I am a first year PhD student at
Mila and DIRO under the supervision of
Simon Lacoste-Julien.
I am broadly interested in constrained optimization and how it
can be used to reliably achieve certain properties in machine learning models.
I am curious about the relationships between constrained
optimization, game theory, bilevel optimization and variational inference.
Check out Cooper, a library for constrained optimization in Pytorch that I co-develop.
Previously, I was an intern at Simon's group at Mila under the
supervision of Jose Gallego-Posada.
Before that, I graduated from the BSc in Mathematical Engineer at
Universidad EAFIT. During the BSc, I spent a
summer at McKinsey & Co. as a research intern.
Research interests: Constrained Optimization, Machine Learning, Sparsity.
Contact: juan43ramirez (at) gmail (dot) com
Jan 27: I will attend Khipu 2023 in Montevideo, Uruguay. Glad to be a part of the Latin American AI community.
Oct 14: See you at the Pytorch conference 2022 at New Orleans! Cooper will be making an appearance (poster).
Sep 14: I will be presenting my first NeurIPS paper: Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love Constraints at New Orleans.
Sep 05: Excited to start a PhD in Artificial Intelligence under the supervision of Simon Lacoste-Julien at Mila and Université de Montréal
Aug 08: Check out the preprint of our paper titled: Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love Constraints.
Jul 25: I am taking part in CIFAR's Deep Learning Reinforcement Learning Summer School.
Jul 8: I am attending the Sparsity in Neural Networks workshop. We are presenting some of our latest work: L0onie: Compressing COINs with L0-constraints.
Mar 15: We have released Cooper: a library for Lagrangian-based constrained optimization in Pytorch.
Dec 17: Flexible Learning of Sparse Neural Networks via Constrained L0 Regularization, won the Best Poster Award at the LatinX in AI Workshop at NeurIPS2021!
Nov 1: I am starting an internship at Mila, one of the most prestigious labs doing research in deep learning. I will be a part of Simon Lacoste-Julien's group under the supervision of Jose Gallego-Posada.
Oct 22: My first ever paper, Flexible Learning of Sparse Neural Networks via Constrained L0 Regularization, has been accepted at the LatinX in AI Workshop at NeurIPS2021!
Sep 1: I am auditing Sarath Chandar's Machine Learning at Polytechnique Montréal.
Aug 2: during the next three weeks, I will attend (virtually) Neuromatch's Deep Learning Summer School.
Jul 18: I am attending an ML conference for the first time: ICML 2021.
Jul 1: I graduated from the BSc in Mathematical Engineering at Universidad EAFIT! Plus, got a mention for my contributions to the student organization. Check out my Linkedin post on the matter.
Jan 23: I started Mandarin Chinese lessons at Instituto Confucio. [Chinese characters follow] 我会说一点汉语.
Jan 14: I am auditing Ioannis Mitliagkas' graduate course on Deep Learning Theory at Université de Montréal.
Jul 2020: Jose Gallego-Posada, current PhD student at Mila and Université de Montréal will supervise me during my second research practice for the BSc. I am starting to learn about deep generative models.
Jul 2020: I am taking Henry Laniado's graduate course in Robust and Non-Parametric Statistics at Universidad EAFIT.
Jan 2020: I am now working to develop ML models to responsibly approve credit cards for clients without a financial history as an intern at Tuya's Risk Analytics Lab in Medellín.
Jun 2019: I have joined McKinsey & Co. in Belgium as a research intern. I am working with Antoine Stevens and Patrick Dehout in leveraging machine learning for the agricultural and chemical industries.
Jan 2019: I travel to Louvain-la-Neuve, Belgium for an exchange semestrer at Université Catholique de Louvain. I am taking Pierre Dupont's graduate courses on Machine Learning and Bioinformatics.
Nov 2017: I will be the director of CIGMA-OE , the Mathematical Engineering committee of the Student Organization at Universidad EAFIT. https://www.instagram.com/cigmaoe/?hl=en
Dec 2015: I have been awarded a full scholarship for the Bachelor's degree in Mathematical Engineering Mathematical Engineering at Universidad EAFIT.
Dec 2015: I got a score amongst the best 0.1% on the Colombian high school examination ICFES. Unfortunately, I did not make the cut for the Andrés Bello prize. Maybe you have to get a score amongst the best 0.01% for that?
Dec 2015: I achieved the first place in the National Chemistry Olympiads of Universidad de Antioquia.
Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love Constraints. J. Gallego-Posada, J. Ramirez, A. Erraqabi, Y. Bengio and S. Lacoste-Julien. NeurIPS, 2022.
L0onie: Compressing COINs with L0-constraints. J. Ramirez and J. Gallego-Posada. 2022 Sparsity in Neural Networks Workshop.
Flexible Learning of Sparse Neural Networks via Constrained L0 Regularization. J. Gallego-Posada, J. Ramirez and A. Erraqabi.
NeurIPS 2021 LatinX in AI Workshop.
J. Gallego-Posada and J. Ramirez (2022). Cooper: a general-purpose library for constrained optimization in Pytorch [Computer software].