VLDB 2026 Research / reviewers in the wild / expert
Nikolai Sinitsyn
dblp:139/2279
· DBLP profile ↗
2ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Databases, data management, data science and information retrieval · 1Human-computer interaction and ubiquitous computing · 1Theory of computation · 1 · 1 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Quantum Algorithm Implementations for BeginnersabstractAs quantum computers become available to the general public, the need has arisen to train a cohort of quantum programmers, many of whom have been developing classical computer programs for most of their careers. While currently available quantum computers have less than 100 qubits, quantum computing hardware is widely expected to grow in terms of qubit count, quality, and connectivity. This review aims at explaining the principles of quantum programming, which are quite different from classical programming, with straightforward algebra that makes understanding of the underlying fascinating quantum mechanical principles optional. We give an introduction to quantum computing algorithms and their implementation on real quantum hardware. We survey 20 different quantum algorithms, attempting to describe each in a succinct and self-contained fashion. We show how these algorithms can be implemented on IBM’s quantum computer, and in each case, we discuss the results of the implementation with respect to differences between the simulator and the actual hardware runs. This article introduces computer scientists, physicists, and engineers to quantum algorithms and provides a blueprint for their implementations. Abhijith Jayakumar, Adetokunbo Adedoyin, John Ambrosiano, Petr M. Anisimov, William Casper, Gopinath Chennupati, Carleton Coffrin, Hristo N. Djidjev, David Gunter, Satish Karra, Nathan Lemons, Shizeng Lin, Alexander Malyzhenkov, David Mascarenas, Susan M. Mniszewski, Balasubramanya T. Nadiga, Daniel O'Malley, Diane Oyen, Scott Pakin, Lakshman Prasad, Randy Roberts, Phillip Romero, Nandakishore Santhi, Nikolai Sinitsyn, Pieter J. Swart, Jim Wendelberger, Boram Yoon, Richard J. Zamora, Wei Zhu 0011, Stephan J. Eidenbenz, Andreas Bärtschi, Patrick J. Coles, Marc Vuffray, Andrey Y. Lokhov |
ACM Trans. Quantum Comput. | 24 |
| 2013 | Visualization and modeling of structural features of a large organizational email networkabstractThis paper presents findings from a study of the email network of a large scientific research organization, focusing on methods for visualizing and modeling organizational hierarchies within large, complex network datasets. In the first part of the paper, we find that visualization and interpretation of complex organizational network data is facilitated by integration of network data with information on formal organizational divisions and levels. By aggregating and visualizing email traffic between organizational units at various levels, we derive several insights into how large subdivisions of the organization interact with each other and with outside organizations. In the second part of the paper, we propose a power law model for predicting degree distribution of organizational email traffic based on hierarchical relationships between managers and employees. This model considers the influence of global email announcements sent from managers to all employees under their supervision, and the role support staff play in generating email traffic, acting as agents for managers. Benjamin H. Sims, Nikolai Sinitsyn, Stephan J. Eidenbenz |
ASONAM | 2 |