Contextual multi-armed bandit algorithms for personalized learning action selection. - Indu Manickam; Andrew S. Lan; Richard G. Baraniuk (ICASSP, 2017)

Conveying language through haptics: a multi-sensory approach. - Nathan Dunkelberger; Jennifer L. Sullivan; Joshua Bradley; Nickolas P. Walling; Indu Manickam; Gautam Dasarathy; Ali Israr; Frances W. Y. Lau; Keith Klumb; Brian Knott; Freddy Abnousi; Richard G. Baraniuk; et al. (UbiComp, 2018)

IdeoTrace: a framework for ideology tracing with a case study on the 2016 U.S. presidential election. - Indu Manickam; Andrew S. Lan; Gautam Dasarathy; Richard G. Baraniuk (ASONAM, 2019)

A Multisensory Approach to Present Phonemes as Language Through a Wearable Haptic Device. - Nathan Dunkelberger; Jennifer L. Sullivan; Joshua Bradley; Indu Manickam; Gautam Dasarathy; Richard G. Baraniuk; Marcia K. O'Malley (IEEE Trans. Haptics, 2021)

Error-in-variables modelling for operator learning. - Ravi G. Patel; Indu Manickam; Myoungkyu Lee; Mamikon A. Gulian (MSML, 2022)

Thermodynamically consistent physics-informed neural networks for hyperbolic systems. - Ravi G. Patel; Indu Manickam; Nathaniel A. Trask; Mitchell A. Wood; Myoungkyu Lee; Ignacio Tomas; Eric C. Cyr (J. Comput. Phys., 2022)

Solving High-Dimensional Inverse Problems with Auxiliary Uncertainty via Operator Learning with Limited Data. - Joseph L. Hart; Mamikon A. Gulian; Indu Manickam; Laura P. Swiler (CoRR, 2023)

Machine Learning Based Resilience Testing of an Address Randomization Cyber Defense. - Ganapathy Mani; Marina Haliem; Bharat K. Bhargava; Indu Manickam; Kevin Kochpatcharin; Myeongsu Kim; Eric D. Vugrin; Weichao Wang; Chris Jenkins; Pelin Angin; Meng Yu 001 (IEEE Trans. Dependable Secur. Comput., 2023)

Stratospheric aerosol source inversion: Noise, variability, and uncertainty quantification. - Joseph L. Hart; Indu Manickam; Mamikon A. Gulian; Laura P. Swiler; Diana Bull; T. Ehrmann; H. Brown; B. Wagman; Jerry Watkins (CoRR, 2024)