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Computer Science
Hungary
2026

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Computer Science 77 1298 1257 1 1 400 19180

Amir Mosavi publications per year

The chart shows the history of publications by Amir Mosavi between 1995 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Amir Mosavi published across 31 years, from 1995 to 2025, averaging 24.3 papers a year. Output peaked at 270 publications in 2020. 41 of the 754 publications appeared in the last two years.

No. of publications
50 100 150 200 250
Bar chart. Horizontal axis: year, 1995 to 2025. Vertical axis: number of publications, 0 to 270. Peak 270 publications in 2020. 1995: 1 publication 1996: 0 publications 1997: 1 publication 1998: 4 publications 1999: 0 publications 2000: 0 publications 2001: 0 publications 2002: 0 publications 2003: 0 publications 2004: 0 publications 2005: 0 publications 2006: 0 publications 2007: 1 publication 2008: 1 publication 2009: 0 publications 2010: 6 publications 2011: 0 publications 2012: 1 publication 2013: 4 publications 2014: 4 publications 2015: 0 publications 2016: 0 publications 2017: 13 publications 2018: 14 publications 2019: 93 publications 2020: 270 publications 2021: 146 publications 2022: 116 publications 2023: 38 publications 2024: 27 publications 2025: 14 publications
1995 2025

754 publications in total across all disciplines

View publications per year as a table
Amir Mosavi: publications per year, 1995 to 2025
Year Publications
1995 1
1996 0
1997 1
1998 4
1999 0
2000 0
2001 0
2002 0
2003 0
2004 0
2005 0
2006 0
2007 1
2008 1
2009 0
2010 6
2011 0
2012 1
2013 4
2014 4
2015 0
2016 0
2017 13
2018 14
2019 93
2020 270
2021 146
2022 116
2023 38
2024 27
2025 14
Total 754
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Amir Mosavi publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Amir Mosavi sits on this spectrum.

No. of scientists
200 400 600
Bar chart with 97 bars. Horizontal axis: publications, 32–41 to 991+. Vertical axis: number of scientists, 0 to 609. Most scientists, 609, have 142–151 publications. The last bar groups every scientist with 991 publications or more. The highlighted bar, 392–401 publications, is where this scientist sits. 32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32–41 publications 991+

This scientist: 400 publications — 87th percentile

87% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

View publications distribution as a table
Number of Computer Science scientists by publication count, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
Publications Scientists This scientist
32–41 7
42–51 22
52–61 82
62–71 134
72–81 249
82–91 324
92–101 421
102–111 420
112–121 497
122–131 544
132–141 555
142–151 609
152–161 559
162–171 534
172–181 556
182–191 583
192–201 519
202–211 508
212–221 490
222–231 437
232–241 423
242–251 408
252–261 377
262–271 301
272–281 335
282–291 320
292–301 293
302–311 250
312–321 238
322–331 206
332–341 209
342–351 208
352–361 162
362–371 176
372–381 127
382–391 158
392–401 128 400
402–411 104
412–421 94
422–431 99
432–441 83
442–451 108
452–461 73
462–471 77
472–481 69
482–491 84
492–501 62
502–511 54
512–521 57
522–531 51
532–541 51
542–551 32
552–561 38
562–571 28
572–581 43
582–591 33
592–601 41
602–611 32
612–621 28
622–631 25
632–641 27
642–651 17
652–661 20
662–671 17
672–681 15
682–691 14
692–701 21
702–711 13
712–721 12
722–731 19
732–741 14
742–751 12
752–761 10
762–771 10
772–781 11
782–791 10
792–801 11
802–811 8
812–821 8
822–831 7
832–841 11
842–851 10
852–861 5
862–871 9
872–881 4
882–891 6
892–901 3
902–911 6
912–921 3
922–931 2
932–941 2
942–951 2
952–961 3
962–971 3
972–981 3
982–990 5
991+ 100
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Amir Mosavi D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Amir Mosavi sits on this spectrum.

No. of scientists
200 400 600 800
Bar chart with 52 bars. Horizontal axis: D-Index, 30–31 to 131+. Vertical axis: number of scientists, 0 to 990. Most scientists, 990, have 36–37 D-Index. The last bar groups every scientist with 131 D-Index or more. The highlighted bar, 76–77 D-Index, is where this scientist sits. 30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30–31 D-Index 131+

This scientist: 77 D-Index — 91st percentile

91% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

View D-Index distribution as a table
Number of Computer Science scientists by D-index, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
D-Index Scientists This scientist
30–31 879
32–33 983
34–35 918
36–37 990
38–39 968
40–41 907
42–43 821
44–45 763
46–47 689
48–49 543
50–51 543
52–53 518
54–55 500
56–57 458
58–59 400
60–61 337
62–63 308
64–65 292
66–67 249
68–69 213
70–71 192
72–73 189
74–75 165
76–77 139 77
78–79 119
80–81 121
82–83 113
84–85 88
86–87 87
88–89 75
90–91 69
92–93 57
94–95 46
96–97 38
98–99 34
100–101 36
102–103 27
104–105 37
106–107 18
108–109 31
110–111 19
112–113 16
114–115 12
116–117 20
118–119 15
120–121 5
122–123 20
124–125 8
126–127 5
128–129 7
130 3
131+ 98
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Research.com Recognitions

  • 2026 - Research.com Computer Science in Hungary Leader Award
  • 2025 - Research.com Computer Science in Hungary Leader Award
  • 2022 - Research.com Computer Science in Hungary Leader Award

Overview

Amir Mosavi is affiliated with Óbuda University in Hungary and has contributed extensively to research in engineering and its related subfields. Their body of work covers a wide range of topics within engineering, with a strong focus on the application of artificial intelligence across various disciplines.

Their main field of study is Engineering, with particular specialization in the following subfields:

  • Civil and Structural Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering
  • Environmental Engineering
  • Building and Construction

Amir Mosavi's research addresses a number of key topics, including:

  • Energy Load and Power Forecasting
  • Hydrological Forecasting Using AI
  • COVID-19 diagnosis using AI
  • Hydrology and Watershed Management Studies
  • COVID-19 epidemiological studies
  • Innovative concrete reinforcement materials
  • Hydraulic flow and structures

They have published prolifically in several recognized venues, with frequent contributions to:

  • Preprints.org
  • Engineering Applications of Computational Fluid Mechanics
  • arXiv (Cornell University)
  • IEEE Access
  • SSRN Electronic Journal

Their recent papers illustrate an emphasis on machine learning and predictive analytics applied to engineering and epidemiology:

  • "Predicting Stock Market Trends Using Machine Learning and Deep Learning Algorithms Via Continuous and Binary Data; a Comparative Analysis" (2020) published in IEEE Access
  • "COVID-19 Outbreak Prediction with Machine Learning" (2020) published in Algorithms
  • "Deep Learning for Stock Market Prediction" (2020) published in Entropy
  • "Predicting Standardized Streamflow index for hydrological drought using machine learning models" (2020) published in Engineering Applications of Computational Fluid Mechanics
  • "COVID-19 Pandemic Prediction for Hungary; A Hybrid Machine Learning Approach" (2020) published in Mathematics

Amir collaborates frequently with several co-authors whose joint work has spanned numerous publications. Among the most frequent co-authors are:

  • Shahab S. Band
  • Sina Ardabili
  • Kwok-wing Chau
  • Narjes Nabipour
  • Shahaboddin Shamshirband

Best Publications

  • Flood prediction using machine learning models: Literature review

    Amir Mosavi;Pinar Ozturk;Kwok Wing Chau

  • An ensemble prediction of flood susceptibility using multivariate discriminant analysis, classification and regression trees, and support vector machines

    Bahram Choubin;Bahram Choubin;Ehsan Moradi;Mohammad Golshan;Jan Adamowski

  • State of the Art of Machine Learning Models in Energy Systems, a Systematic Review

    Amir Mosavi;Amir Mosavi;Amir Mosavi;Mohsen Salimi;Sina Faizollahzadeh Ardabili;Timon Rabczuk

  • Sustainable Business Models: A Review

    Saeed Nosratabadi;Amir Mosavi;Shahaboddin Shamshirband;Edmundas Kazimieras Zavadskas

  • COVID-19 outbreak prediction with machine learning

    Sina F. Ardabili;Amir Mosavi;Pedram Ghamisi;Filip Ferdinand

  • Predicting and Mapping of Soil Organic Carbon Using Machine Learning Algorithms in Northern Iran

    Mostafa Emadi;Ruhollah Taghizadeh-Mehrjardi;Ali Cherati;Majid Danesh

  • Sustainable business models: A review

    Saeed Nosratabadi;Amir Mosavi;Shahaboddin Shamshirband;Edmundas Kazimieras Zavadskas

  • Predicting Stock Market Trends Using Machine Learning and Deep Learning Algorithms Via Continuous and Binary Data; a Comparative Analysis

    Mojtaba Nabipour;Pooyan Nayyeri;Hamed Jabani;S Shahab

  • Deep Learning for Stock Market Prediction

    M. Nabipour;P. Nayyeri;H. Jabani;A. Mosavi;A. Mosavi

  • Flash-flood hazard assessment using ensembles and Bayesian-based machine learning models: Application of the simulated annealing feature selection method.

    Farzaneh Sajedi Hosseini;Bahram Choubin;Amir Mosavi;Narjes Nabipour

  • COVID-19 pandemic prediction for Hungary; A hybrid machine learning approach

    Gergo Pinter;Imre Felde;Amir Mosavi;Pedram Ghamisi

  • Deep Learning for Detecting Building Defects Using Convolutional Neural Networks

    Husein Perez;Joseph H. M. Tah;Amir Mosavi

  • Predicting Standardized Streamflow index for hydrological drought using machine learning models

    Shahabbodin Shamshirband;Sajjad Hashemi;Hana Salimi;Saeed Samadianfard

  • Evaluating urban flood risk using hybrid method of TOPSIS and machine learning

    Elham Rafiei-Sardooi;Ali Azareh;Bahram Choubin;Amir H. Mosavi;Amir H. Mosavi

  • Integrated machine learning methods with resampling algorithms for flood susceptibility prediction.

    Esmaeel Dodangeh;Bahram Choubin;Ahmad Najafi Eigdir;Narjes Nabipour

  • Flash Flood Susceptibility Modeling Using New Approaches of Hybrid and Ensemble Tree-Based Machine Learning Algorithms

    Shahab S. Band;Saeid Janizadeh;Subodh Chandra Pal;Asish Saha

  • Wind speed prediction using a hybrid model of the multi-layer perceptron and whale optimization algorithm

    Saeed Samadianfard;Sajjad Hashemi;Katayoun Kargar;Mojtaba Izadyar

  • Advances in Machine Learning Modeling Reviewing Hybrid and Ensemble Methods

    Sina Ardabili;Amir Mosavi;Amir Mosavi;Annamária R. Várkonyi-Kóczy

  • Prediction of Hydropower Generation Using Grey Wolf Optimization Adaptive Neuro-Fuzzy Inference System

    Majid Dehghani;Hossein Riahi-Madvar;Farhad Hooshyaripor;Amir Mosavi;Amir Mosavi

  • Modeling Pan Evaporation Using Gaussian Process Regression K-Nearest Neighbors Random Forest and Support Vector Machines; Comparative Analysis

    Sevda Shabani;Saeed Samadianfard;Mohammad Taghi Sattari;Amir Mosavi

  • Ensemble Boosting and Bagging Based Machine Learning Models for Groundwater Potential Prediction

    Amirhosein Mosavi;Farzaneh Sajedi Hosseini;Bahram Choubin;Massoud Goodarzi

  • Ensemble models with uncertainty analysis for multi-day ahead forecasting of chlorophyll a concentration in coastal waters

    Shahaboddin Shamshirband;Ehsan Jafari Nodoushan;Jason E. Adolf;Azizah Abdul Manaf

  • Prediction of Compression Index of Fine-Grained Soils Using a Gene Expression Programming Model

    Danial Mohammadzadeh;Seyed-Farzan Kazemi;Amir Mosavi;Ehsan Nasseralshariati

  • A New Online Learned Interval Type-3 Fuzzy Control System for Solar Energy Management Systems

    Zhi Liu;Ardashir Mohammadzadeh;Hamza Turabieh;Majdi Mafarja

  • Snow avalanche hazard prediction using machine learning methods

    Bahram Choubin;Moslem Borji;Amir Mosavi;Amir Mosavi;Farzaneh Sajedi-Hosseini

Frequent Co-Authors

Shahab S. Band
Shahab S. Band National Yunlin University of Science and Technology
Kwok-wing Chau
Kwok-wing Chau Hong Kong Polytechnic University
Pedram Ghamisi
Pedram Ghamisi Helmholtz-Zentrum Dresden-Rossendorf
Timon Rabczuk
Timon Rabczuk Bauhaus University, Weimar
Ahmad Sedaghat
Ahmad Sedaghat Australian University Kuwait
Abdolhossein Hemmati-Sarapardeh
Abdolhossein Hemmati-Sarapardeh Shahid Bahonar University of Kerman
Alireza Baghban
Alireza Baghban Amirkabir University of Technology
Hossein Moayedi
Hossein Moayedi Duy Tan University
Hossein Bonakdari
Hossein Bonakdari University of Ottawa
Roohallah Alizadehsani
Roohallah Alizadehsani Deakin University

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