Events

WISS Presentation
Dr. Pedro Pedrosa Rebouças Filho
Wednesday, April 2 – 12-1pm
ITE 459
Free lunch for those who RSVP

Bridging AI Theory and Practice: Deep Learning, Explainability, and Real-World Applications

Artificial Intelligence has become a fundamental pillar in modern technological advancements, with deep learning leading breakthroughs across multiple domains. However, despite the remarkable progress, AI models often remain “black boxes,” raising concerns about transparency, reliability, and trust.

In this talk, we will explore how AI research bridges theory and practice, emphasizing the significance of Deep Learning and Explainable AI (XAI) in real-world applications. The discussion will include foundational concepts, current challenges, and innovative solutions developed at LAPISCO — ranging from AI-driven surveillance systems to healthcare applications that enhance medical diagnosis.

This session aims to foster discussions on collaborative research opportunities by presenting key research contributions and industry-driven projects, bridging the gap between academia and applied AI solutions.

Dr. Pedro Pedrosa Rebouças Filho is an AI and Machine Learning researcher with over 15 years of expertise in academia and industry. He is currently a Postdoctoral Research Fellow at UMBC under the supervision of Professor Houbing Song. Since 2008, Dr. Pedrosa has served as an Associate Professor at the Federal Institute of Ceará (IFCE), and since 2016, as a Visiting Professor at the Federal University of Ceará (UFC).

Dr. Pedrosa leads AI research at LAPISCO, where he has managed over 30 major projects focused on AI-driven solutions for surveillance, healthcare, and energy. He holds a PhD in Teleinformatics from UFC and has completed postdoctoral work at the University of Porto. A distinguished member of the Brazilian Academy of Sciences and IEEE Senior Member, Dr. Pedrosa has received prestigious awards such as the BRAGFOST Young Scientist Award and BRICS Young Scientist Award. He has published over 200 papers, contributing significantly to both academic research and real-world AI applications.

Personal Website: reboucasfilhopedropedrosa.github.io
LinkedIn: linkedin.com/in/reboucasfilho-pedropedrosa