Davide Venturelli

2.7k total citations · 1 hit paper
43 papers, 1.4k citations indexed

About

Davide Venturelli is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Davide Venturelli has authored 43 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Artificial Intelligence, 12 papers in Computational Theory and Mathematics and 9 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Davide Venturelli's work include Quantum Computing Algorithms and Architecture (36 papers), Quantum Information and Cryptography (20 papers) and Machine Learning and Algorithms (5 papers). Davide Venturelli is often cited by papers focused on Quantum Computing Algorithms and Architecture (36 papers), Quantum Information and Cryptography (20 papers) and Machine Learning and Algorithms (5 papers). Davide Venturelli collaborates with scholars based in United States, Canada and Japan. Davide Venturelli's co-authors include Eleanor Rieffel, Bryan O’Gorman, Rupak Biswas, Stuart Hadfield, Zhihui Wang, Vadim Smelyanskiy, Salvatore Mandrà, Jeremy Frank, N. Minh and Sergey Knysh and has published in prestigious journals such as Physical Review B, Science Advances and IEEE Transactions on Wireless Communications.

In The Last Decade

Davide Venturelli

42 papers receiving 1.3k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

From the Quantum Approximate Optimization Algorithm to a Quantum Alternating Operator Ansatz

2019 431 citations Stuart Hadfield, Zhihui Wang et al. profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Davide Venturelli	1.2k	390	309	193	79	43	1.4k
Bryan O’Gorman	1.0k 0.8×	315 0.8×	339 1.1×	121 0.6×	72 0.9×	23	1.2k
Martin Roetteler	1.1k 0.9×	392 1.0×	508 1.6×	197 1.0×	60 0.8×	49	1.3k
Iordanis Kerenidis	1.3k 1.0×	350 0.9×	599 1.9×	96 0.5×	60 0.8×	71	1.5k
Alex Bocharov	815 0.7×	209 0.5×	241 0.8×	129 0.7×	79 1.0×	15	964
Vojtěch Havlíček	1.2k 1.0×	240 0.6×	403 1.3×	143 0.7×	35 0.4×	17	1.4k
Rudy Raymond	671 0.5×	140 0.4×	238 0.8×	78 0.4×	79 1.0×	64	849
Jozef Gruska	767 0.6×	672 1.7×	228 0.7×	75 0.4×	38 0.5×	64	1.1k
Tomohiro Sonobe	756 0.6×	119 0.3×	133 0.4×	294 1.5×	36 0.5×	6	919
Miklós Sántha	1.0k 0.8×	665 1.7×	237 0.8×	72 0.4×	103 1.3×	68	1.2k
Muyuan Li	548 0.4×	93 0.2×	215 0.7×	227 1.2×	67 0.8×	28	824

Countries citing papers authored by Davide Venturelli

Since Specialization

Citations

This map shows the geographic impact of Davide Venturelli's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Davide Venturelli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Davide Venturelli more than expected).

Fields of papers citing papers by Davide Venturelli

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Davide Venturelli. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Davide Venturelli. The network helps show where Davide Venturelli may publish in the future.

Co-authorship network of co-authors of Davide Venturelli

This figure shows the co-authorship network connecting the top 25 collaborators of Davide Venturelli. A scholar is included among the top collaborators of Davide Venturelli based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Davide Venturelli. Davide Venturelli is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Biamonte, Jacob, et al.. (2025). Improving Quantum Approximate Optimization by Noise-Directed Adaptive Remapping. Quantum. 9. 1906–1906. 1 indexed citations

Wudarski, Filip, et al.. (2025). Benchmarking the operation of quantum heuristics and Ising machines: scoring parameter setting strategies on optimization applications. Quantum Machine Intelligence. 7(2). 86–86. 1 indexed citations

Dupont, Maxime, et al.. (2024). A Multilevel Approach for Solving Large-Scale QUBO Problems with Noisy Hybrid Quantum Approximate Optimization. 1–10. 2 indexed citations

Hadfield, Stuart, Maxime Dupont, M. Sohaib Alam, et al.. (2024). Design and execution of quantum circuits using tens of superconducting qubits and thousands of gates for dense Ising optimization problems. Physical Review Applied. 22(4). 9 indexed citations

Laird, Carl D., et al.. (2024). Utilizing modern computer architectures to solve mathematical optimization problems: A survey. Computers & Chemical Engineering. 184. 108627–108627. 3 indexed citations

Venturelli, Davide, et al.. (2024). Uniformly decaying subspaces for error-mitigated quantum computation. Physical review. A. 110(4).

Kim, Minsung, et al.. (2024). Uplink MIMO Detection Using Ising Machines: A Multi-Stage Ising Approach. IEEE Transactions on Wireless Communications. 23(11). 17037–17053. 3 indexed citations

Bernal, David E., et al.. (2024). A Copositive Framework for Analysis of Hybrid Ising-Classical Algorithms. SIAM Journal on Optimization. 34(2). 1455–1489. 1 indexed citations

Trummer, Immanuel & Davide Venturelli. (2024). Leveraging Quantum Computing for Database Index Selection. 14–26. 4 indexed citations

10.

Dupont, Maxime, Bhuvanesh Sundar, Stephen Jeffrey, et al.. (2023). Quantum-enhanced greedy combinatorial optimization solver. Science Advances. 9(45). eadi0487–eadi0487. 23 indexed citations

11.

Pokharel, Bibek, et al.. (2023). Inter-generational comparison of quantum annealers in solving hard scheduling problems. Quantum Information Processing. 22(10). 3 indexed citations

12.

Venturelli, Davide, et al.. (2022). Perturbation-based Formulation of Maximum Likelihood MIMO Detection for Coherent Ising Machines. GLOBECOM 2022 - 2022 IEEE Global Communications Conference. 2523–2528. 6 indexed citations

13.

Kim, Minsung, et al.. (2022). Warm-started quantum sphere decoding via reverse annealing for massive IoT connectivity. 1–14. 9 indexed citations

14.

LaRose, Ryan, Eleanor Rieffel, & Davide Venturelli. (2022). Mixer-phaser Ansätze for quantum optimization with hard constraints. Quantum Machine Intelligence. 4(2). 9 indexed citations

15.

Stollenwerk, Tobias, Bryan O’Gorman, Davide Venturelli, et al.. (2019). Quantum Annealing Applied to De-Conflicting Optimal Trajectories for Air Traffic Management. IEEE Transactions on Intelligent Transportation Systems. 21(1). 285–297. 74 indexed citations

16.

Pokharel, Bibek, Davide Venturelli, & Eleanor Rieffel. (2017). Performance of Quantum Annealers on Hard Scheduling Problems. Bulletin of the American Physical Society. 2017. 1 indexed citations

17.

Hadfield, Stuart, Zhihui Wang, Eleanor Rieffel, et al.. (2017). Quantum Approximate Optimization with Hard and Soft Constraints. 15–21. 24 indexed citations

18.

Tran, Tony, Zhihui Wang, N. Minh, et al.. (2016). Explorations of Quantum-Classical Approaches to Scheduling a Mars Lander Activity Problem. National Conference on Artificial Intelligence. 4 indexed citations

19.

O’Gorman, Bryan, Eleanor Rieffel, N. Minh, Davide Venturelli, & Jeremy Frank. (2016). Comparing planning problem compilation approaches for quantum annealing. The Knowledge Engineering Review. 31(5). 465–474. 2 indexed citations

20.

O’Gorman, Bryan, Eleanor Rieffel, N. Minh, Davide Venturelli, & Jeremy Frank. (2015). Compiling Planning into Quantum Optimization Problems: A Comparative Study. 3 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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