Combining Search, Social Media, and Traditional Data Sources to Improve Influenza Surveillance. - Mauricio Santillana; André T. Nguyen; Mark Dredze; Michael J. Paul; Elaine O. Nsoesie; John S. Brownstein (PLoS Comput. Biol., 2015)

Adversarial Attacks, Regression, and Numerical Stability Regularization. - André T. Nguyen; Edward Raff (CoRR, 2018)

Would a File by Any Other Name Seem as Malicious? - André T. Nguyen; Edward Raff; Aaron Sant-Miller (IEEE BigData, 2019)

Connecting Lyapunov Control Theory to Adversarial Attacks. - Arash Rahnama; André T. Nguyen; Edward Raff (CoRR, 2019)

Heterogeneous Relational Kernel Learning. - André T. Nguyen; Edward Raff (CoRR, 2019)

Towards the Use of Neural Networks for Influenza Prediction at Multiple Spatial Resolutions. - Emily L. Aiken; André T. Nguyen; Mauricio Santillana (CoRR, 2019)

Robust Design of Deep Neural Networks Against Adversarial Attacks Based on Lyapunov Theory. - Arash Rahnama; André T. Nguyen; Edward Raff (CVPR, 2020)

Practical Cross-modal Manifold Alignment for Grounded Language. - André T. Nguyen; Luke E. Richards; Gaoussou Youssouf Kebe; Edward Raff; Kasra Darvish; Frank Ferraro; Cynthia Matuszek (CoRR, 2020)

Real-time estimation of disease activity in emerging outbreaks using internet search information. - Emily L. Aiken; Sarah F. McGough; Maimuna S. Majumder; Gal Wachtel; André T. Nguyen; Cécile Viboud; Mauricio Santillana (PLoS Comput. Biol., 2020)

Adversarial Transfer Attacks With Unknown Data and Class Overlap. - Luke E. Richards; André T. Nguyen; Ryan Capps; Steven Forsyth; Cynthia Matuszek; Edward Raff (AISec@CCS, 2021)

Practical Cross-Modal Manifold Alignment for Robotic Grounded Language Learning. - André T. Nguyen; Luke E. Richards; Gaoussou Youssouf Kebe; Edward Raff; Kasra Darvish; Frank Ferraro; Cynthia Matuszek (CVPR Workshops, 2021)

Leveraging Uncertainty for Improved Static Malware Detection Under Extreme False Positive Constraints. - André T. Nguyen; Edward Raff; Charles Nicholas; James Holt (CoRR, 2021)

Estimating the cumulative incidence of COVID-19 in the United States using influenza surveillance, virologic testing, and mortality data: Four complementary approaches. - Fred S. Lu; André T. Nguyen; Nicholas B. Link; Mathieu Molina; Jessica T. Davis; Matteo Chinazzi; Xinyue Xiong; Alessandro Vespignani; Marc Lipsitch; Mauricio Santillana (PLoS Comput. Biol., 2021)

Out of Distribution Data Detection Using Dropout Bayesian Neural Networks. - André T. Nguyen; Fred Lu; Gary Lopez Munoz; Edward Raff; Charles Nicholas; James Holt (AAAI, 2022)

Minimizing Compute Costs: When Should We Run More Expensive Malware Analysis? - André T. Nguyen; Richard Zak; Luke E. Richards; Maya Fuchs; Fred Lu; Robert Brandon; Gary Lopez Munoz; Edward Raff; Charles Nicholas; James Holt (CAMLIS, 2022)

Improving Out-of-Distribution Detection via Epistemic Uncertainty Adversarial Training. - Derek Everett; André T. Nguyen; Luke E. Richards; Edward Raff (CoRR, 2022)

Position: Challenges and Opportunities for Differential Privacy in the U.S. Federal Government. - Amol Khanna; Adam McCormick; André T. Nguyen; Chris Aguirre; Edward Raff (CoRR, 2024)

Stop Walking in Circles! Bailing Out Early in Projected Gradient Descent. - Philip Doldo; Derek Everett; Amol Khanna; André T. Nguyen; Edward Raff (CVPR, 2025)