Publications

White papers:

I'm co-author and contributor of two HEP Software Foundation community white papers, see http://hepsoftwarefoundation.org/activities/cwp.html 

Software publications:

Transitioning existing data reduction workflows at the Cornell High Energy Synchrotron Source to Galaxy, Rolf Verberg, Kelly Nygren, Keara Soloway, Valentin Kuznetsov, Devin Bougie, Werner Sun, Platform for Advanced Scientific Computing Conference 2023 (PASC23), Davos, Switzerland, 26-28 June, 2023, DOI 10.5281/zenodo.8132184

Evaluation and Implementation of Various Persistent Storage Options for CMSWEB Services in Kubernetes Infrastructure at CERN,  M. Imran, V. Kuznetsov, P. Paparrigopoulos, S. Trigazis, A Pfeiffer, ACAT 2023 J. Phys.: Conf. Ser. 2438 https://iopscience.iop.org/issue/1742-6596/2438/1 

Preparing distributed computing operations for the HL-LHC era with Operational Intelligence,  A Di. Girolamo, et. al., https://doi.org/10.3389/fdata.2021.753409 

Preparing distributed computing operations for the HLLHC era with Operational Intelligence, A Di. Girolamo, et. al., https://cds.cern.ch/record/2752591/files/ATL-SOFT-PROC-2021-001.pdf 

The evolution of the CMS monitoring infrastructure, Christian Ariza-Porras, Valentin Kuznetsov, Federica Legger, Rahul Indra, Nikodemas Tuckus, Ceyhun Uzunoglu, DOI: https://doi.org/10.1051/epjconf/202125102004 

Migration of CMSWEB cluster at CERN to Kubernetes: : a comprehensive study, Muhammad Imran, Valentin Kuznetsov, et. al., DOI: 10.1007/s10586-021-03325-0, https://link.springer.com/article/10.1007/s10586-021-03325-0 and https://doi.org/10.22323/1.390.0911, https://arxiv.org/pdf/2102.12751.pdf  or https://pos.sissa.it/390/911/pdf 

Smart Caching at CMS: applying AI to XCache edge services, Daniele Spiga, Diego Ciangottini, Mirco Tracolli, Tommaso Tedeschi, Daniele Cesini, Tommaso Boccali, Valentina Poggioni, Marco Baioletti, Valentin Kuznetsov,  The European Physical Journal Conferences 245:04024 DOI:10.1051/epjconf/202024504024

Big data solutions for CMS computing monitoring and analytics, Christian Ariza-Porras , Valentin Kuznetsov , and Federica Legger, EPJ Web of Conferences 245, 03022 (2020), https://doi.org/10.1051/epjconf/202024503022

MLaaS4HEP: Machine Learning as a Service for HEP, V. Kuznetsov, L. Giommi, D. Bonacorsi, Comput Softw Big Sci 5, 17 (2021). https://doi.org/10.1007/s41781-021-00061-3, or https://arxiv.org/abs/2007.14781 

Operational Intelligence for Distributed Computing Systems for Exascale Science, A.i Girolamo, F. Legger , P. Paparrigopoulos , A. Klimentov , J. Schovancová , V. Kuznetsov , M. Lassnig , L. Clissa, L. Rinaldi, M. Sharma , H. Bakhshiansohi , M. Zvada , D. Bonacorsi , S. Tisbeni , L. Giommi, L. Sousa, T. Diotalevi, M. Grigorieva, S. Padolski, EPJ Web of Conferences 245, 03017 (2020), https://doi.org/10.1051/epjconf/202024503017 

Using DODAS as deployment manager for smart caching of CMS data management system, M. Tracolli, M. Antonacci, T. Boccali, D. Bonacorsi, D Ciangottini, G. Donvito, C. Duma, L. Gaido, D. Salomoni, D.Spiga, V. Kuznetsov, https://iopscience.iop.org/article/10.1088/1742-6596/1525/1/012057 , doi:10.1088/1742-6596/1525/1/012057

The CMS monitoring infrastructure and applications, C. Ariza-Porras, V. Kuznetsov, F. Legger, Computing Software Big Science 5, 5 (2021). https://doi.org/10.1007/s41781-020-00051-x or https://arxiv.org/abs/2007.03630

Machine Learning as a Service for HEP, V. Kuznetsov, http://arxiv.org/abs/1811.04492 

Gaining insight from large data volumes with ease, V. Kuznetsov, http://arxiv.org/abs/1811.04785 

Machine Learning in High Energy Physics Community White Paper, K. Albertsson et. al, https://doi.org/10.48550/arXiv.1807.02876 or  https://arxiv.org/abs/1807.02876 

A Roadmap for HEP Software and Computing R&D for the 2020s, A.A. Alves Jr, et. al, Comput Softw Big Sci (2019) 3, 7, https://doi.org/10.1007/s41781-018-0018-8, or https://arxiv.org/abs/1712.06982 

The archive solution for distributed workflow management agents of the CMS experiment at LHC. V. Kuznetsov, N. Fischer, Y. Guo, Computing and Software for Big Science (2018) 2:1, doi: 10.1007/s41781-018-0005-0 

Exploiting Apache Spark platform for CMS computing analytics, M. Meoni, V. Kuznetsov, L. Menichetti, J. Rumševičius, T. Boccali, D. Bonacorsi, ACAT 2017, http://arxiv.org/abs/1711.00552 

Exploiting analytics techniques in CMS computing monitoring, D. Bonacorsi, V. Kuznetsov, N. Magini, A. Repečka, E. Vaandering, Journal of Physics: Conference Series 898 (2017) 092030 doi:10.1088/1742-6596/898/9/092030

Predicting dataset popularity for the CMS experiment V. Kuznetsov, T. Li, L. Giommi, D. Bonacorsi, T. Wildish Journal of Physics: Conference Series 762 (2016) 012048 doi:10.1088/1742-6596/762/1/012048 

Exploring Patterns and Correlations in CMS Computing Operations Data with Big Data Analytics Techniques, D. Bonacorsi, T. Wildish, L. Giommi, V. Kuznetsov, (2015) DOI: https://doi.org/10.22323/1.239.0008

Exploiting CMS data popularity to model the evolution of data management for Run-2 and beyond D. Bonacorsi, T. Boccali, D. Giordano, M. Girone, M. Neri, N. Magini, V. Kuznetsov and T. Wildish J. Phys.: Conf. Ser. 664, 032003 doi:10.1088/1742-6596/664/3/032003 

The CMS Data Management System M. Giffels, Y. Guo, V. Kuznetsov, N. Magini and T. Wildish J. Phys.: Conf. Ser. 513 042052 doi:10.1088/1742-6596/513/4/042052 

Keyword Search over Data Service Integration for Accurate Results V. Zemleris, V. Kuznetsov and R. Gwadera, J. Phys.: Conf. Ser. 513 032106 doi:10.1088/1742-6596/513/3/032106 

Life in extra dimensions of database world or penetration of NoSQL in HEP community V Kuznetsov et al., J. Phys.: Conf. Ser. 396 052043 2012, doi:10.1088/1742-6596/396/5/052043  

Data Aggregation System - a system for information retrieval on demand over relational and non-relational distributed data sources G. Ball, V. Kuznetsov, D. Evans and S. Metson, doi:10.1088/1742-6596/331/4/042029 

The CMS Data Aggregation System V. Kuznetsov, D. Evans, S. Metson, doi:10.1016/j.procs.2010.04.172 

The CMS DBS query language By A. Afaq, V. Kuznetsov, L. Lueking, D.Riley, V. Sekhri, doi:10.1088/1742-6596/219/4/042043 

Distributed Analysis in CMS CMS collaboration, doi: 10.1007/s10723-010-9152-1 

Provenance in High-Energy Physics Workflows A. Dolgert, L. Gibbons, C.D. Jones, V. Kuznetsov, M. Riedewald, D. Riley, C. Sharp, P. Wittich Computing in Science & Engineering, Vol 10, No. 3, p. 22, 2008 

A multi-dimensional view on information retrieval of CMS data A. Dolgert, L. Gibbons, V. Kuznetsov, C. Jones, D. Riley, J. Phys.: Conf. Ser. Volume 119, 072013, 2008 

The CMS Dataset Bookkeeping Service A. Afaq, et. al., J. Phys.: Conf. Ser. Volumne 119, 072001, 2008 

The New EventStore Data Management System For The CLEO-c Experiment C.D. Jones, V. Kuznetsov, D. Riley, G.J. Sharp, Int. J. Mod. Phys. A20:3868-3870, 2005

Experimental Physics:

Observation of a new boson at a mass of 125 GeV with the CMS experiment at the LHC The CMS Collaboration, arXiv:1207.7235v1, CERN-PH-EP/2012-220, 2012/08/01

Higgs and B physics in Run II, V. Kuznetsov for D0 collaboration, arXiv:hep-ex/0101055 

The preliminary results from the NOMAD-STAR detector, V. Kuznetsov for NOMAD experiment, Nuclear Physics B - Proceedings Supplements Volume 78, Issues 1–3, August 1999, Pages 287-292, DOI 10.1016/S0920-5632(99)00559-9

Final NOMAD results on νµ → ντ and νe → ντ oscillations including a new search for ντ appearance using hadronic τ decays, NOMAD experiment, http://cds.cern.ch/record/507056/files/0106102.pdf

Theoretical Physics:

The Toroid Dipole Moment of the Neutrino, V. Dubovik, V. Kuznetsov, International Journal of Modern Physics A 13(30):5257-5277 1998, DOI: 10.1142/S0217751X98002419

Transition Radiation of the Neutrino Toroid Dipole Moment, E. Bukina, V. Dubovik, V. Kuznetsov Physics Letters B 435(1-2) 1998, DOI: 10.1016/S0370-2693(98)00776-X 

Relationship Between the Kobayashi-Maskawa and Chau-Keung Presentations of the Quark Mixing Matrix, V. Kuznetsov, V. A. Naumov Il Nuovo Cimento A 108(12):1451-1456 1995, DOI: 10.1007/BF02821061

Geometric phases for three-level non-Hermitian system, S.E. Korenblit, V. Kuznetsov, V. A. Naumov, DOI: 10.13140/RG.2.1.1878.1282