• MS in Computer Science (In Progress), The University of Texas at El Paso (2023)
• Ph D in Mathematics, New Mexico State University (2015)
• Ph D in Mathematics, New Mexico State University (2015)
• MS in Mathematics, The University of Texas at El Paso (2009)
• BS in Computer Science, The University of Texas at El Paso (2007)

• Why Squashing Functions in Multi-Layer Neural Networks Proceedings of the 2020 IEEE International Conference on Systems, Man, and Cybernetics SMC’2020 (2020), Julio C. Urenda, Orsolya Csiszar, Gabor Csiszar, Jozsef Dombi, Olga M. Kosheleva, Vladik Y. Kreinovich.
• How Mathematics and Computing Can Help Fight the Pandemic: Two Pedagogical Examples Proceedings of the Annual Conference of the North American Fuzzy Information Processing Society NAFIPS’2020 (2020), Julio C. Urenda, Olga M. Kosheleva, Martine C. Ceberio, Vladik Y. Kreinovich.
• How User Ratings Change with Time: Theoretical Explanation of an Empirical Formula Proceedings of the Annual Conference of the North American Fuzzy Information Processing Society NAFIPS’2020 (2020), Julio C. Urenda, Manuel J. Hernandez, Natalia Villanueva-Rosales, Vladik Y. Kreinovich.
• Natural Invariance Explains Empirical Success of Specific Membership Functions, Hedge Operations, and Negation Operations Proceedings of the Annual Conference of the North American Fuzzy Information Processing Society NAFIPS’2020 (2020), Julio C. Urenda, Orsolya Csiszar, Gabor Csiszar, Jozsef Dombi, Gyorgy Eigner, Vladik Y. Kreinovich.
• Why a Classification Based on Linear Approximation to Dynamical Systems Often Works Well in Nonlinear Cases Proceedings of the Annual Conference of the North American Fuzzy Information Processing Society NAFIPS’2020 (2020), Julio C. Urenda, Vladik Y. Kreinovich.
• COVID-19 Peak Immunity Values Seem to Follow Lognormal Distribution Applied Mathematical Sciences 14 12 (2020), Julio C. Urenda, Olga M. Kosheleva, Vladik Y. Kreinovich, Tonghui Wang.
• Two Runners in the Time of Social Distancing, Speedboats in the Gulf of Finland: How to Best Pass? International Mathematical Forum 15 7 (2020), Julio C. Urenda, Olga M. Kosheleva, Vladik Y. Kreinovich.
• Which Distributions (or Families of Distributions) Best Represent Interval Uncertainty: Case of Permutation-Invariant Criteria Proceedings of the 18th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems IPMU'2020, Lisbon, Portugal, June 15-19, 2020 (2020), Michael Beer, Julio C. Urenda, Olga M. Kosheleva, Vladik Y. Kreinovich.
• Why Spiking Neural Networks Are Efficient: A Theorem Proceedings of the 18th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems IPMU'2020, Lisbon, Portugal, June 15-19, 2020 (2020), Michael Beer, Julio C. Urenda, Olga M. Kosheleva, Vladik Y. Kreinovich.
• Hierarchial Multiclass Classification Works Better Than Direct Classification: An Explanation of the Empirical Fact Journal of Uncertain Systems 13 3 (2019), Julio C. Urenda, Nancy Avila, Nelly Gordillo, Vladik Y. Kreinovich.
• How to Make Decisions: Consider Multiple Scenarios, Consult Experts, Play Down Emotions – Quantitative Explanation of Commonsense Ideas Journal of Uncertain Systems 13 3 (2019), Julio C. Urenda, Francis Biney, Marco Cardiel, Perla De La O, Anthony DesArmier, Noa Dodson, Taylor Dodson, Sebastian Gonzalez, Laura Hinojos, Jorge Huerta, Ryan Jones, Oliver Martinez, Carlos A. Saldana Matamoros, Manuel Munoz, Vladik Y. Kreinovich.
• In the Absence of Information, 1/n Investment Makes Perfect Sense Applied Mathematical Sciences 13 12 (2019), Julio C. Urenda, Vladik Y. Kreinovich.
• When revolutions happen: algebraic explanation Journal of Uncertain Systems 13 2 (2019), Julio C. Urenda, Vladik Y. Kreinovich.
• Which Fourier components are most informative: general idea and case studies Journal of Uncertain Systems 13 2 (2019), Julio C. Urenda, Nancy Avila, Nelly Gordillo, Vladik Y. Kreinovich.
• Why Derivative: Invariance-Based Explanation Mathematical Structures and Modeling 52 (2019), Julio C. Urenda, Olga M. Kosheleva, Vladik Y. Kreinovich.
• Why Experts Sometimes Do Not Perform Well in Unusual Situations Mathematical Structures and Modeling 51 (2019), Julio C. Urenda, Vladik Y. Kreinovich.
• Why liquids? a symmetry-based solution to Weisskopf’s challenge Journal of Uncertain Systems 13 3 (2019), Julio C. Urenda, Vladik Y. Kreinovich.
• Why The Obvious Necessary Condition is (Often) Also Sufficient (TONCAS): An Explanation of the Phenomenon Mathematical Structures and Modeling 52 (2019), Julio C. Urenda, Vladik Y. Kreinovich.
• Why Top Experts Are Paid So Much: Economics-Based Explanation Applied Mathematical Sciences 13 12 (2019), Julio C. Urenda, Vladik Y. Kreinovich.

• Why Rectified Linear Activation Functions? Why Max-Pooling? A Possible Explanation (2021), Volume Tijuana Mexico, Julio C. Urenda.
• A Point-Free Version of the Alexandroff-Hausdorff Theorem (2021), Volume Las Cruces NM, Julio C. Urenda.
• Mexican Folk Arithmetic Algorithm Makes Perfect Sense (2021), Volume Purdue University, Julio C. Urenda.
• Why Squashing Functions in Multi-Layer Neural Networks (2020), Volume Toronto Canada, Julio C. Urenda.
• Covering Arrays as Algebraic Varieties (2019), Volume SFU-Vancouver Canada, Julio C. Urenda.

No info available.