2022-2023: postdoc at Aalto University, (Espoo, Finland) In prof. Jukka Suomela's team
2023-2025: postdoc at Bocconi University (Milan, Italy) in prof. Luca Trevisan's team
2025-ongoing: international postodctoral researchet at Gran Sasso Science Institute (L'Aquila, Italy).
EDUCATION
2013-2019 B.Sc. and M.Sc. in Mathematics at University of Rome "La Sapienza" (Rome, Italy).
2019-2022 P.h.D. in Computer Science at Inria Sophia Antipolis & Université Côte d'Azur (Sophia Antipolis, France).
RESEARCH, TEACHING, or OTHER INTERESTS
Theoretical Computer Science, Computational Theory and Mathematics, Computer Networks and Communications, Discrete Mathematics and Combinatorics
16
Scopus Publications
220
Scholar Citations
8
Scholar h-index
7
Scholar i10-index
Scopus Publications
Survival in infants with trisomy 18, palliative care and ethical reflections: a single center considerations Serena Caggiano, Sabrina Persia, Francesco D’Amore, Marina Macchiaiolo, Maria Fornari, Vitangelo Clemente, Maria Giovanna Paglietti, Alessandra Schiavino, Gianfranco Butera, Sergio Filippelli, Luigi Zucaro, Renato Cutrera Italian Journal of Pediatrics, 2026 BACKGROUND: Trisomy 18 was once considered a fatal diagnosis due to the presence of cardiac and extracardiac lesions. However, with the increasing use of therapeutic management, 3% to 25% of infants with trisomy 18 may survive beyond their first year, depending on the interventions provided. Currently, there are no clear and widely accepted criteria to guide medical decisions for children with trisomy 18. This means that patients could often be at risk of either over-treatment or therapeutic abandonment. We aimed to explore the effectiveness of intensive and non-intensive treatments in enhancing the clinical burden of disease and survival of children with trisomy 18 syndrome METHODS: a retrospective monocentric study in Bambino Gesù Children’s Hospital, IRCCS Rome, Italy. We enrolled all patients discharged from our hospital with genetic diagnosis of trisomy 18 between 2018 and 2023. Clinical data from birth were collected and categorized into two groups: those who received intensive treatment and those who underwent a palliative approach. Intensive treatment was defined as corrective heart surgery, use of invasive respiratory support, or at least one hospitalization in an intensive care unit. Survival probabilities at different age intervals were calculated, and the clinical burden of disease was assessed, taking into account device dependence, number of emergency department visits per year, and the daily intake of medications at home RESULTS: 32 patients were enrolled. Children with a low device dependence had significantly higher survival(p= 0,01). Neither palliative nor corrective heart surgery affected survival for patients with major cardiac defects. Conversely in children with minor heart defects surgery significantly increased survival probability(p= 0.01), particularly the corrective approach(p= 0.01). High number of emergency department visits(p=0.03) and high number of drugs taken daily(p=0.02) significantly reduced survival. No significant differences emerged between the two groups in terms of burden of disease. CONCLUSIONS: proportional to the initial clinical conditions all treatment options, which may include both comfort care and heart surgery, should be re-evaluated to determine the approach that prioritizes the best interest of each child with trisomy 18.
Distributed Quantum Advantage in Locally Checkable Labeling Problems Alkida Balliu, Filippo Casagrande, Francesco d’Amore, Massimo Equi, Barbara Keller, Henrik Lievonen, Dennis Olivetti, Gustav Schmid, Jukka Suomela Proceedings of the Annual ACM SIAM Symposium on Discrete Algorithms, 2026 In this paper, we present the first known example of a locally checkable labeling problem (LCL) that admits asymptotic distributed quantum advantage in the LOCAL model of distributed computing: our problem can be solved in \(O(\log n)\) communication rounds in the quantum-LOCAL model, but it requires \(\Omega(\log n \cdot \log^{0.99}\log n)\) communication rounds in the classical randomized-LOCAL model.
Online Locality Meets Distributed Quantum Computing Amirreza Akbari, Xavier Coiteux-Roy, Francesco d'Amore, François Le Gall, Henrik Lievonen, Darya Melnyk, Augusto Modanese, Shreyas Pai, Marc-Olivier Renou, Václav Rozhoň, Jukka Suomela Proceedings of the Annual ACM Symposium on Theory of Computing, 2025 We connect three distinct lines of research that have recently explored extensions of the classical LOCAL model of distributed computing: A. distributed quantum computing and non-signaling distributions [e.g. STOC 2024], B. finitely-dependent processes [e.g. Forum Math. Pi 2016], and C. locality in online graph algorithms and dynamic graph algorithms [e.g. ICALP 2023]. We prove new results on the capabilities and limitations of all of these models of computing, for locally checkable labeling problems (LCLs). We show that all these settings can be sandwiched between the classical LOCAL model and what we call the randomized online-LOCAL model. Our work implies limitations on the quantum advantage in the distributed setting, and we also exhibit a new barrier for proving tighter bounds. Our main technical results are these: (1) All LCL problems solvable with locality O(log⋆n) in the classical deterministic LOCAL model admit a finitely-dependent distribution with locality O(1). This answers an open question by Holroyd [2024], and also presents a new barrier for proving bounds on distributed quantum advantage using causality-based arguments. (2) In rooted trees, if we can solve an LCL problem with locality o(logloglogn) in the randomized online-LOCAL model (or any of the weaker models, such as quantum-LOCAL), we can solve it with locality O(log⋆n) in the classical deterministic LOCAL model. One of many implications is that in rooted trees, O(log⋆n) locality in quantum-LOCAL is not stronger than O(log⋆n) locality in classical LOCAL.
Distributed Quantum Advantage for Local Problems Alkida Balliu, Sebastian Brandt, Xavier Coiteux-Roy, Francesco d'Amore, Massimo Equi, François Le Gall, Henrik Lievonen, Augusto Modanese, Dennis Olivetti, Marc-Olivier Renou, Jukka Suomela, Lucas Tendick, Isadora Veeren Proceedings of the Annual ACM Symposium on Theory of Computing, 2025 We present the first local problem that shows a super-constant separation between the classical randomized LOCAL model of distributed computing and its quantum counterpart. By prior work, such a separation was known only for an artificial graph problem with an inherently global definition [Le Gall et al. 2019]. We present a problem that we call iterated GHZ, which is defined using only local constraints. Formally, it is a family of locally checkable labeling problems [Naor and Stockmeyer 1995]; in particular, solutions can be verified with a constant-round distributed algorithm. We show that in graphs of maximum degree Δ, any classical (deterministic or randomized) LOCAL model algorithm will require Ω(Δ) rounds to solve the iterated GHZ problem, while the problem can be solved in 1 round in quantum-LOCAL. We use the round elimination technique to prove that the iterated GHZ problem requires Ω(Δ) rounds for classical algorithms. This is the first work that shows that round elimination is indeed able to separate the two models, and this also demonstrates that round elimination cannot be used to prove lower bounds for quantum-LOCAL. To apply round elimination, we introduce a new technique that allows us to discover appropriate problem relaxations in a mechanical way; it turns out that this new technique extends beyond the scope of the iterated GHZ problem and can be used to e.g. reproduce prior results on maximal matchings [FOCS 2019, PODC 2020] in a systematic manner.
Phase transition of the 3-majority opinion dynamics with noisy interactions Francesco d'Amore, Isabella Ziccardi Theoretical Computer Science, 2025 Communication noise is a common feature in several real-world scenarios where systems of agents need to communicate in order to pursue some collective task. Indeed, many biologically inspired systems that try to achieve agreements on some opinion must implement resilient dynamics, i.e. that are not strongly affected by noisy communications. In this work, we study the 3-Majority dynamics, an opinion dynamics that has been shown to be an efficient protocol for the majority consensus problem, in which we introduce a simple feature of uniform communication noise, following D'Amore et al. (2022). We prove that, in the fully connected communication network of n agents and in the binary opinion case, the process induced by the 3-Majority dynamics exhibits a phase transition. For a noise probability p < 1 / 3 , the dynamics reach in logarithmic time an almost-consensus metastable phase which lasts for a polynomial number of rounds with high probability. We characterize this phase by showing that there exists an attractive equilibrium value s eq ∈ [ n ] for the bias of the system, i.e. the difference between the majority community size and the minority one. Moreover, we show that the agreement opinion is the initial majority one if the bias towards it is of magnitude Ω ( n log n ) in the initial configuration. If, instead, p > 1 / 3 , we show that no form of consensus is possible, and any information regarding the initial majority opinion is lost in logarithmic time with high probability. Despite more communications per-round being allowed, the 3-Majority dynamics surprisingly turns out to be less resilient to noise than the Undecided-State dynamics, whose noise threshold value is p = 1 / 2 .
On the h-Majority Dynamics with Many Opinions d'Amore, Francesco, D'Archivio, Niccolò, Giakkoupis, George, Natale, Emanuele Leibniz International Proceedings in Informatics Lipics, 2025 We present the first upper bound on the convergence time to consensus of the well-known h-majority dynamics with k opinions, in the synchronous setting, for h and k that are both non-constant values. We suppose that, at the beginning of the process, there is some initial additive bias towards some plurality opinion, that is, there is an opinion that is supported by x nodes while any other opinion is supported by strictly fewer nodes. We prove that, with high probability, if the bias is ω(√x) and the initial plurality opinion is supported by at least x = ω(log n) nodes, then the process converges to plurality consensus in O(log n) rounds whenever h = ω(n log n / x). A main corollary is the following: if k = o(n / log n) and the process starts from an almost-balanced configuration with an initial bias of magnitude ω(√{n/k}) towards the initial plurality opinion, then any function h = ω(k log n) suffices to guarantee convergence to consensus in O(log n) rounds, with high probability. Our upper bound shows that the lower bound of Ω(k / h²) rounds to reach consensus given by Becchetti et al. (2017) cannot be pushed further than Ω̃(k / h). Moreover, the bias we require is asymptotically smaller than the Ω(√{nlog n}) bias that guarantees plurality consensus in the 3-majority dynamics: in our case, the required bias is at most any (arbitrarily small) function in ω(√x) for any value of k ≥ 2.
New Limits on Distributed Quantum Advantage: Dequantizing Linear Programs Alkida Balliu, Corinna Coupette, Cruciani, Antonio, Francesco d’Amore, Massimo Equi, et al. Leibniz International Proceedings in Informatics Lipics, 2025 In this work, we give two results that put new limits on distributed quantum advantage in the context of the LOCAL model of distributed computing: 1) We show that there is no distributed quantum advantage for any linear program. Put otherwise, if there is a quantum-LOCAL algorithm 𝒜 that finds an α-approximation of some linear optimization problem Π in T communication rounds, we can construct a classical, deterministic LOCAL algorithm 𝒜' that finds an α-approximation of Π in T rounds. As a corollary, all classical lower bounds for linear programs, including the KMW bound, hold verbatim in quantum-LOCAL. 2) Using the above result, we show that there exists a locally checkable labeling problem (LCL) for which quantum-LOCAL is strictly weaker than the classical deterministic SLOCAL model. Our results extend from quantum-LOCAL to finitely dependent and non-signaling distributions, and one of the corollaries of our work is that the non-signaling model and the SLOCAL model are incomparable in the context of LCL problems: By prior work, there exists an LCL problem for which SLOCAL is strictly weaker than the non-signaling model, and our work provides a separation in the opposite direction.
No Distributed Quantum Advantage for Approximate Graph Coloring Xavier Coiteux-Roy, Francesco d'Amore, Rishikesh Gajjala, Fabian Kuhn, François Le Gall, Henrik Lievonen, Augusto Modanese, Marc-Olivier Renou, Gustav Schmid, Jukka Suomela Proceedings of the Annual ACM Symposium on Theory of Computing, 2024 We give an almost complete characterization of the hardness of c-coloring χ-chromatic graphs with distributed algorithms, for a wide range of models of distributed computing. In particular, we show that these problems do not admit any distributed quantum advantage. To do that: We give a new distributed algorithm that finds a c-coloring in χ-chromatic graphs in Õ(n1/α) rounds, with α = ⌊c−1/χ − 1⌋. We prove that any distributed algorithm for this problem requires Ω(n1/α) rounds. Our upper bound holds in the classical, deterministic LOCAL model, while the near-matching lower bound holds in the non-signaling model. This model, introduced by Arfaoui and Fraigniaud in 2014, captures all models of distributed graph algorithms that obey physical causality; this includes not only classical deterministic LOCAL and randomized LOCAL but also quantum-LOCAL, even with a pre-shared quantum state. We also show that similar arguments can be used to prove that, e.g., 3-coloring 2-dimensional grids or c-coloring trees remain hard problems even for the non-signaling model, and in particular do not admit any quantum advantage. Our lower-bound arguments are purely graph-theoretic at heart; no background on quantum information theory is needed to establish the proofs.
Brief Announcement: Distributed Derandomization Revisited Sameep Dahal, Francesco d’Amore, Henrik Lievonen, Timothé Picavet, Jukka Suomela Leibniz International Proceedings in Informatics Lipics, 2023 One of the cornerstones of the distributed complexity theory is the derandomization result by Chang, Kopelowitz, and Pettie [FOCS 2016]: any randomized LOCAL algorithm that solves a locally checkable labeling problem (LCL) can be derandomized with at most exponential overhead. The original proof assumes that the number of random bits is bounded by some function of the input size. We give a new, simple proof that does not make any such assumptions-it holds even if the randomized algorithm uses infinitely many bits. While at it, we also broaden the scope of the result so that it is directly applicable far beyond LCL problems.
Revisiting the Random Subset Sum Problem A. D. Cunha, Francesco d’Amore, F. Giroire, Hicham Lesfari, Emanuele Natale, L. Viennot Leibniz International Proceedings in Informatics Lipics, 2023 The average properties of the well-known Subset Sum Problem can be studied by the means of its randomised version, where we are given a target value $z$, random variables $X_1, \\ldots, X_n$, and an error parameter $\\varepsilon>0$, and we seek a subset of the $X_i$s whose sum approximates $z$ up to error $\\varepsilon$. In this setup, it has been shown that, under mild assumptions on the distribution of the random variables, a sample of size $\\mathcal{O}(\\log(1/\\varepsilon))$ suffices to obtain, with high probability, approximations for all values in $[-1/2, 1/2]$. Recently, this result has been rediscovered outside the algorithms community, enabling meaningful progress in other fields. In this work we present an alternative proof for this theorem, with a more direct approach and resourcing to more elementary tools.
Polynomially Over-Parameterized Convolutional Neural Networks Contain Structured Strong Winning Lottery Tickets Advances in Neural Information Processing Systems, 2023
Planning with Biological Neurons and Synapses Francesco D'Amore, Daniel Mitropolsky, Pierluigi Crescenzi, Emanuele Natale, Christos H. Papadimitriou Proceedings of the 36th Aaai Conference on Artificial Intelligence Aaai 2022, 2022
Search via Parallel Lévy Walks on Z2 Andrea Clementi, Francesco d'Amore, George Giakkoupis, Emanuele Natale Proceedings of the Annual ACM Symposium on Principles of Distributed Computing, 2021
Brief Announcement: DéjàVu: A Minimalistic Mechanism for Distributed Plurality Consensus F d'Amore, ND Archivio, G Giakkoupis, F Giroire, E Natale PODC 2026-ACM Symposium on Principles of Distributed Computing , 2026 2026
DéjàVu: A Minimalistic Mechanism for Distributed Plurality Consensus F d'Amore, N d'Archivio, G Giakkoupis, F Giroire, E Natale arXiv preprint arXiv:2604.03648 , 2026 2026 Citations: 1
Survival in infants with trisomy 18, palliative care and ethical reflections: a single center considerations S Caggiano, S Persia, F D’Amore, M Macchiaiolo, M Fornari, V Clemente, ... Italian Journal of Pediatrics , 2026 2026
Distributed quantum advantage in locally checkable labeling problems A Balliu, F Casagrande, F d’Amore, M Equi, B Keller, H Lievonen, ... Proceedings of the 2026 Annual ACM-SIAM Symposium on Discrete Algorithms … , 2026 2026 Citations: 6
New Hardness Results for the LOCAL Model via a Simple Self-Reduction A Balliu, F Casagrande, F d'Amore, D Olivetti arXiv preprint arXiv:2510.19972 , 2025 2025
Distributed Algorithms for Potential Problems A Balliu, T Boudier, F d'Amore, F Kuhn, D Olivetti, G Schmid, J Suomela arXiv preprint arXiv:2507.12038 , 2025 2025
On the -majority dynamics with many opinions F d'Amore, N d'Archivio, G Giakkoupis, E Natale arXiv preprint arXiv:2506.20218 , 2025 2025 Citations: 4
Distributed quantum advantage for local problems A Balliu, S Brandt, X Coiteux-Roy, F d'Amore, M Equi, F Le Gall, ... Proceedings of the 57th Annual ACM Symposium on Theory of Computing, 451-462 , 2025 2025 Citations: 22
Online locality meets distributed quantum computing A Akbari, X Coiteux-Roy, F d'Amore, F Le Gall, H Lievonen, D Melnyk, ... Proceedings of the 57th Annual ACM Symposium on Theory of Computing, 1295-1306 , 2025 2025 Citations: 34
New limits on distributed quantum advantage: Dequantizing linear programs A Balliu, C Coupette, A Cruciani, F d'Amore, M Equi, H Lievonen, ... arXiv preprint arXiv:2506.07574 , 2025 2025 Citations: 6
On the limits of distributed quantum computing F d'Amore arXiv preprint arXiv:2503.11394 , 2025 2025 Citations: 3
Phase transition of the 3-majority opinion dynamics with noisy interactions F d'Amore, I Ziccardi Theoretical Computer Science 1028, 115030 , 2025 2025 Citations: 4
No distributed quantum advantage for approximate graph coloring X Coiteux-Roy, F d'Amore, R Gajjala, F Kuhn, F Le Gall, H Lievonen, ... Proceedings of the 56th Annual ACM Symposium on Theory of Computing, 1901-1910 , 2024 2024 Citations: 36
Polynomially Over-Parameterized Convolutional Neural Networks Contain Structured Strong Winning Lottery Tickets A da Cunha, F d'Amore, E Natale Advances in Neural Information Processing Systems 36 , 2024 2024 Citations: 9
Revisiting the Random Subset Sum Problem ACW da Cunha, F d'Amore, F Giroire, H Lesfari, E Natale, L Viennot 31st Annual European Symposium on Algorithms (ESA 2023) 274, 37:1--37:11 , 2023 2023 Citations: 7
Distributed derandomization revisited S Dahal, F d'Amore, H Lievonen, T Picavet, J Suomela arXiv preprint arXiv:2305.07351 , 2023 2023 Citations: 8
On the collective behaviors of bio-inspired distributed systems F d'Amore Université Côte d'Azur , 2022 2022
On the multidimensional random subset sum problem L Becchetti, ACW da Cunha, A Clementi, F d'Amore, H Lesfari, E Natale, ... arXiv preprint arXiv:2207.13944 , 2022 2022 Citations: 5
Planning with biological neurons and synapses F d'Amore, D Mitropolsky, P Crescenzi, E Natale, CH Papadimitriou Proceedings of the AAAI Conference on Artificial Intelligence 36 (1), 21-28 , 2022 2022 Citations: 12
Phase transition of the 3-majority dynamics with uniform communication noise F d’Amore, I Ziccardi International Colloquium on Structural Information and Communication … , 2022 2022 Citations: 14
MOST CITED SCHOLAR PUBLICATIONS
No distributed quantum advantage for approximate graph coloring X Coiteux-Roy, F d'Amore, R Gajjala, F Kuhn, F Le Gall, H Lievonen, ... Proceedings of the 56th Annual ACM Symposium on Theory of Computing, 1901-1910 , 2024 2024 Citations: 36
Online locality meets distributed quantum computing A Akbari, X Coiteux-Roy, F d'Amore, F Le Gall, H Lievonen, D Melnyk, ... Proceedings of the 57th Annual ACM Symposium on Theory of Computing, 1295-1306 , 2025 2025 Citations: 34
Phase transition of a non-linear opinion dynamics with noisy interactions F d’Amore, A Clementi, E Natale International Colloquium on Structural Information and Communication … , 2020 2020 Citations: 26
Search via Parallel Lévy Walks on Z^2 A Clementi, F d'Amore, G Giakkoupis, E Natale Proceedings of the 2021 ACM Symposium on Principles of Distributed Computing … , 2021 2021 Citations: 23
Distributed quantum advantage for local problems A Balliu, S Brandt, X Coiteux-Roy, F d'Amore, M Equi, F Le Gall, ... Proceedings of the 57th Annual ACM Symposium on Theory of Computing, 451-462 , 2025 2025 Citations: 22
Phase transition of the 3-majority dynamics with uniform communication noise F d’Amore, I Ziccardi International Colloquium on Structural Information and Communication … , 2022 2022 Citations: 14
Planning with biological neurons and synapses F d'Amore, D Mitropolsky, P Crescenzi, E Natale, CH Papadimitriou Proceedings of the AAAI Conference on Artificial Intelligence 36 (1), 21-28 , 2022 2022 Citations: 12
Polynomially Over-Parameterized Convolutional Neural Networks Contain Structured Strong Winning Lottery Tickets A da Cunha, F d'Amore, E Natale Advances in Neural Information Processing Systems 36 , 2024 2024 Citations: 9
Distributed derandomization revisited S Dahal, F d'Amore, H Lievonen, T Picavet, J Suomela arXiv preprint arXiv:2305.07351 , 2023 2023 Citations: 8
Revisiting the Random Subset Sum Problem ACW da Cunha, F d'Amore, F Giroire, H Lesfari, E Natale, L Viennot 31st Annual European Symposium on Algorithms (ESA 2023) 274, 37:1--37:11 , 2023 2023 Citations: 7
Distributed quantum advantage in locally checkable labeling problems A Balliu, F Casagrande, F d’Amore, M Equi, B Keller, H Lievonen, ... Proceedings of the 2026 Annual ACM-SIAM Symposium on Discrete Algorithms … , 2026 2026 Citations: 6
New limits on distributed quantum advantage: Dequantizing linear programs A Balliu, C Coupette, A Cruciani, F d'Amore, M Equi, H Lievonen, ... arXiv preprint arXiv:2506.07574 , 2025 2025 Citations: 6
On the multidimensional random subset sum problem L Becchetti, ACW da Cunha, A Clementi, F d'Amore, H Lesfari, E Natale, ... arXiv preprint arXiv:2207.13944 , 2022 2022 Citations: 5
On the -majority dynamics with many opinions F d'Amore, N d'Archivio, G Giakkoupis, E Natale arXiv preprint arXiv:2506.20218 , 2025 2025 Citations: 4
Phase transition of the 3-majority opinion dynamics with noisy interactions F d'Amore, I Ziccardi Theoretical Computer Science 1028, 115030 , 2025 2025 Citations: 4
On the limits of distributed quantum computing F d'Amore arXiv preprint arXiv:2503.11394 , 2025 2025 Citations: 3
DéjàVu: A Minimalistic Mechanism for Distributed Plurality Consensus F d'Amore, N d'Archivio, G Giakkoupis, F Giroire, E Natale arXiv preprint arXiv:2604.03648 , 2026 2026 Citations: 1
Brief Announcement: DéjàVu: A Minimalistic Mechanism for Distributed Plurality Consensus F d'Amore, ND Archivio, G Giakkoupis, F Giroire, E Natale PODC 2026-ACM Symposium on Principles of Distributed Computing , 2026 2026
Survival in infants with trisomy 18, palliative care and ethical reflections: a single center considerations S Caggiano, S Persia, F D’Amore, M Macchiaiolo, M Fornari, V Clemente, ... Italian Journal of Pediatrics , 2026 2026
New Hardness Results for the LOCAL Model via a Simple Self-Reduction A Balliu, F Casagrande, F d'Amore, D Olivetti arXiv preprint arXiv:2510.19972 , 2025 2025
