2023 - Research.com Computer Science in Italy Leader Award
2007 - Fellow of the International Federation of Automatic Control (IFAC)
Roberto Tempo mainly investigates Randomized algorithm, Mathematical optimization, Robustness, Probabilistic logic and Control theory. His Randomized algorithm research incorporates themes from Theoretical computer science, PageRank, Probabilistic analysis of algorithms, Iterative method and Topology. His Mathematical optimization research includes elements of Convex optimization, Linear system, Exponential stability, Control theory and System identification.
His Robustness research is multidisciplinary, incorporating perspectives in Control system, Bounded function, Stability and Probabilistic method. His biological study spans a wide range of topics, including Norm, Probability density function, Sample size determination and Nonlinear system. His Control theory study integrates concerns from other disciplines, such as Extreme point and Nyquist stability criterion.
Roberto Tempo focuses on Mathematical optimization, Randomized algorithm, Probabilistic logic, Robustness and Algorithm. Roberto Tempo interconnects Convex optimization, Computational complexity theory, Estimation theory, Applied mathematics and System identification in the investigation of issues within Mathematical optimization. His studies in Randomized algorithm integrate themes in fields like Theoretical computer science, Lyapunov function, Randomized algorithms as zero-sum games, Artificial intelligence and Monte Carlo method.
The Theoretical computer science study combines topics in areas such as Distributed algorithm, Web page and Search engine. His Probabilistic logic research incorporates themes from Uncertain systems, Probabilistic-based design optimization and Nonlinear system. Roberto Tempo focuses mostly in the field of Robustness, narrowing it down to topics relating to Bounded function and, in certain cases, Norm.
His primary areas of study are Mathematical optimization, Probabilistic logic, Randomized algorithm, Robustness and Theoretical computer science. His Mathematical optimization research is multidisciplinary, incorporating perspectives in Convex optimization, Control theory, Nonlinear system, Sampling and Strongly connected component. His work on Probabilistic analysis of algorithms as part of general Probabilistic logic study is frequently linked to Convexity, bridging the gap between disciplines.
His Randomized algorithm study is associated with Algorithm. His biological study focuses on Robust control. His Theoretical computer science study combines topics from a wide range of disciplines, such as Social network, Asynchronous communication and Complex network.
Roberto Tempo spends much of his time researching Mathematical optimization, Randomized algorithm, Social network, Robustness and Theoretical computer science. His Mathematical optimization research is multidisciplinary, relying on both Sampling, Convex function, Probabilistic logic, Convex optimization and Constraint satisfaction. His research on Randomized algorithm concerns the broader Algorithm.
The various areas that Roberto Tempo examines in his Social network study include Terminal, Multi-agent system, Gossip, Social group and Complex network. In the subject of general Robustness, his work in Robust control is often linked to Quantization, thereby combining diverse domains of study. Roberto Tempo works mostly in the field of Theoretical computer science, limiting it down to topics relating to Centrality and, in certain cases, Communications protocol, Distributed computing and Closeness.
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Randomized Algorithms for Analysis and Control of Uncertain Systems: With Applications
Roberto Tempo;Giuseppe Calafiore;Fabrizio Dabbene.
(2012)
Randomized Algorithms for Analysis and Control of Uncertain Systems
Roberto Tempo;Giuseppe Calafiore;Fabrizio Dabbene.
(2004)
A tutorial on modeling and analysis of dynamic social networks. Part I
Anton V. Proskurnikov;Anton V. Proskurnikov;Anton V. Proskurnikov;Roberto Tempo.
Annual Reviews in Control (2017)
Probabilistic robustness analysis: explicit bounds for the minimum number of samples
R. Tempo;E. W. Bai;F. Dabbene.
Systems & Control Letters (1997)
Optimal algorithms theory for robust estimation and prediction
M. Milanese;R. Tempo.
IEEE Transactions on Automatic Control (1985)
Network science on belief system dynamics under logic constraints
Noah E. Friedkin;Anton V. Proskurnikov;Anton V. Proskurnikov;Roberto Tempo;Sergey E. Parsegov.
Science (2016)
Extreme point results for robust stabilization of interval plants with first-order compensators
B.R. Barmish;C.V. Hollot;F.J. Kraus;R. Tempo.
IEEE Transactions on Automatic Control (1992)
Novel Multidimensional Models of Opinion Dynamics in Social Networks
Sergey E. Parsegov;Anton V. Proskurnikov;Roberto Tempo;Noah E. Friedkin.
IEEE Transactions on Automatic Control (2017)
Survey paper: Research on probabilistic methods for control system design
Giuseppe C. Calafiore;Fabrizio Dabbene;Roberto Tempo.
Automatica (2011)
Probabilistic robust design with linear quadratic regulators
Boris T. Polyak;Roberto Tempo.
Systems & Control Letters (2001)
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