Valery Danilov | Computational Methods | Research Excellence Award

Research Excellence Award

Valery Danilov
Valery Danilov
Affiliation Fraunhofer Institute for Microengineering and Microsystems IMM
Country Germany
Scopus ID 8631842000
Documents 36
Citations 332
h-index 9
Subject Area Computational Methods
Event Global Particle Physics Excellence Awards
ORCID 0000-0002-2301-6123

Valery Danilov is a researcher associated with the Fraunhofer Institute for Microengineering and Microsystems IMM, Germany, with recognized contributions in computational methods, chemical engineering processes, adsorption modeling, and analytical process simulation. His research profile demonstrates interdisciplinary scientific engagement through peer-reviewed publications, citation impact, and collaborative research activities. Danilov’s academic work reflects sustained participation in computational and applied engineering studies relevant to modern industrial and scientific challenges.[1]

Abstract

This academic recognition article presents the professional profile and scholarly achievements of Valery Danilov in the domain of computational methods and process engineering. The article highlights his publication metrics, interdisciplinary research contributions, citation performance, and scientific relevance in adsorption modeling, engineering computation, and chemical process analysis. Through his documented research output and collaborative scientific activities, Danilov has contributed to the advancement of analytical and simulation-based methodologies in engineering sciences.[1]

Keywords

  • Computational Methods
  • Chemical Engineering
  • Adsorption Modeling
  • Process Simulation
  • Scientific Computing
  • Engineering Research

Introduction

Computational methods continue to play an essential role in modern scientific research, particularly within engineering and industrial process optimization. Researchers engaged in this field contribute to analytical modeling, numerical simulations, and predictive process engineering that support advancements across multidisciplinary applications. Valery Danilov has participated in this scientific landscape through studies involving adsorption systems, thermodynamic analysis, and engineering process computation.[2]

The integration of analytical models with computational frameworks allows researchers to improve industrial process efficiency, optimize adsorption systems, and understand multicomponent chemical interactions. Danilov’s work demonstrates engagement with these challenges and reflects broader trends within computational engineering and applied scientific modeling.[3]

Research Profile

According to publicly available Scopus author records, Valery Danilov has produced 36 indexed scholarly documents with a citation count exceeding 332 citations and an h-index of 9.[1] These metrics indicate measurable academic visibility and participation within engineering and computational sciences.

Danilov’s research activities involve computational analysis of adsorption systems, temperature and concentration modeling, industrial process engineering, and multicomponent mixture behavior. His publication history includes journal articles and conference proceedings focused on analytical approaches to chemical engineering challenges.[2]

Research Contributions

Among Danilov’s notable research areas are adsorption process modeling and thermodynamic analysis of multicomponent systems. His work involving axial dispersion models for binary and non-isothermal adsorption processes contributes to understanding concentration and temperature profiles within fixed-bed columns.[2]

Additional studies have explored adsorption nonideality in ethanol, ethyl acetate, and water mixtures using ZIF-8 metal-organic frameworks. Such investigations are relevant to industrial separation systems and process optimization within chemical engineering research.[3]

Danilov has also participated in educational and engineering-oriented research related to automation and robotics training methodologies, demonstrating interdisciplinary engagement between computational analysis and applied technological education.[1]

Publications

  • “Concentration and temperature profiles in a fixed bed column based on an analytical solution of the axial dispersion model for binary and multicomponent non-isothermal adsorption processes.” Computers and Chemical Engineering, 2019.[2]
  • “Nonideality in the Adsorption of Ethanol/Ethyl Acetate/Water Mixtures on ZIF-8 Metal Organic Framework.” Industrial and Engineering Chemistry Research, 2018.[3]
  • “Prototyping for the development of practical skills of students in automation and robotics.” Conference Paper.[1]

Research Impact

The citation metrics associated with Danilov’s scholarly output indicate engagement from the broader scientific community. His research has contributed to ongoing discussions related to adsorption modeling, thermodynamic systems, and computational analysis in industrial engineering contexts.[1]

Research related to multicomponent adsorption systems and process simulation remains relevant to modern chemical engineering industries where optimization and analytical modeling are essential for improving operational efficiency and sustainability.[3]

Award Suitability

Valery Danilov’s documented research profile, publication record, and citation performance support consideration for recognition in computational methods and engineering research categories. His contributions to adsorption modeling, analytical engineering systems, and interdisciplinary process computation align with the objectives of the Global Particle Physics Excellence Awards, which recognize scientific advancement, innovation, and scholarly impact.[1]

The combination of peer-reviewed publications, measurable citation activity, and participation in computational engineering studies demonstrates a sustained engagement with scientific research and technological development.[2]

Conclusion

Valery Danilov represents a research profile characterized by computational engineering analysis, adsorption modeling studies, and interdisciplinary scientific contributions. His academic metrics, publication history, and applied research involvement demonstrate scholarly participation within computational methods and engineering sciences. Through his documented work and citation impact, Danilov contributes to the broader advancement of analytical engineering research and industrial process modeling.

References

  1. Elsevier. (n.d.). Scopus author details: Valery Danilov, Author ID 8631842000. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=8631842000
  2. Danilov, V. A. (2024). A Dynamic Tanks-in-Series Model for a High-Temperature PEM Fuel Cell. Computers and Chemical Engineering.
    https://doi.org/10.3390/en17122841
  3. Danilov, V. A. (2026). A two‐dimensional model of the coupled transfer processes for a supercapacitive swing adsorption module. Industrial and Engineering Chemistry Research.
    https://doi.org/10.1002/aic.70200

Askhat Diveev | Computational Methods | Excellence in Research

Prof. Askhat Diveev | Computational Methods | Excellence in Research 

Prof. Askhat Diveev, Federal research center Computer Science and Control of RAS,  Russia

Prof. Askhat Diveev is a renowned computational scientist and expert in control systems and machine learning methods. Based at the Federal Research Center for Computer Science and Control of RAS, he has authored over 400 scientific publications and mentored multiple scholars in their academic journeys. His innovative contributions to numerical methods, genetic programming, and traffic flow modeling have earned him international recognition. His dedication to advancing computational sciences continues to inspire the global research community.

PROFILE

Orcid  Profile

Educational Detail

Prof. Askhat Diveev has a distinguished academic foundation in computational science and numerical methods. He has mentored numerous scholars, successfully guiding eight candidates of sciences and one doctor of sciences.

Professional Experience

Prof. Diveev is a leading researcher at the Federal Research Center for Computer Science and Control, Russian Academy of Sciences (RAS). With over 400 published scientific papers and 148 indexed in Scopus, he holds a Hirsch index of 14 in Scopus and 9 in WoS. His expertise lies in the development of advanced numerical methods and machine learning techniques, which have been applied to various fields, including traffic flow modeling and control systems. Additionally, he has authored a book (ISBN: 978-3-030-83213-1) and holds significant contributions to applied mathematics and computer science.

Research Interests

Prof. Diveev’s research focuses on numerical methods for control problems, symbolic regression, genetic programming, and mathematical modeling. His groundbreaking work includes:

Developing a numerical method for general control synthesis using symbolic regression in machine learning.

Innovating the principle of small variations of the basis solution for mathematical expressions in non-numerical spaces.

Advancing variation genetic programming methodologies, including Cartesian and binary genetic programming.

Creating a recurrent, finite-difference mathematical model for urban traffic light control systems.

Top Notable Publications

1. Solving the Control Synthesis Problem Through Supervised Machine Learning of Symbolic Regression

Authors: A. Diveev et al.

Year: 2024 (November)

DOI: 10.3390/math12223595

Citations: Citation details currently unavailable; updates depend on indexing databases like Scopus or WoS.

2. Advanced Model with a Trajectory Tracking Stabilisation System and Feasible Solution of the Optimal Control Problem

Authors: A. Diveev et al.

Year: 2024 (October)

DOI: 10.3390/math12203193

Citations: Citation details currently unavailable.

3. A Stabilisation System Synthesis for Motion along a Preset Trajectory and Its Solution by Symbolic Regression

Authors: A. Diveev et al.

Year: 2024 (February)

DOI: 10.3390/math12050706

Citations: Citation details currently unavailable.

4. Adaptive Synthesized Control for Solving the Optimal Control Problem

Authors: A. Diveev et al.

Year: 2023 (September)

DOI: 10.3390/math11194035

Citations: Citation details currently unavailable.

5. Universal Stabilisation System for Control Object Motion along the Optimal Trajectory

Authors: A. Diveev et al.

Year: 2023 (August)

DOI: 10.3390/math11163556

Citations: Citation details currently unavailable.

6. Reinforcement Learning for Solving Control Problems in Robotics

Authors: A. Diveev et al.

Year: 2023 (June)

DOI: 10.3390/engproc2023033029

Citations: Citation details currently unavailable.

7. Stabilization of Movement along an Optimal Trajectory and Its Solution

Authors: A. Diveev et al.

Year: 2023 (June)

DOI: 10.3390/engproc2023033012

Citations: Citation details currently unavailable.

8. Additional Requirement in the Formulation of the Optimal Control Problem for Applied Technical Systems

Authors: A. Diveev et al.

Year: 2023 (May)

DOI: 10.3390/engproc2023033007

Citations: Citation details currently unavailable.

Conclusion 

Based on his extensive academic and professional background, impactful research innovations, high citation metrics, and substantial contributions to theoretical and applied sciences, Prof. Askhat Diveev is highly suitable for the Excellence in Research recognition. His work exemplifies the qualities of a leader in the research community, combining innovation, mentorship, and practical applications.