Exploring the combination of Artificial Intelligence and Operations Research for Combinatorial Optimization.
I'm a scientist and engineer focused on Deep Reinforcement Learning and Operations Research methods to solve Combinatorial Optimization problems. Currently working as a researcher at INESC-ID and teaching at IST.
Latest Posts
Notes on RL: An Introduction
A deep dive into the foundational concepts of Reinforcement Learning, exploring Markov Decision Processes (MDPs) and basic policy iteration methods.
Attention: Learn To Solve Routing Problems
Analyzing the application of Attention mechanisms in Neural Combinatorial Optimization. How transformers can replace heuristics for TSP and VRP.
Combinatorial Optimization Intro
An introduction to the field of Combinatorial Optimization, focusing on complexity classes (P vs NP) and exact vs. heuristic solving methods.
Latest Projects
WSmart Route+ RL Agent
A Reinforcement Learning agent designed to optimize Waste Collection routing. This project explores how RL agents can learn efficient paths in dynamic environments compared to traditional heuristics.
CSE Master of Science (MSc) Dissertation GNN
Thesis: "Leveraging Deep Unsupervised Models Towards Learning Robust Multimodal Representations". Developed and compared new Multimodal Deep Unsupervised Models.
Personal Website Next.js
The website you are looking at right now, showcasing my blog posts and projects. Built with Next.js, React, and Tailwind CSS for modern design.