Moltz, Steve Ritter, Deepak Venugopal |
| 2025 | AIED | Analyzing Strategies in MATHia with BERT. | Abisha Thapa Magar, Stephen E. Fancsali, Vasile Rus, April Murphy, Steven Ritter, Deepak Venugopal |
| 2025 | LAK | "Can A Language Model Represent Math Strategies?": Learning Math Strategies from Big Data using BERT. | Abisha Thapa Magar, Anup Shakya, Stephen E. Fancsali, Vasile Rus, April Murphy, Steven Ritter, Deepak Venugopal |
| 2025 | UAI | Reparameterizing Hybrid Markov Logic Networks to handle Covariate-Shift in Representations. | Anup Shakya, Abisha Thapa Magar, Somdeb Sarkhel, Deepak Venugopal |
| 2023 | EDM | Scalable and Equitable Math Problem Solving Strategy Prediction in Big Educational Data. | Anup Shakya, Vasile Rus, Deepak Venugopal |
| 2023 | ICDM | On the Verification of Embeddings with Hybrid Markov Logic. | Anup Shakya, Abisha Thapa Magar, Somdeb Sarkhel, Deepak Venugopal |
| 2022 | LREC | Question Modifiers in Visual Question Answering. | William Britton, Somdeb Sarkhel, Deepak Venugopal |
| 2021 | EDM | The Nature of Achievement Goal Motivation Profiles: Exploring Situational Motivation in An Algebra-Focused Intelligent Tutoring System. | Leigh M. Harrell-Williams, Christian Mueller, Stephen Fancsali, Steven Ritter, Xiaofei Zhang, Deepak Venugopal |
| 2021 | EDM | The Learner Data Institute - Conceptualization: A Progress Report. | Vasile Rus, Stephen E. Fancsali, Philip I. Pavlik Jr., Deepak Venugopal, Arthur C. Graesser, Steven Ritter, Dale Bowman, The LDI Team |
| 2021 | EDM | Student Strategy Prediction using a Neuro-Symbolic Approach. | Anup Shakya, Vasile Rus, Deepak Venugopal |
| 2021 | EDM | Neuro-Symbolic Models: A Scalable, Explainable Framework for Strategy Discovery from Big Edu-Data. | Deepak Venugopal, Vasile Rus, Anup Shakya |
| 2020 | IJCNN | CIDMP: Completely Interpretable Detection of Malaria Parasite in Red Blood Cells using Lower-dimensional Feature Space. | Anik Khan, Kishor Datta Gupta, Deepak Venugopal, Nirman Kumar |
| 2019 | AAAI | On Lifted Inference Using Neural Embeddings. | Mohammad Maminur Islam, Somdeb Sarkhel, Deepak Venugopal |
| 2019 | AISTATS | Adaptive Rao-Blackwellisation in Gibbs Sampling for Probabilistic Graphical Models. | Craig Kelly, Somdeb Sarkhel, Deepak Venugopal |
| 2019 | QRS | DDoS Intrusion Detection Through Machine Learning Ensemble. | Saikat Das, Ahmed M. Mahfouz, Deepak Venugopal, Sajjan G. Shiva |
| 2018 | AAAI | Learning Mixtures of MLNs. | Mohammad Maminur Islam, Somdeb Sarkhel, Deepak Venugopal |
| 2018 | AISTATS | Efficient Weight Learning in High-Dimensional Untied MLNs. | Khan Mohammad Al Farabi, Somdeb Sarkhel, Deepak Venugopal |
| 2017 | IJCAI | Efficient Inference for Untied MLNs. | Somdeb Sarkhel, Deepak Venugopal, Nicholas Ruozzi, Vibhav Gogate |
| 2017 | IJCNN | Adaptive blocked Gibbs sampling for inference in probabilistic graphical models. | Mohammad Maminur Islam, Mohammad Khan Al Farabi, Deepak Venugopal |
| 2016 | AAAI | Scalable Training of Markov Logic Networks Using Approximate Counting. | Somdeb Sarkhel, Deepak Venugopal, Tuan Anh Pham, Parag Singla, Vibhav Gogate |
| 2016 | COLING | Joint Inference for Event Coreference Resolution. | Jing Lu, Deepak Venugopal, Vibhav Gogate, Vincent Ng |
| 2016 | COLING | Joint Inference for Mode Identification in Tutorial Dialogues. | Deepak Venugopal, Vasile Rus |
| 2016 | UAI | Non-parametric Domain Approximation for Scalable Gibbs Sampling in MLNs. | Deepak Venugopal, Somdeb Sarkhel, Kyle Cherry |
| 2015 | AAAI | Scaling-Up Inference in Markov Logic. | Deepak Venugopal |
| 2015 | AAAI | Just Count the Satisfied Groundings: Scalable Local-Search and Sampling Based Inference in MLNs. | Deepak Venugopal, Somdeb Sarkhel, Vibhav Gogate |
| 2014 | AAAI | Evidence-Based Clustering for Scalable Inference in Markov Logic. | Deepak Venugopal, Vibhav Gogate |
| 2014 | AISTATS | Lifted MAP Inference for Markov Logic Networks. | Somdeb Sarkhel, Deepak Venugopal, Parag Singla, Vibhav Gogate |
| 2014 | EMNLP | Relieving the Computational Bottleneck: Joint Inference for Event Extraction with High-Dimensional Features. | Deepak Venugopal, Chen Chen, Vibhav Gogate, Vincent Ng |
| 2013 | AAAI | GiSS: Combining Gibbs Sampling and SampleSearch for Inference in Mixed Probabilistic and Deterministic Graphical Models. | Deepak Venugopal, Vibhav Gogate |
| 2013 | UAI | Dynamic Blocking and Collapsing for Gibbs Sampling. | Deepak Venugopal, Vibhav Gogate |
| 2012 | AAAI | Advances in Lifted Importance Sampling. | Vibhav Gogate, Abhay Kumar Jha, Deepak Venugopal |
| 2007 | IPCCC | A Malware Signature Extraction and Detection Method Applied to Mobile Networks. | Guoning Hu, Deepak Venugopal |
| 2006 | PST | Intelligent virus detection on mobile devices. | Deepak Venugopal, Guoning Hu, Nicoleta Roman |