About Me

Hello and welcome to my homepage!

I’m Diego Fregolent Mendes de Oliveira, an Assistant Professor at the School of Electrical Engineering & Computer Science at the University of North Dakota. My research explores the intersection between people and computing systems, with a focus on how information flows through social networks and how its quality and integrity are shaped in cyberspace. I am particularly interested in ensuring the trustworthiness and reliability of social computing systems.

Another important area of my research is Diversity, Equity, and Inclusion (DEI) across scientific disciplines. By analyzing publication records, funding data, and awards, I work to uncover and understand gender disparities in academia.

My expertise spans complex network systems, including data analysis, machine learning, agent-based modeling, and computational social science. I also have a strong background in chaos and dynamical systems, studying nonlinear dynamics, chaotic attractors, and bifurcation phenomena.

Before joining the University of North Dakota, I held several research positions. I was a Postdoctoral Research Associate at the Statistical and Applied Mathematical Sciences Institute (SAMSI) and the University of North Carolina, where I collaborated with Prof. Peter Mucha, Prof. M. Gregory Forest, and Prof. David Banks. I also served as a Research Scientist at Rensselaer Polytechnic Institute and the Army Research Lab, working with Prof. Boleslaw K. Szymanski and Dr. Kevin S. Chan.

Prior to that, I was a Postdoctoral Fellow at Northwestern University, collaborating with Prof. Luís Amaral and Prof. Brian Uzzi in the Department of Chemical and Biological Engineering and the Northwestern Institute on Complex Systems (NICO).

Here, you can find more about my work on complex networks and time-dependent systems.

Research Interests

Complex Network Systems: Data analysis, data visualization, big data, data mining, machine learning, optimization, social network analysis, sentiment analysis, agent-based modeling, computational social science, information diffusion, modeling dynamical processes on networks, online social media.

Chaos and Dynamical Systems: Nonlinear dynamics, closed and open systems, scaling laws, discrete maps, chaotic dynamics, conservative and dissipative systems, time-dependent systems, Fermi acceleration, billiards, kicked systems, chaotic and periodic attractors, bifurcations, and boundary crises.