I earned my PhD from the Department of Computer Science at the University of Maryland, College Park, advised by Prof. David Mount. My research interests lie generally in Theoretical Computer Science, including Computational Geometry, Approximation Algorithms, and Data Structures. I’m always looking for research opportunities, just contact me!
My research revolves around the goal of achieving more efficient nearest-neighbor classification, showing results that are practical for large-scale applications, while also having provable theoretical guarantees. This work focuses on two main subjects. First, on the development and analysis of algorithms to reduce the training set used for classification. These reduced subsets can be either heuristically obtained [CCCG’19, CCCG’20] or \(\varepsilon\)-coresets [ESA’20]. Additionally, I’ve been working on proposing new data structures specially tailored for answering \(\varepsilon\)-approximate nearest-neighbor classification queries [ESA’21], achieving the lowest complexity of any approach so far.
I completed my undegraduate studies at Universidad Simón Bolívar, Venezuela, earning a BEng. in Computer Science, Cum Laude. During those years, I had the pleasure of working with great people. First, with Prof. María-Esther Vidal, on topics related to Semantic Web and Graph Databases (see publications). Additionally, I was advised by Prof. Emely Arráiz towards my undegraduate thesis, titled Bio-Inspired Metaheuristics for Instance Selection, which was awarded an outstanding honorable mention by the committee.
Born and raised in Venezuela . My country lives under a dictatorship that has forced over 5M people to flee. Venezuela deserves to be free, and we will never stop fighting. During my free time, I enjoy photography (specially macro photography), biking, hiking, dancing, and cooking.
Condensation HeuristicsSee CCCG'19, CCCG'20
$$ \varepsilon $$-Coresets for the NN RuleSee ESA'20
Chromatic AVDSee ESA'21
Ph.D. in Computer ScienceUniversity of Maryland, College Park 2015-2022
M.Sc. in Computer ScienceUniversity of Maryland, College Park 2015-2018
B.Eng. in Computer ScienceUniversidad Simón Bolívar 2009-2014 · Cum Laude
Facebook Inc.Software Engineer PhD Intern Seattle • Summer 2019
University of MarylandTA & Summer Lecturer 2015-2022
Universidad Simón BolívarVisiting Professor Virtually • Spring 2022
Venezuela InteligenteCo-founder & Developer 2012-2017
Universidad Simón BolívarResearch & Teaching Assistant 2012-2015
|Jun 8, 2022||Accepted abstract for the Young Researchers Forum at SoCG’22 (Symposium on Computational Geometry), Berlin, Germany (attending virtually).|
|May 9, 2022||Successfully defended my dissertation titled “Algorithms and Data Structures for Faster Nearest-Neighbor Classification” You can find the presentation slides here.|
|Feb 8, 2022||Working as a Visiting Professor at Universidad Simón Bolívar (Venezuela), teaching Algorithms & Data Structures II for the first term of 2022.|
|Sep 6, 2021||Paper accepted to ESA’21 (European Symposium on Algorithms), Lisbon, Portugal (virtual).|
|Jun 7, 2021||Accepted talk for the 5th Workshop on Geometry and Machine Learning. This will take place during SoCG’21 (Symposium on Comp. Geometry), Buffalo, USA (virtual).|
|Sep 7, 2020||Paper accepted to ESA’20 (European Symposium on Algorithms), Pisa, Italy (virtual).|
PreprintImproved Search of Relevant Points for Nearest-Neighbor ClassificationPreprint on the arXiv, to be submitted, 2022
ESA’21Boundary-Sensitive Approach for Approximate Nearest-Neighbor Classification29th Annual European Symposium on Algorithms, 2021
ESA’20Coresets for the Nearest-Neighbor Rule28th Annual European Symposium on Algorithms, 2020
CCCG’20Social Distancing is Good for Points too!32nd Canadian Conference on Computational Geometry, 2020
CCCG’19Guarantees on Nearest-Neighbor Condensation Heuristics31nd Canadian Conference on Computational Geometry, 2019