'Beating the news' with EMBERS: forecasting civil unrest using open source indicators. - Naren Ramakrishnan; Patrick Butler; Sathappan Muthiah; Nathan Self; Rupinder Paul Khandpur; Parang Saraf; Wei Wang 064; Jose Cadena; Anil Vullikanti; Gizem Korkmaz; Chris J. Kuhlman; Achla Marathe; et al. (KDD, 2014)

Detecting and forecasting domestic political crises: a graph-based approach. - Yaser Keneshloo; Jose Cadena; Gizem Korkmaz; Naren Ramakrishnan (WebSci, 2014)

Combining Heterogeneous Data Sources for Civil Unrest Forecasting. - Gizem Korkmaz; Jose Cadena; Chris J. Kuhlman; Achla Marathe; Anil Vullikanti; Naren Ramakrishnan (ASONAM, 2015)

An integrated agent-based approach for modeling disease spread in large populations to support health informatics. - Keith Bissett; Jose Cadena; Maleq Khan; Chris J. Kuhlman; Bryan L. Lewis; Pyrros A. Telionis (BHI, 2016)

On Dense Subgraphs in Signed Network Streams. - Jose Cadena; Anil Kumar S. Vullikanti; Charu C. Aggarwal (ICDM, 2016)

EMBERS at 4 years: Experiences operating an Open Source Indicators Forecasting System. - Sathappan Muthiah; Patrick Butler; Rupinder Paul Khandpur; Parang Saraf; Nathan Self; Alla Rozovskaya; Liang Zhao 002; Jose Cadena; Chang-Tien Lu; Anil Vullikanti; Achla Marathe; Kristen Maria Summers; et al. (KDD, 2016)

Multi-source models for civil unrest forecasting. - Gizem Korkmaz; Jose Cadena; Chris J. Kuhlman; Achla Marathe; Anil Vullikanti; Naren Ramakrishnan (Soc. Netw. Anal. Min., 2016)

Fast graph scan statistics optimization using algebraic fingerprints. - Jose Cadena; Saliya Ekanayake; Anil Vullikanti (IEEE BigData, 2017)

Near-Optimal and Practical Algorithms for Graph Scan Statistics. - Jose Cadena; Feng Chen 001; Anil Vullikanti (SDM, 2017)

Context-aided analysis of community evolution in networks. - Giuliana Pallotta; Goran Konjevod; Jose Cadena; Phan Nguyen (Stat. Anal. Data Min., 2017)

Graph Scan Statistics With Uncertainty. - Jose Cadena; Arinjoy Basak; Anil Vullikanti; Xinwei Deng (AAAI, 2018)

Mining Heavy Temporal Subgraphs: Fast Algorithms and Applications. - Jose Cadena; Anil Vullikanti (AAAI, 2018)

Graph Anomaly Detection Based on Steiner Connectivity and Density. - Jose Cadena; Feng Chen 001; Anil Vullikanti (Proc. IEEE, 2018)

Finding Interesting Subgraphs with Guarantees. - Jose Cadena (2018)

Collaborative Inference Of Missing Smart Electric Meter Data For A Building. - Nan Duan; Jose Cadena; Pedro Sotorrio; Jhi-Young Joo (MLSP, 2019)

MIDAS: Multilinear detection at scale. - Saliya Ekanayake; Jose Cadena; Udayanga Wickramasinghe; Anil Vullikanti (J. Parallel Distributed Comput., 2019)

Discovery of under immunized spatial clusters using network scan statistics. - Jose Cadena; David Falcone; Achla Marathe; Anil Vullikanti (BMC Medical Informatics Decis. Mak., 2019)

Near-Optimal and Practical Algorithms for Graph Scan Statistics with Connectivity Constraints. - Jose Cadena; Feng Chen 001; Anil Vullikanti (ACM Trans. Knowl. Discov. Data, 2019)

Finding Spatial Clusters Susceptible to Epidemic Outbreaks due to Undervaccination. - Jose Cadena; Achla Marathe; Anil Vullikanti (AAMAS, 2020)

Critical Spatial Clusters for Vaccine Preventable Diseases. - Jose Cadena; Achla Marathe; Anil Vullikanti (SBP-BRiMS, 2020)

Modeling the temporal network dynamics of neuronal cultures. - Jose Cadena; Ana Paula Sales; Doris Lam; Heather A. Enright; Elizabeth K. Wheeler; Nicholas O. Fischer (PLoS Comput. Biol., 2020)

Decentralized Black-Box Variational Inference for Bayesian Learning on Sensor Networks. - Jose Cadena; Priyadip Ray; Ryan A. Goldhahn (ACSCC, 2021)

End-to-End Framework for Imputation and State Discovery in Longitudinal Energy Data. - Alexander Ladd; Kwan Ho Ryan Chan; Sam Nguyen; Jose Cadena; Brenda Ng (e-Energy, 2021)

Stochastic Gradient-Based Distributed Bayesian Estimation in Cooperative Sensor Networks. - Jose Cadena; Priyadip Ray; Hao Chen 001; Braden Soper; Deepak Rajan; Anton Yen; Ryan A. Goldhahn (IEEE Trans. Signal Process., 2021)

Bayesian Multiagent Active Sensing and Localization via Decentralized Posterior Sampling. - Braden C. Soper; Priyadip Ray; Jose Cadena; Hao Chen 001; Ryan A. Goldhahn (IEEECONF, 2022)

Dynamic modeling of hospitalized COVID-19 patients reveals disease state-dependent risk factors. - Braden C. Soper; Jose Cadena; Sam Nguyen; Kwan Ho Ryan Chan; Paul Kiszka; Lucas Aaron Womack; Mark Work; Joan M. Duggan; Steven T. Haller; Jennifer A. Hanrahan; David J. Kennedy; Deepa Mukundan; et al. (J. Am. Medical Informatics Assoc., 2022)

Scientific Computing Algorithms to Learn Enhanced Scalable Surrogates for Mesh Physics. - Brian R. Bartoldson; Yeping Hu; Amar Saini; Jose Cadena; Yucheng Fu; Jie Bao; Zhijie Xu; Brenda Ng; Phan Nguyen (CoRR, 2023)

Comparative study of machine learning techniques for post-combustion carbon capture systems. - Yeping Hu; Bo Lei; Yash Girish Shah; Jose Cadena; Amar Saini; Grigorios Panagakos; Phan Nguyen (Frontiers Artif. Intell., 2024)

Accelerating computational fluid dynamics simulation of post-combustion carbon capture modeling with MeshGraphNets. - Bo Lei; Yucheng Fu; Jose Cadena; Amar Saini; Yeping Hu; Jie Bao; Zhijie Xu; Brenda Ng; Phan Nguyen (Frontiers Artif. Intell., 2024)

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics. - Haonan Zhu; Mary Silva; Jose Cadena; Braden Soper; Michal Lisicki; Braian Peetoom; Sergio E. Baranzini; Shivshankar Sundaram; Priyadip Ray; Jeff Drocco (CoRR, 2025)