Double-spend Attack Models with Time Advantange for Bitcoin. - Carlos Pinzón 001; Camilo Rocha (CLEI Selected Papers, 2016)

Make Puzzles Great Again. - Nicolás Aristizabal; Carlos Pinzón 001; Camilo Rueda; Frank Valencia (The Art of Modelling Computational Systems, 2019)

A Random Network Model for the Analysis of Blockchain Designs with Communication Delay. - Carlos Pinzón 001; Camilo Rocha; Jorge Finke (CoRR, 2019)

Algorithmic Analysis of Blockchain Efficiency with Communication Delay. - Carlos Pinzón 001; Camilo Rocha; Jorge Finke (FASE, 2020)

Computing Distributed Knowledge as the Greatest Lower Bound of Knowledge. - Carlos Pinzón 001; Santiago Quintero; Sergio Ramírez; Frank Valencia (RAMiCS, 2021)

On the impossibility of non-trivial accuracy under fairness constraints. - Carlos Pinzón 001; Catuscia Palamidessi; Pablo Piantanida; Frank Valencia (CoRR, 2021)

On the Impossibility of Non-trivial Accuracy in Presence of Fairness Constraints. - Carlos Pinzón 001; Catuscia Palamidessi; Pablo Piantanida; Frank Valencia (AAAI, 2022)

Causal Discovery for Fairness. - Ruta Binkyte; Karima Makhlouf; Carlos Pinzón 001; Sami Zhioua; Catuscia Palamidessi (AFCP, 2022)

Minimizing Information Leakage under Padding Constraints. - Sebastian Simon; Cezara Petrui; Carlos Pinzón 001; Catuscia Palamidessi (CoRR, 2022)

On the Computation of Distributed Knowledge as the Greatest Lower Bound of Knowledge. - Santiago Quintero; Carlos Pinzón 001; Sergio Ramírez; Frank Valencia (CoRR, 2022)

Counting and Computing Join-Endomorphisms in Lattices (Revisited). - Carlos Pinzón 001; Santiago Quintero; Sergio Ramírez; Camilo Rueda; Frank Valencia (CoRR, 2022)

Frequency Estimation of Evolving Data Under Local Differential Privacy. - Héber Hwang Arcolezi; Carlos Pinzón 001; Catuscia Palamidessi; Sébastien Gambs (EDBT, 2023)

Obfuscation Padding Schemes that Minimize Rényi Min-Entropy for Privacy. - Sebastian Simon; Cezara Petrui; Carlos Pinzón 001; Catuscia Palamidessi (ISPEC, 2023)

Exploring fairness and privacy in machine learning. (Exploring fairness and privacy in machine learning). - Carlos Pinzón 001 (2023)

Causal Discovery Under Local Privacy. - Ruta Binkyte; Carlos Pinzón 001; Szilvia Lestyan; Kangsoo Jung; Héber Hwang Arcolezi; Catuscia Palamidessi (CLeaR, 2024)

Why the p-norms p=1, p=2 and p=∞ are so special? An answer based on spatial uniformity. - Carlos Pinzón 001 (CoRR, 2024)

On the incompatibility of accuracy and equal opportunity. - Carlos Pinzón 001; Catuscia Palamidessi; Pablo Piantanida; Frank Valencia (Mach. Learn., 2024)

Jeffrey's update rule as a minimizer of Kullback-Leibler divergence. - Carlos Pinzón 001; Catuscia Palamidessi (CoRR, 2025)

Estimating the True Distribution of Data Collected with Randomized Response. - Carlos Antonio Pinzón; Ehab ElSalamouny; Lucas Massot; Alexis Miller; Héber Hwang Arcolezi; Catuscia Palamidessi (AAAI, 2026)

Information Leakage Envelopes. - Sara Saeidian; Carlos Antonio Pinzón; Catuscia Palamidessi (CoRR, 2026)