Assistant Professor · Department of Computer and Digital Systems Engineering (PCS) · Polytechnic School, University of São Paulo (USP)
Vinicius is an Assistant Professor in the Department of Computer and Digital Systems Engineering (PCS) at the Polytechnic School of the University of São Paulo (Poli-USP). His research focuses on Artificial Intelligence and Optimization, including multi-objective optimization, metaheuristics, multi-agent systems, large language models, machine learning, cloud task scheduling, and Software Engineering. He is a member of the THUS the Future initiative (Techno-Human Systems of the Future Foundations in Artificial Intelligence, Control, and Computing), affiliated with the USP-CNRS International Research Center, with particular involvement in the CHAINS project (Sustainable Software Supply Chains).
He holds a PhD in Computer Engineering from the Polytechnic School of the University of São Paulo and completed a one-year visiting doctoral research period at the University of Nottingham. His doctoral research investigated the use of multi-agent systems and social choice theory in the development of hyper-heuristics for multi-objective optimization problems. He holds an MSc in Computer Science from the Federal University of Paraná (UFPR), where he conducted research on multi-objective optimization applied to Software Engineering, and a BSc in Information Systems from the University of Western São Paulo (Unoeste).
He also has industry experience as a data engineer, machine learning engineer, and software developer in Brazilian and US-based companies. At USP, he is also involved in teaching and supervision activities, having taught topics related to Artificial Intelligence, Machine Learning, and Data Science in undergraduate and graduate-level professional programs.
Artificial Intelligence applied to multi-objective cloud workflow scheduling, including heuristics, metaheuristics, hyper-heuristics and language models.
Research on multi-agent systems, social choice theory and hyper-heuristics for multi-objective optimization.
One-year research period at the Computational Optimisation and Learning Lab, during the PhD, focused on hyper-heuristics and real-world optimization problems.
Hyper-heuristics and multi-objective optimization applied to software integration and testing order problems.
Undergraduate education in computing and information systems.