What is she best known for?
The fields of study she is best known for:
- Artificial intelligence
- Programming language
- Statistics
Francesca Rossi mainly focuses on Mathematical optimization, Constraint satisfaction, Constraint programming, Theoretical computer science and Artificial intelligence.
Her research integrates issues of Constraint satisfaction dual problem, Semantic reasoner and Scheduling in her study of Mathematical optimization.
Her Constraint satisfaction study necessitates a more in-depth grasp of Constraint.
Francesca Rossi interconnects Computational complexity theory, Semantics, Preference and Time complexity in the investigation of issues within Theoretical computer science.
Her work carried out in the field of Artificial intelligence brings together such families of science as Condorcet method, Approval voting, Bullet voting and Cardinal voting systems.
Her Constraint logic programming study typically links adjacent topics like Local consistency.
Her most cited work include:
- Handbook of Constraint Programming (1017 citations)
- Semiring-based constraint satisfaction and optimization (611 citations)
- Algebraic approaches to graph transformation. Part I: basic concepts and double pushout approach (437 citations)
What are the main themes of her work throughout her whole career to date?
Francesca Rossi mainly investigates Mathematical optimization, Artificial intelligence, Constraint, Theoretical computer science and Constraint satisfaction.
Her studies deal with areas such as Preference, Matching, Constraint satisfaction dual problem, Local consistency and Fuzzy logic as well as Mathematical optimization.
Her studies in Artificial intelligence integrate themes in fields like Machine learning, Preference and Set.
Francesca Rossi combines subjects such as Computational complexity theory and Set with her study of Theoretical computer science.
Her research in Constraint satisfaction intersects with topics in Constraint programming and Constraint satisfaction problem.
Her research in Constraint programming is mostly concerned with Concurrent constraint logic programming.
She most often published in these fields:
- Mathematical optimization (28.75%)
- Artificial intelligence (16.61%)
- Constraint (16.61%)
What were the highlights of her more recent work (between 2016-2020)?
- Set (7.67%)
- Artificial intelligence (16.61%)
- Management science (5.43%)
In recent papers she was focusing on the following fields of study:
Francesca Rossi mainly investigates Set, Artificial intelligence, Management science, Machine learning and Mathematical optimization.
The Set study combines topics in areas such as Test, Agency and Reinforcement learning.
In general Artificial intelligence study, her work on Ai systems often relates to the realm of Upper and lower bounds, thereby connecting several areas of interest.
Her Management science research is multidisciplinary, incorporating elements of Complex system, Multi-agent system and Decision theory.
As a part of the same scientific study, Francesca Rossi usually deals with the Machine learning, concentrating on Classifier and frequently concerns with Ranking.
Her study focuses on the intersection of Mathematical optimization and fields such as Matching with connections in the field of Structure and Group.
Between 2016 and 2020, her most popular works were:
- Using Contextual Bandits with Behavioral Constraints for Constrained Online Movie Recommendation. (29 citations)
- Preferences and Ethical Principles in Decision Making (19 citations)
- Incorporating Behavioral Constraints in Online AI Systems (18 citations)
In her most recent research, the most cited papers focused on:
- Artificial intelligence
- Programming language
- Statistics
Her main research concerns Set, Management science, Formalism, Ai systems and Theoretical computer science.
Her study in Set is interdisciplinary in nature, drawing from both Agency and Artificial intelligence, Reinforcement learning.
The various areas that Francesca Rossi examines in her Artificial intelligence study include Test and Constraint.
Her Management science study combines topics in areas such as Decision theory, Multi-agent system, Knowledge representation and reasoning and Logical reasoning.
Her study in Ai systems is interdisciplinary in nature, drawing from both Regret, Thompson sampling and Extension.
Her Theoretical computer science research includes themes of Leverage and Value.
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