جست‌وجوی استاد و پژوهشگر

• Embedded Operating Systems
• Multicore and Reconfigurable Architectures
• Concurrency
• +۴ مورد دیگر

Giovani Gracioli is an Assistant Professor at the Department of Knowledge Engineering, College of Technology, Federal University of Santa Catarina (UFSC), Florianópolis. He is also a member of the Graduate Program in Computer Science and the Software/Hardware Integration Lab (LISHA). His research focuses on Embedded Operating Systems Exploiting multicore and reconfigurable architectures Concurrency and inter-processor synchronization Real-time resource management and scheduling Memory management in RTOS His recent publications emphasize embedded systems and real-time operating systems (RTOS), with studies on interrupt tracing and recording, schedulability analysis for resource access protocols, and the adaptation of systems for multicore architectures. These works align with his broader interests in concurrency, parallelism, and efficient resource management in constrained environments. He actively participates in academic events as a program committee member and organizational chair for conferences like ECRTS, RTSS, and SBESC. For research collaboration or advising opportunities, interested students can contact him via email at giovani@lisha.ufsc.br or phone +55 48 3721-2318.

Marco Molinaroمشاهده پروفایل

استاد

• Online Algorithms
• Convex Optimization
• Machine Learning
• +۵ مورد دیگر

Marco Molinaro is a Professor in the Computer Science Department at PUC-Rio . He previously held Assistant Professor positions at TU Delft (EWI), Georgia Tech (ISyE, ACO), and was a PhD student in the ACO program at Carnegie Mellon University . Education: PhD in Algorithms, Combinatorics, and Optimization (ACO), Carnegie Mellon University Research Interests: Marco's work lies at the intersection of online algorithms , convex optimization , machine learning , and operations research . His recent publications analyze: Online scheduling and VM allocation in data centers Complexity of branch-and-bound trees Information-theoretic bounds for optimization problems Explainable decision trees and their theoretical limits Stochastic and adversarial bandit algorithms Curvature properties in optimization sets His research often bridges abstract mathematical frameworks (e.g., Lipschitz functions, supermodular norms) with practical applications in cloud computing, machine learning, and game theory. Publication Trends: Marco's recent work focuses on online convex optimization and its extensions to data center resource allocation (Kamino: latency-driven VM scheduling), dynamic bin packing , and information complexity in mixed-integer models. He frequently collaborates with researchers at institutions like Carnegie Mellon University and TU Delft, with recurring co-authors Santanu Dey, Amitabh Basu, and Thomas Kesselheim. Teaching: Marco teaches advanced courses in algorithm design and analysis at PUC-Rio, including: Analise de Algoritmos (2020–2025) Projeto e Analise de Algoritmos (postgraduate, 2020–2025) Algoritmos e Incerteza (postgraduate, 2020) Estruturas Discretas (2021) His curriculum emphasizes online learning , random-order models , and PAC learning , with connections to game theory and practical implementations.