World's Best Scientists 2026 revealed!
Manisa Pipattanasomporn

Manisa Pipattanasomporn

D-Index & Metrics

Engineering and Technology

D-Index
43
Citations
10332
World Ranking
6034
National Ranking
12

Manisa Pipattanasomporn 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 Manisa Pipattanasomporn 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: 132 publications — 20th percentile

20% of scientists in this discipline score the same or lower.

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

Manisa Pipattanasomporn 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 Manisa Pipattanasomporn 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: 43 D-Index — 39th percentile

39% of scientists in this discipline score the same or lower.

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

Overview

Manisa Pipattanasomporn is affiliated with Chulalongkorn University in Thailand and conducts research primarily in the fields of Engineering and Computer Science. Their work spans several subfields including Electrical and Electronic Engineering, Building and Construction, Information Systems, Computer Vision and Pattern Recognition, and Global and Planetary Change.

The scientist's research topics cover a range of areas related to energy systems and computational methods. These include:

  • Smart Grid Energy Management
  • Energy Load and Power Forecasting
  • Building Energy and Comfort Optimization
  • Blockchain Technology Applications and Security
  • Smart Grid Security and Resilience
  • Electricity Theft Detection Techniques
  • Image and Signal Denoising Methods

Some of the recent papers authored or co-authored by Manisa Pipattanasomporn are:

  • "Robust short-term electrical load forecasting framework for commercial buildings using deep recurrent neural networks," 2020, Applied Energy
  • "CU-BEMS, smart building electricity consumption and indoor environmental sensor datasets," 2020, Scientific Data
  • "Data-driven short-term natural gas demand forecasting with machine learning techniques," 2021, Journal of Petroleum Science and Engineering
  • "Cybersecure and scalable, token-based renewable energy certificate framework using blockchain-enabled trading platform," 2022, Electrical Engineering
  • "Simultaneous wound border segmentation and tissue classification using a conditional generative adversarial network," 2021, The Journal of Engineering

Manisa Pipattanasomporn frequently collaborates with several researchers. Notable co-authors include:

  • Murat Kuzlu
  • Ümit Cali
  • Onur Elma
  • Vinayak Sharma
  • Ramesh Reddi

The scientist has published in multiple venues, with a recurrent presence in:

  • arXiv (Cornell University)
  • Applied Energy
  • Scientific Data
  • Journal of Petroleum Science and Engineering
  • Electrical Engineering

Best Publications

  • Multi-agent systems in a distributed smart grid: Design and implementation

    M. Pipattanasomporn;H. Feroze;S. Rahman

  • An Algorithm for Intelligent Home Energy Management and Demand Response Analysis

    M. Pipattanasomporn;M. Kuzlu;S. Rahman

  • Communication network requirements for major smart grid applications in HAN, NAN and WAN

    Murat Kuzlu;Manisa Pipattanasomporn;Saifur Rahman

  • Grid Integration of Electric Vehicles and Demand Response With Customer Choice

    Shengnan Shao;M. Pipattanasomporn;S. Rahman

  • Challenges of PHEV penetration to the residential distribution network

    Shengnan Shao;Manisa Pipattanasomporn;Saifur Rahman

  • Day-ahead building-level load forecasts using deep learning vs. traditional time-series techniques

    Mengmeng Cai;Manisa Pipattanasomporn;Saifur Rahman

  • Demand Response as a Load Shaping Tool in an Intelligent Grid With Electric Vehicles

    Shengnan Shao;M. Pipattanasomporn;S. Rahman

  • Load Profiles of Selected Major Household Appliances and Their Demand Response Opportunities

    Manisa Pipattanasomporn;Murat Kuzlu;Saifur Rahman;Yonael Teklu

  • Development of physical-based demand response-enabled residential load models

    Shengnan Shao;Manisa Pipattanasomporn;Saifur Rahman

  • Impact of TOU rates on distribution load shapes in a smart grid with PHEV penetration

    Shengnan Shao;Tianshu Zhang;Manisa Pipattanasomporn;Saifur Rahman

  • Distribution Voltage Regulation Through Active Power Curtailment With PV Inverters and Solar Generation Forecasts

    Shibani Ghosh;Saifur Rahman;Manisa Pipattanasomporn

  • Performance Analysis of a Hyperledger Fabric Blockchain Framework: Throughput, Latency and Scalability

    Murat Kuzlu;Manisa Pipattanasomporn;Levent Gurses;Saifur Rahman

  • Hardware Demonstration of a Home Energy Management System for Demand Response Applications

    M. Kuzlu;M. Pipattanasomporn;S. Rahman

  • Implications of on-site distributed generation for commercial/industrial facilities

    M. Pipattanasomporn;M. Willingham;S. Rahman

  • Robust short-term electrical load forecasting framework for commercial buildings using deep recurrent neural networks

    Gopal Chitalia;Gopal Chitalia;Manisa Pipattanasomporn;Manisa Pipattanasomporn;Vishal Garg;Saifur Rahman

  • Intelligent Distributed Autonomous Power Systems (IDAPS)

    S. Rahman;M. Pipattanasomporn;Y. Teklu

  • Comparative analysis of auction mechanisms and bidding strategies for P2P solar transactive energy markets

    Jason Lin;Manisa Pipattanasomporn;Manisa Pipattanasomporn;Saifur Rahman

  • Assessment of communication technologies and network requirements for different smart grid applications

    M. Kuzlu;M. Pipattanasomporn

  • An energy management model to study energy and peak power savings from PV and storage in demand responsive buildings

    Fakeha Sehar;Manisa Pipattanasomporn;Saifur Rahman

  • Flywheel Energy Storage Systems for Ride-through Applications in a Facility Microgrid

    R. Arghandeh;M. Pipattanasomporn;S. Rahman

  • Real-time co-simulation platform using OPAL-RT and OPNET for analyzing smart grid performance

    D. Bian;M. Kuzlu;M. Pipattanasomporn;S. Rahman

Frequent Co-Authors

Saifur Rahman
Saifur Rahman Virginia Tech
Yi Tang
Yi Tang Nanyang Technological University
Mehmet Uzunoglu
Mehmet Uzunoglu Yıldız Technical University
Roger A. Dougal
Roger A. Dougal University of South Carolina
Michael Steurer
Michael Steurer Florida State University
Weerakorn Ongsakul
Weerakorn Ongsakul Asian Institute of Technology

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