Ph.D.
- Jazmín Ojeda — Hydrology with artificial intelligence.
- Alejandro Reckziegel — Co-supervisor. Mosquito models with Dr. Christian Schaerer.
- Juan Vicente Bogado — Co-supervisor. Dengue models with Dr. Christian Schaerer.
Mentoring
Training researchers multiplies impact.
Undergraduate, master's and doctoral projects in computing, AI and scientific instrumentation. Each link opens the available PDF summary.
Current students
Research and undergraduate projects currently in progress, organized by academic level.
Master's in Artificial Intelligence
- Ivan Gonzalez — Space weather, with Dr. Jorge Molina.
- Monica Fernández — Electricity demand, with MSc. Carlos Sauer.
- Andrea Cristaldo — Co-supervisor, with Dr. Eduardo Redondo.
- Federico Moran — AI for urban floods, with Dr. Enrique Vargas (UCA).
- Juan Barboza — Gait analysis with AI, with Dr. Fernando Brunetti (UCA).
Undergraduate engineering
- Mathias Aguilar and Héctor Velázquez — Water-level sensors and rain gauges.
- Victoria Paredes and Francisco González — IoT and precipitation nowcasting.
- Evelyn Paredes and Venus Ayala — Citizen science for floods.
- Fabrizio Moisés Caballero Aquino and Judith Giselle Jacquet Boschi — Specialized models for forecasting electricity-demand peaks in Paraguay's National Interconnected System.
- Marcos Ariel Villalba Villalba and Ignacio Gabriel Soler Galiano — Shear verification of reinforced-concrete beams using large language models (LLMs) and deterministic comparison, with MSc. Herman Segovia.
- Mauricio Josué Romero Ferreira — Improvements to solar-radio-burst acquisition and automatic classification, with a solar tracker at the e-CALLISTO Paraguay station.
Completed theses
Technical and executive summaries organized from newest to oldest.
Recent projects
- Local processing prototype for detection and classification — Carlos Benítez.
- Deep Learning and agent-based modeling application — Lucar Pin and Mateo Martínez.
- AI for photovoltaic system diagnosis and predictive maintenance — Gonzalo Rojas and Mathias Benítez.
Completed projects
- Smart device for residential electricity demand profiles — Clement Torres and Victor Viveros.
- Low-cost portable cardiac monitoring device — Carlos Oliveri and Abel Torales.
- AI-based intelligent mosquito trap — Diego Balbuena and Mathias Barrios.
- Rotating equipment fault detection — Emanuel Orzusa.
- Wingbeat detector and automated mosquito classification — Norman Zichner.
- Control and data-processing system for the MUA mission — Sebastián Monje.
- Low-cost autonomous particulate matter station — Silvia Jacqueline Barreto Cristaldo.
- Thermal insulation waste reduction using Six Sigma — Rodrigo Azcurra and Fabio Maidana.
- Particle detector for FIUNA's MUA mission — Maximiliano Romero.
Completed projects
- Intelligent muon-track reconstruction system — Santiago Ferreyra.
- Artificial intelligence for antiviral drug prediction — Rafael Adorno.
Completed projects
- Deep Learning for short-term electricity demand forecasting — Aguilar and Vargas.
- Low-cost geomagnetic station — Cristian Paniagua.
- Lung cancer detection and diagnosis with data science — Emilio.
- CALLISTO optimization and automated solar radio burst detection — Ivan Gonzalez.
- Muon segmentation and tracking for CONNIE — Karina and Carlos.
Completed projects
- Injection mold for an intelligent electrocardiograph casing — Horacio and Renato.
- Characterization of a transverse electromagnetic-wave cell — Alejandro Reckziegel.
- Low-cost communication system for LEO satellites — Miranda and Kunert.
- Instance segmentation for particle detection — Espinoza and Toledo.
- Monitoring and characterization of electricity demand profiles — Hans.
Completed project
- Deep Learning for muon identification in the CONNIE experiment — Javier Bernal.
Completed projects
- Platform for nanosatellite attitude-control testing — Fretes and Galeano.
- Morales and Verdún thesis summary.
- CanSat picosatellite design and implementation — Moreira.
- Attitude determination and control system for CubeSats — Víctor Guillermo.
Completed project
- Facial pain-expression recognition using convolutional neural networks — Yuli Viterbori and Jorge Hernaez.