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Rising Stars
2025

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Rising Stars

D-Index
47
Citations
6427
World Ranking
408
National Ranking
7

Engineering and Technology

D-Index
55
Citations
9266
World Ranking
3069
National Ranking
17

Ümit Ağbulut publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Ümit Ağbulut sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 181 publications — 40th percentile

40% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Ümit Ağbulut D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Ümit Ağbulut sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 55 D-Index — 70th percentile

70% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Ümit Ağbulut is a researcher affiliated with Yıldız Technical University in Turkey. Their scientific contributions focus primarily on engineering with a broad engagement in several subfields. These include biomedical engineering, fluid flow and transfer processes, mechanical engineering, renewable energy, sustainability and the environment, and materials chemistry.

Their research addresses key topics such as biodiesel production and applications, advanced combustion engine technologies, catalytic processes in materials science, thermochemical biomass conversion processes, solar thermal and photovoltaic systems, vehicle emissions and performance, as well as lubricants and their additives.

Ümit Ağbulut has published extensively, with a significant number of papers appearing in established venues. Frequent publication outlets include:

  • Energy
  • International Journal of Hydrogen Energy
  • Journal of Thermal Analysis and Calorimetry
  • Fuel
  • Case Studies in Thermal Engineering

Notable recent papers authored or co-authored by them are:

  • Prediction of daily global solar radiation using different machine learning algorithms: Evaluation and comparison (2020), Renewable and Sustainable Energy Reviews
  • Impact of various metal-oxide based nanoparticles and biodiesel blends on the combustion, performance, emission, vibration and noise characteristics of a CI engine (2020), Fuel
  • Forecasting of transportation-related energy demand and CO2 emissions in Turkey with different machine learning algorithms (2021), Sustainable Production and Consumption

Additionally, related works frequently involve collaborations, with several recurring co-authors who have contributed to their research projects. These frequent collaborators include Suat Sarıdemir, Ali Etem Gürel, Asif Afzal, Saboor Shaik, and C. Ahamed Saleel.

Ümit Ağbulut's work incorporates innovative methodologies such as machine learning algorithms applied to forecasting and prediction models in energy systems and emissions. This is illustrated in publications addressing solar radiation prediction and transportation-related emissions forecasting.

Best Publications

  • Prediction of daily global solar radiation using different machine learning algorithms: Evaluation and comparison

    Ümit Ağbulut;Ali Etem Gürel;Yunus Biçen

  • Impact of various metal-oxide based nanoparticles and biodiesel blends on the combustion, performance, emission, vibration and noise characteristics of a CI engine

    Ümit Ağbulut;Mustafa Karagöz;Suat Sarıdemir;Ahmet Öztürk

  • Forecasting of transportation-related energy demand and CO2 emissions in Turkey with different machine learning algorithms

    Ümit Ağbulut

  • Electricity production based forecasting of greenhouse gas emissions in Turkey with deep learning, support vector machine and artificial neural network algorithms

    Melahat Sevgül Bakay;Ümit Ağbulut

  • Recent advances in hydrogen production from biomass waste with a focus on pyrolysis and gasification

    Unknown

  • Experimental investigation of combustion, performance and emission characteristics of a diesel engine fuelled with diesel–biodiesel–alcohol blends

    Ümit Ağbulut;Suat Sarıdemir;Serdar Albayrak

  • Investigation on the combined effect of the hydrogen premixing and nanoparticle mixed pyrolysed oil of transformer oil waste in engine characteristics

    Unknown

  • Waste to energy: Production of waste tire pyrolysis oil and comprehensive analysis of its usability in diesel engines

    Mustafa Karagöz;Ümit Ağbulut;Suat Sarıdemir

  • A general view to converting fossil fuels to cleaner energy source by adding nanoparticles

    Ümit Ağbulut;Suat Sarıdemir

  • Production of waste soybean oil biodiesel with various catalysts, and the catalyst role on the CI engine behaviors

    Unknown

  • Optimization of Thermal and Structural Design in Lithium-Ion Batteries to Obtain Energy Efficient Battery Thermal Management System (BTMS): A Critical Review

    H. Fayaz;Asif Afzal;A. D. Mohammed Samee;Manzoore Elahi M. Soudagar

  • Assessment of machine learning, time series, response surface methodology and empirical models in prediction of global solar radiation

    Ali Etem Gürel;Ümit Ağbulut;Yunus Biçen

  • Understanding behaviors of compression ignition engine running on metal nanoparticle additives-included fuels: A control comparison between biodiesel and diesel fuel

    Unknown

  • Technological solutions for boosting hydrogen role in decarbonization strategies and net-zero goals of world shipping: Challenges and perspectives

    Unknown

  • Energy recovery from waste animal fats and detailed testing on combustion, performance, and emission analysis of IC engine fueled with their blends enriched with metal oxide nanoparticles

    Unknown

  • Hydrogen Production by Water Splitting with Support of Metal and Carbon-Based Photocatalysts

    Unknown

  • Different energy storage techniques: recent advancements, applications, limitations, and efficient utilization of sustainable energy

    Unknown

  • Microalgae bio-oil production through pyrolysis and hydrothermal liquefaction: Mechanism and characteristics.

    Unknown

  • Hydrothermal carbonization of food waste as sustainable energy conversion path.

    Unknown

  • Experimental investigation and prediction of performance and emission responses of a CI engine fuelled with different metal-oxide based nanoparticles–diesel blends using different machine learning algorithms

    Ümit Ağbulut;Ali Etem Gürel;Suat Sarıdemir

  • Energy, exergy, economic and sustainability assessments of a compression ignition diesel engine fueled with tire pyrolytic oil−diesel blends

    Mustafa Karagoz;Cuneyt Uysal;Umit Agbulut;Suat Saridemir

  • Effects of high-dosage copper oxide nanoparticles addition in diesel fuel on engine characteristics

    Ümit Ağbulut;Suat Sarıdemir;Upendra Rajak;Fikret Polat

  • Experimental analysis of CPV/T solar dryer with nano-enhanced PCM and prediction of drying parameters using ANN and SVM algorithms

    Mehmet Onur Karaağaç;Alper Ergün;Ümit Ağbulut;Ali Etem Gürel

  • Experimental investigation of fusel oil (isoamyl alcohol) and diesel blends in a CI engine

    Ümit Ağbulut;Suat Sarıdemir;Mustafa Karagöz

  • Prediction of performance, combustion and emission characteristics for a CI engine at varying injection pressures

    Ümit Ağbulut;Mustafa Ayyıldız;Suat Sarıdemir

  • A review of stability, thermophysical properties and impact of using nanofluids on the performance of refrigeration systems

    Gökhan Yıldız;Ümit Ağbulut;Ali Etem Gürel

  • Combustion, performance, vibration and noise characteristics of cottonseed methyl ester–diesel blends fuelled engine

    Suat Sarıdemir;Ümit Ağbulut

  • Exergetic and exergoeconomic analyses of a CI engine fueled with diesel-biodiesel blends containing various metal-oxide nanoparticles

    Mustafa Karagoz;Cuneyt Uysal;Umit Agbulut;Suat Saridemir

  • Performance analysis of using CuO-Methanol nanofluid in a hybrid system with concentrated air collector and vacuum tube heat pipe

    Metin Kaya;Ali Etem Gürel;Ümit Ağbulut;İlhan Ceylan

  • Investigating the role of fuel injection pressure change on performance characteristics of a DI-CI engine fuelled with methyl ester

    Suat Sarıdemir;Ali Etem Gürel;Ümit Ağbulut;Faruk Bakan

Frequent Co-Authors

Upendra Rajak
Upendra Rajak RGM College Of Engineering and Technology
Ataollah Khanlari
Ataollah Khanlari University of Turkish Aeronautical Association
Azim Doğuş Tuncer
Azim Doğuş Tuncer Catalan Institute of Nanoscience and Nanotechnology
Tikendra Nath Verma
Tikendra Nath Verma National Institute Of Technology
Adnan Sözen
Adnan Sözen Gazi University
A. Muthu Manokar
A. Muthu Manokar SRM TRP Engineering College
Ahamed Saleel C
Ahamed Saleel C King Khalid University
M.A. Mujtaba
M.A. Mujtaba University of Engineering and Technology Lahore

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