Daniel Fuertes

Daniel Fuertes

Assistant Professor @ Universidad Politécnica de Madrid (UPM)

🔬 AI Researcher  |  👨‍🏫 Assistant Professor  |  🦾 Deep Reinforcement Learning

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👋 About Me

Daniel Fuertes received the Bachelor’s degree in Telecommunication Engineering in 2019 and the Ph.D. degree in Telecommunication Engineering in 2025, both from the Universidad Politécnica de Madrid (UPM), Madrid, Spain. He has been a member of the Grupo de Tratamiento de Imágenes (Image Processing Group) at UPM since 2020, actively participating in several research projects with industry partners. In 2025, he joined the Department of Signals, Systems, and Communications as an Assistant Professor of Signal Theory and Communications.

His research interests lie in the fields of Artificial Intelligence, Deep Learning, Reinforcement Learning, Autonomous Navigation, Vehicle Routing Problems, Computer Vision, Machine Learning, and Signal Processing.

Summary:

• 📡 Telecommunications Engineer, specialized in audiovisual systems and signal processing.
• 📈 Master’s in Signal Theory and Communications, focused on Machine Learning for Big Data.
• 🎓 PhD in Telecomunications Engineering at Grupo de Tratamiento de Imágenes (GTI).
• 🌍 International internship at Idiap Research Institute.
• ✈️ Several research projects with industry partners like Airbus Defence and Space.
• 🧠 AI Researcher in Transformer Networks, LLMs, Computer Vision, and Autonomous Navigation.

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🛠️ Skills & Tools

💻 Programming, Scripting & IDEs
🤖 Deep (Reinforcement) Learning
🗃️ DevOps & Tools
📊 Scientific Computing, ML & Visualization
🧪 Experiment Tracking
✍️ Documentation & Writing
💻 OS & Environment

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📚 Publications

Multi-agent Route Planning using Deep Reinforcement Learning Techniques and Transformer Networks for Graph Analysis

PhD in Telecommunication Engineering (UPM), 2025

📖 Thesis

NaviFormer: A Deep Reinforcement Learning Transformer-like Model to Holistically Solve the Navigation Problem

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2025

📄 Paper Arxiv 👾 Code

Multi-stage Planning for Multi-target Surveillance using Aircrafts Equipped with Synthetic Aperture Radars Aware of Target Visibility

IEEE International Conference on Automation Science and Engineering (CASE), 2025

📄 Paper Arxiv

TOP-Former: A Multi-Agent Transformer Approach for the Team Orienteering Problem

IEEE Transactions on Intelligent Transportation Systems, 2025

📄 Paper Arxiv 👾 Code

Enhanced Nighttime Vehicle Detection for On-Board Processing

IEEE Access, 2025

📄 Paper

Solving Routing Problems for Multiple Cooperative Unmanned Aerial Vehicles using Transformer Networks

Engineering Applications of Artificial Intelligence, 2023

📄 Paper 👾 Code

People Detection with Omnidirectional Cameras using a Spatial Grid of Deep Learning Foveatic Classifiers

Digital Signal Processing, 2022

📄 Paper 👾 Code

LogoMix: A Data Augmentation Technique for Object Detection Applied to Logo Recognition

IEEE International Conference on Consumer Electronics (ICCE), 2022

📄 Paper 👾 Code

Implementation of a logo detection system based on deep learning strategies for media impact analysis in social networks

Master in Signal Theory and Communications (UPM), 2020

📖 Thesis

Implementation of a vehicle detection system based on convolutional neural networks from traffic IP cameras

Bachelor’s Degree in Telecommunication Engineering (UPM), 2019

📖 Thesis

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🏆 Awards

• 🥇 CESEDEN First Prize – Defense Tech Research (Zarco del Valle), 2023.
• 🥈 CESEDEN Second Prize – Defense Tech Research (Zarco del Valle), 2022.
• 📺 RTVE Award – Best Academic Record in Audiovisual Systems (2019)