Henrique Ferraz de Arrua
Centre: BIFI
Institution: Universidad de Zaragoza, Zaragoza (España)
Position: Researchers from the “ARAID” program
E-mail: henrique.ferraz@bifi.es
Phone: 976762989
Web: https://bifi.es/physics/Complex Systems and Networks
Profile:
Personal statement
I began my research career while studying Computer Science at the University of São Paulo, Brazil, where I developed a strong interest in computational and mathematical modeling. I later pursued a master’s and a Ph.D. in Computer Science and Computational Mathematics at the University of São Paulo (ICMC-USP), where my doctoral work – awarded the CAPES Thesis Award for the best Ph.D. thesis in Computer Science in Brazil (2020) – focused on text representation as networks for machine learning and the dynamics of knowledge acquisition in citation networks.
My academic path has included research stays and positions at institutions in Brazil, Spain, Italy, and the United States, such as IFSC-USP, the University of Zaragoza, the ISI Foundation, the CENTAI Institute, and George Mason University. These experiences have enabled me to collaborate with international research groups in areas that span complex networks, artificial intelligence, computational social sciences, and data science.
Since joining the BIFI Institute at the University of Zaragoza as an ARAID researcher, I have continued exploring the intersection between complex systems and computation, particularly in the analysis of social and food composition data. My multidisciplinary background also includes work in image processing, neural networks, and parallel programming.
Researcher profile identity
I am an R3 established researcher. I study artificial intelligence and complex systems. These systems consist of many interconnected elements, and their interactions result in behaviors that cannot be explained by examining the components individually. I use network-based representations to study these systems, but I also explore computational approaches beyond networks. I combine methods from artificial intelligence, machine learning, and computational social sciences to understand how systems behave and evolve. I have applied these approaches to social networks, knowledge dynamics, scientific citations, food composition data, and other areas.
Why my research is important
While my research is rooted in an understanding of complex systems and artificial intelligence, it offers the distinct advantage of applying advanced techniques to a wide variety of practical challenges. For example, I combine methods from AI, complex networks and computational social sciences to model intricate dynamics, from social simulations to the analysis of food composition data. This demonstrates how these advances have a direct impact on public health, moving beyond theoretical computer science. My inherently multidisciplinary approach links fundamental research with practical applications, benefiting the generation of new scientific knowledge, industry understanding and society as a whole. My contributions extend beyond scientific results. I develop essential tools and methodologies to help people make informed decisions when managing complex phenomena in our data-rich world.
Know more about me and my research here
- Personal web: https://hfarruda.gitlab.io/
- Research group project page: https://cosnet.bifi.es/
- LinkedIn: https://www.linkedin.com/in/henrique-ferraz-de-arruda-5071a479/
