eFuzz: A Fuzzer for DLMS/COSEM Electricity Meters. - Henrique Dantas; Zekeriya Erkin; Christian Doerr; Raymond Hallie; Gerrit van der Bij (SEGS@CCS, 2014)

Neural decoding using a nonlinear generative model for brain-computer interface. - Henrique Dantas; Spencer S. Kellis; V. John Mathews; Bradley Greger (ICASSP, 2014)

Recording and Decoding for Neural Prostheses. - David J. Warren; Spencer S. Kellis; Jacob G. Nieveen; Suzanne M. Wendelken; Henrique Dantas; Tyler S. Davis; Douglas T. Hutchinson; Richard A. Normann; Gregory A. Clark; V. John Mathews (Proc. IEEE, 2016)

Neural decoding systems using Markov Decision Processes. - Henrique Dantas; V. John Mathews; Suzanne M. Wendelken; Tyler S. Davis; Gregory A. Clark; David J. Warren (ICASSP, 2017)

Shared Human-Machine Control for Self-Aware Prostheses. - Henrique Dantas; Jacob Nieven; Tyler S. Davis; Xiao Fu; Gregory A. Clark; David J. Warren; V. John Mathews (ICASSP, 2018)

Semi-Supervised Adaptive Learning for Decoding Movement Intent from Electromyograms. - Henrique Dantas; V. John Mathews; David J. Warren (EUSIPCO, 2019)

Deep Learning Movement Intent Decoders Trained With Dataset Aggregation for Prosthetic Limb Control. - Henrique Dantas; David J. Warren; Suzanne M. Wendelken; Tyler S. Davis; Gregory A. Clark; V. John Mathews (IEEE Trans. Biomed. Eng., 2019)

Interpreting Volitional Movement Intent From Biological Signals: A Review. - Henrique Dantas; Taylor C. Hansen; David J. Warren; V. John Mathews (IEEE Signal Process. Mag., 2021)

Shared Prosthetic Control Based on Multiple Movement Intent Decoders. - Henrique Dantas; Taylor C. Hansen; David J. Warren; V. John Mathews (IEEE Trans. Biomed. Eng., 2021)