World's Best Scientists 2026 revealed!
Francisco Facchinei

Francisco Facchinei

D-Index & Metrics

Computer Science

D-Index
44
Citations
15186
World Ranking
7387
National Ranking
191

Mathematics

D-Index
44
Citations
15190
World Ranking
1531
National Ranking
41

Overview

Francisco Facchinei is affiliated with Sapienza University of Rome in Italy. Their research spans across several interrelated fields, predominantly in Computer Science, Engineering, and Mathematics. The subfields connected to their work include Computational Mechanics, Artificial Intelligence, Numerical Analysis, Computational Theory and Mathematics, and Epidemiology.

The scientist's research focuses on topics such as Sparse and Compressive Sensing Techniques, Stochastic Gradient Optimization Techniques, Advanced Optimization Algorithms Research, Optimization and Variational Analysis, Complexity and Algorithms in Graphs, as well as Liver Disease and Transplantation and its diagnosis and treatment.

Recent publications by Facchinei demonstrate a concentration on optimization theory and applications. Notable papers include:

  • Asynchronous parallel algorithms for nonconvex optimization, 2020, IRIS Research product catalog (Sapienza University of Rome)
  • Ghost penalties in nonconvex constrained optimization: Diminishing stepsizes and iteration complexity, 2021, Iris (Roma Tre University)
  • Ghost Penalties in Nonconvex Constrained Optimization: Diminishing Stepsizes and Iteration Complexity, 2021, Mathematics of Operations Research
  • Deep Neural Network Regression to Assist Non-Invasive Diagnosis of Portal Hypertension, 2023, Healthcare
  • Diminishing stepsize methods for nonconvex composite problems via ghost penalties: from the general to the convex regular constrained case, 2020, Optimization Methods & Software

Frequent coauthors associated with their work include Vyacheslav Kungurtsev, Gesualdo Scutari, Lorenzo Lampariello, Loris Cannelli, and Federico Baldisseri. This reflects a collaborative approach across multiple research areas within computational optimization and applied problem domains.

The scientist frequently publishes in venues such as IRIS Research product catalog (Sapienza University of Rome), arXiv (Cornell University), Iris (Roma Tre University), Healthcare, and Optimization Methods & Software. These venues align with their multi-disciplinary methodology combining theoretical and applied research.

Best Publications

  • Finite-Dimensional Variational Inequalities and Complementarity Problems

    Francisco Facchinei;Jong-Shi Pang

  • Generalized Nash equilibrium problems

    Francisco Facchinei;Christian Kanzow

  • A semismooth equation approach to the solution of nonlinear complementarity problems

    Tecla De Luca;Francisco Facchinei;Christian Kanzow

  • A smoothing method for mathematical programs with equilibrium constraints

    Francisco Facchinei;Houyuan Jiang;Liqun Qi

  • Convex Optimization, Game Theory, and Variational Inequality Theory

    Gesualdo Scutari;Daniel Palomar;Francisco Facchinei;Jong-shi Pang

  • On generalized Nash games and variational inequalities

    Francisco Facchinei;Andreas Fischer;Veronica Piccialli

  • A New Merit Function For Nonlinear Complementarity Problems And A Related Algorithm

    Francisco Facchinei;João Soares

  • Decomposition by Partial Linearization: Parallel Optimization of Multi-Agent Systems

    Gesualdo Scutari;Francisco Facchinei;Peiran Song;Daniel P. Palomar

  • Parallel and Distributed Methods for Constrained Nonconvex Optimization—Part I: Theory

    Gesualdo Scutari;Francisco Facchinei;Lorenzo Lampariello

  • Design of Cognitive Radio Systems Under Temperature-Interference Constraints: A Variational Inequality Approach

    Jong-Shi Pang;Gesualdo Scutari;Daniel P Palomar;Francisco Facchinei

  • On the Accurate Identification of Active Constraints

    Francisco Facchinei;Andreas Fischer;Christian Kanzow

  • Distributed Power Allocation With Rate Constraints in Gaussian Parallel Interference Channels

    Jong-Shi Pang;G. Scutari;F. Facchinei;Chaoxiong Wang

  • A game-theoretic approach to computation offloading in mobile cloud computing

    Valeria Cardellini;Vittoria De Nitto Personé;Valerio Di Valerio;Francisco Facchinei

  • Real and Complex Monotone Communication Games

    Gesualdo Scutari;Francisco Facchinei;Jong-Shi Pang;Daniel P. Palomar

  • A nonsmooth inexact Newton method for the solution of large-scale nonlinear complementarity problems

    Francisco Facchinei;Christian Kanzow

  • Nash equilibria: The variational approach

    Francisco Facchinei;Jong Shi Pang

  • Parallel Selective Algorithms for Nonconvex Big Data Optimization

    Francisco Facchinei;Gesualdo Scutari;Simone Sagratella

  • Penalty Methods for the Solution of Generalized Nash Equilibrium Problems

    Francisco Facchinei;Christian Kanzow

  • Quadratically and superlinearly convergent algorithms for the solution of inequality constrained minimization problems

    F. Facchinei;S. Lucidi

  • Generalized Nash equilibrium problems and Newton methods

    Francisco Facchinei;Andreas Fischer;Veronica Piccialli

Frequent Co-Authors

Gesualdo Scutari
Gesualdo Scutari Purdue University West Lafayette
Jong-Shi Pang
Jong-Shi Pang University of Southern California
Christian Kanzow
Christian Kanzow University of Würzburg
Roberto Cominetti
Roberto Cominetti Adolfo Ibáñez University
Jean B. Lasserre
Jean B. Lasserre Laboratory for Analysis and Architecture of Systems
Daniel P. Palomar
Daniel P. Palomar Hong Kong University of Science and Technology
Stefano Lucidi
Stefano Lucidi Sapienza University of Rome
Brian M. Sadler
Brian M. Sadler United States Army Research Laboratory
Michael C. Ferris
Michael C. Ferris University of Wisconsin–Madison
Liqun Qi
Liqun Qi Hong Kong Polytechnic University

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