> I'm a 2nd year Ph.D. student at the University of Pennsylvania, where I mostly think about optimization theory, signal processing and machine learning with Prof. Ribeiro.
Before graduate school, I spent some time at Stanford's Kundaje Lab, working on chromatin accessibility prediction and genomic motif discovery. I was also a summer intern at CERN, contributing to the CMS Open Data initiative with Dr. Lassila-Perini.
I'm originally from Montevideo, Uruguay, where I obtained a BSc. in Electrical Engineering from UdelaR . During my undergrad I was a signal processing intern at ProteanTecs , a chip predictive maintenance start-up, and before that, I was a software developer at IBM .
3401 Walnut, Room 405b
Philadelphia, PA, 19104
Most recent publications on Google Scholar.
‡ indicates equal contribution.
Neural Networks with Quantization Constraints.
Ignacio Hounie*, Juan Elenter*, Alejandro Ribeiro
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2023.
A Lagrangian Duality Approach to Active Learning
Juan Elenter, Navid NaderiAlizadeh, Alejandro Ribeiro
Neural Information Processing Systems, 2022.
Neural Networks with Quantization Constraints.
Ignacio Hounie*, Juan Elenter*, Alejandro Ribeiro
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2023.
A Lagrangian Duality Approach to Active Learning
Juan Elenter, Navid NaderiAlizadeh, Alejandro Ribeiro
Neural Information Processing Systems, 2022.
Graph Neural Networks for genome enabled prediction of complex traits.
Juan Elenter, Ignacio Hounie, Guillermo Etchebarne,María Inés Fariello, Federico Lecumberry
Probabilistic Modeling in Genomics, CSHL, 2021.
Full Resume in PDF.
Some stuff I like about my country.
Water is my natural environment.