curriculum vitae
Contact Information
| Name | Andrea Brilli |
| Professional Title | PostDoc |
| brilli@diag.uniroma1.it |
Professional Summary
Researcher in Operations Research specialized in nonlinear constrained optimization, active member of the Derivative-Free community. Passionate for solving complex problems and enthusiastic about applying cutting-edge techniques to real-world challenges.
Education
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2021 - 2025 Rome, Italy
Ph.D.
Sapienza, University of Rome
Operations Research
- Curriculum: Operations Research
- Thesis: Derivative-Free Optimization: worst-case complexity for Line-Search methods and a mixed Penalty-Barrier approach
- ABRO (Automatic control, Bioengineering and Operations Research)
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2019 - 2021 Rome, Italy
Master degree
Sapienza, University of Rome
Management Engineering
- Curriculum: Decision Models
- Thesis: An interior penalty method for black-box constrained optimization
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2015 - 2019 Rome, Italy
Bachelor degree
Sapienza, University of Rome
Management Engineering
Experience
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2024 - Rome, Italy
PostDoc
Sapienza University of Rome
Department of Computer, Control and Management Engineering. Funded by PRIN (NextGenerationEU funds) for hydrodynamic optimization study on biomimetic and innovative hydrodynamic configurations for autonomous underwater gliders (AUG), specifically designed for ocean surveying.
- Support to PhD students on advanced techniques for training neural networks and derivative-free techniques
- Collaboration with INESC MN (Lisbon, Portugal) for optimization of structural design parameters of metamaterials
- Collaboration with NOVA University of Lisbon on techniques to approximate the Pareto Front of constrained multiobjective optimization problems
- Collaboration with Polytechnique Montréal to study nonsmooth constrained optimization problems
- Collaboration with University of Florence to enhance performance of Augmented Lagrangian techniques
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2024 - 2024 Montréal, Canada
Ph.D. Visiting Researcher
Polytechnique Montréal
Six months of collaboration with Professor Sébastien Le Digabel and Professor Youssef Diouane to enhance the performance of NOMAD solver.
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2022 - 2023 Lisbon, Portugal
Ph.D. Visiting Researcher
Universidade NOVA de Lisboa
One year of collaboration with Professor Ana Luísa Custódio and Ph.D. Everton Jose da Silva to enhance the performance of the SID-PSM algorithm.
Teaching
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2025 - 2026 Rome, Italy
Mathematical Programming
Sapienza University of Rome
Bachelor degree in Computer Science Engineering
- Introduction to multivariate calculus and mathematical optimization
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2026 - 2026 Rome, Italy
Optimization of Complex Systems
Sapienza University of Rome
Master degree in Industrial Engineering
- Advanced algorithms for nonlinear optimization
Awards
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2025 AIROYoung Dissertation Award
AIROYoung (Italian Operations Research Society)
Yearly award for the best doctoral thesis in Operations Research defended in Italy.
Publications
Published
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2026 Complexity results and active-set identification of a derivative-free method for bound-constrained problems
Journal of Optimization Theory and Applications
Analysis of complexity and active-set identification for derivative-free optimization with bound constraints.
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2025 Tunable ito–metal plasmonic metamaterial channel for tailored sensing: A simulation-driven approach
AIP Advances
Optimization-driven design of plasmonic metamaterial sensors for tailored sensing applications.
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2025 An interior point method for nonlinear constrained derivative-free optimization
Optimization Methods and Software
Novel interior point approach for solving general nonlinear constrained problems without derivatives.
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2026 Nonlinear derivative-free constrained optimization with a penalty-interior point method and direct search
arXiv preprint
Mixed penalty-interior point method combined with direct search for general constrained derivative-free optimization.
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2024 Worst case complexity bounds for linesearch-type derivative-free algorithms
Journal of Optimization Theory and Applications
Theoretical complexity analysis for linesearch-based derivative-free optimization methods.
Preprints
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2026 A penalty-interior point method combined with mads for equality and inequality constrained optimization
arXiv preprint
Novel constraint-handling method combining penalty and interior point approaches with MADS algorithm for nonsmooth problems.
Skills
Languages
Certificates
- Deep Learning Specialization - Coursera (2020)
- Data-driven Astronomy - University of Sydney (2020)
- CyberChallenge 2020 - CINI (Consorzio interuniversitario Nazionale per l'Informatica) (2020)
Projects
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DFL - Derivative-Free Library
Collaborator for the implementation of algorithms in Python within the DFL library. Author of LOG-DFL.
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LOG-DS
Co-author of the LOG-DS algorithm, a direct search method for general nonlinear constrained problems implemented in Matlab.
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NOMAD
A Blackbox Optimization Software. Supported the implementation of new constraint-handling strategies within the package.
References
- Professor Giampaolo Liuzzi
Ph.D. supervisor, Sapienza University of Rome. Email - liuzzi@diag.uniroma1.it
- Professor Stefano Lucidi
Master thesis advisor, Sapienza University of Rome. Email - lucidi@diag.uniroma1.it
- Professor Ana Luísa Custódio
NOVA University of Lisbon. Email - algb@fct.unl.pt
- Professor Sébastien Le Digabel
Polytechnique Montréal. Email - sebastien.le-digabel@polymtl.ca
- Professor Youssef Diouane
Polytechnique Montréal. Email - youssef.diouane@polymtl.ca