arXiv subjects

Alejandro Rodriguez Perez

Publications and source records attributed to Alejandro Rodriguez Perez.

3 recordsLinked to original sources

arXiv2025

Coherent Field Emission Upon Ultrafast Laser Irradiation of the Tip Plasmon

Irradiation of sharp silver tips with femtosecond laser pulses leads to photoassisted coherent field emission without a static field. We reconstruct the time profile of the emission, and show that the process is entirely governed by the collective response of the tip plasmon and its field emission. Weak-field optical excitation leads to multiphoton absorption and field emission from the tip apex due to the enhanced local field. The attendant sharp field gradient ensures ponderomotive acceleration of emitted electrons and non-local light-matter interaction. The crossover regime in which simultaneous multiphoton absorption and optical field emission take place is evidenced by the time profile of electron emission correlation, laser power dependence, and polarization angle dependence of each harmonic current.

physics.optics↗

arXiv2024

On the Challenges of Creating Datasets for Analyzing Commercial Sex Advertisements to Assess Human Trafficking Risk and Organized Activity

Our study addresses the challenges of building datasets to understand the risks associated with organized activities and human trafficking through commercial sex advertisements. These challenges include data scarcity, rapid obsolescence, and privacy concerns. Traditional approaches, which are not automated and are difficult to reproduce, fall short in addressing these issues. We have developed a reproducible and automated methodology to analyze five million advertisements. In the process, we identified further challenges in dataset creation within this sensitive domain. This paper presents a streamlined methodology to assist researchers in constructing effective datasets for combating organized crime, allowing them to focus on advancing detection technologies.

cs.LG↗

arXiv2023

Combatting Human Trafficking in the Cyberspace: A Natural Language Processing-Based Methodology to Analyze the Language in Online Advertisements

This project tackles the pressing issue of human trafficking in online C2C marketplaces through advanced Natural Language Processing (NLP) techniques. We introduce a novel methodology for generating pseudo-labeled datasets with minimal supervision, serving as a rich resource for training state-of-the-art NLP models. Focusing on tasks like Human Trafficking Risk Prediction (HTRP) and Organized Activity Detection (OAD), we employ cutting-edge Transformer models for analysis. A key contribution is the implementation of an interpretability framework using Integrated Gradients, providing explainable insights crucial for law enforcement. This work not only fills a critical gap in the literature but also offers a scalable, machine learning-driven approach to combat human exploitation online. It serves as a foundation for future research and practical applications, emphasizing the role of machine learning in addressing complex social issues.

cs.LG↗