What's Most Broken? A Tool to Assist Data-Driven Iterative Improvement of an Intelligent Tutoring System. - Mononito Goswami; Shiven Mian; Jack Mostow (AAAI, 2019)

What's Most Broken? Design and Evaluation of a Tool to Guide Improvement of an Intelligent Tutor. - Shiven Mian; Mononito Goswami; Jack Mostow (AIED (1), 2019)

Are You Paying Attention? Detecting Distracted Driving in Real-Time. - Maitree Leekha; Mononito Goswami; Rajiv Ratn Shah; Yifang Yin; Roger Zimmermann (BigMM, 2019)

Detecting Patterns of Physiological Response to Hemodynamic Stress via Unsupervised Deep Learning. - Chufan Gao; Fabian Falck; Mononito Goswami; Anthony Wertz; Michael R. Pinsky; Artur Dubrawski (CoRR, 2019)

Discriminating Cognitive Disequilibrium and Flow in Problem Solving: A Semi-Supervised Approach Using Involuntary Dynamic Behavioral Signals. - Mononito Goswami; Lujie Chen; Artur Dubrawski (AAAI, 2020)

Modeling Involuntary Dynamic Behaviors to Support Intelligent Tutoring (Student Abstract). - Mononito Goswami; Lujie Chen; Chufan Gao; Artur Dubrawski (AAAI, 2020)

A Multi-Task Approach to Open Domain Suggestion Mining (Student Abstract). - Minni Jain; Maitree Leekha; Mononito Goswami (AAAI, 2020)

What Makes a Better Companion? Towards Social & Engaging Peer Learning. - Rajni Jindal; Maitree Leekha; Minkush Manuja; Mononito Goswami (ECAI, 2020)

A Multi-task Approach to Open Domain Suggestion Mining Using Language Model for Text Over-Sampling. - Maitree Leekha; Mononito Goswami; Minni Jain (ECIR (2), 2020)

Toward Learning at Scale in Developing Countries: Lessons from the Global Learning XPRIZE Field Study. - Andrew A. McReynolds; Sheba P. Naderzad; Mononito Goswami; Jack Mostow (L@S, 2020)

Towards Social & Engaging Peer Learning: Predicting Backchanneling and Disengagement in Children. - Mononito Goswami; Minkush Manuja; Maitree Leekha (CoRR, 2020)

Detecting intrusive transactions in databases using partially-ordered sequential rule mining and fractional-distance based anomaly detection. - Indu Singh; Minkush Manuja; Rishabh Mathur; Mononito Goswami (Int. J. Intell. Eng. Informatics, 2020)

A Binary PSO Approach for Improving the Performance of Wireless Sensor Networks. - Ajay Kaushik; Mononito Goswami; Minkush Manuja; S. Indu 001; Daya Gupta (Wirel. Pers. Commun., 2020)

Weak Supervision for Affordable Modeling of Electrocardiogram Data. - Mononito Goswami; Benedikt Boecking; Artur Dubrawski (AMIA, 2021)

The Word is Mightier than the Label: Learning without Pointillistic Labels using Data Programming. - Chufan Gao; Mononito Goswami (CoRR, 2021)

Learning Graph Neural Networks for Multivariate Time Series Anomaly Detection. - Saswati Ray; Sana Lakdawala; Mononito Goswami; Chufan Gao (CoRR, 2021)

Weakly Supervised Classification of Vital Sign Alerts as Real or Artifact. - Arnab Dey; Mononito Goswami; Joo Heung Yoon; Gilles Clermont; Michael R. Pinsky; Marilyn Hravnak; Artur Dubrawski (AMIA, 2022)

Counterfactual Phenotyping with Censored Time-to-Events. - Chirag Nagpal; Mononito Goswami; Keith Dufendach; Artur Dubrawski (KDD, 2022)

Classifying Unstructured Clinical Notes via Automatic Weak Supervision. - Chufan Gao; Mononito Goswami; Jieshi Chen; Artur Dubrawski (MLHC, 2022)

Unsupervised Model Selection for Time Series Anomaly Detection. - Mononito Goswami; Cristian I. Challu; Laurent Callot; Lenon Minorics; Andrey Kan (ICLR, 2023)

AQuA: A Benchmarking Tool for Label Quality Assessment. - Mononito Goswami; Vedant Sanil; Arjun Choudhry; Arvind Srinivasan 002; Chalisa Udompanyawit; Artur Dubrawski (NeurIPS, 2023)

JoLT: Jointly Learned Representations of Language and Time-Series for Clinical Time-Series Interpretation (Student Abstract). - Yifu Cai; Arvind Srinivasan 002; Mononito Goswami; Arjun Choudhry; Artur Dubrawski (AAAI, 2024)

PICSR: Prototype-Informed Cross-Silo Router for Federated Learning (Student Abstract). - Eric Enouen; Sebastian Caldas; Mononito Goswami; Artur Dubrawski (AAAI, 2024)

MOMENT: A Family of Open Time-series Foundation Models. - Mononito Goswami; Konrad Szafer; Arjun Choudhry; Yifu Cai; Shuo Li; Artur Dubrawski (ICML, 2024)

Implicit Reasoning in Deep Time Series Forecasting. - Willa Potosnak; Cristian Challu; Mononito Goswami; Michal Wilinski; Nina Zukowska; Artur Dubrawski (CoRR, 2024)

Unveiling and Manipulating Concepts in Time Series Foundation Models. - Michal Wilinski; Mononito Goswami; Nina Zukowska; Willa Potosnak; Artur Dubrawski (CoRR, 2024)

Towards Long-Context Time Series Foundation Models. - Nina Zukowska; Mononito Goswami; Michal Wilinski; Willa Potosnak; Artur Dubrawski (CoRR, 2024)

TimeSeriesExam: A time series understanding exam. - Yifu Cai; Arjun Choudhry; Mononito Goswami; Artur Dubrawski (CoRR, 2024)

Investigating Compositional Reasoning in Time Series Foundation Models. - Willa Potosnak; Cristian Challu; Mononito Goswami; Kin G. Olivares; Michal Wilinski; Nina Zukowska; Artur Dubrawski (CoRR, 2025)

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents. - Yifu Cai; Xinyu Li; Mononito Goswami; Michal Wilinski; Gus Welter; Artur Dubrawski (CoRR, 2025)