World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
52
Citations
10806
World Ranking
5081
National Ranking
31

Seungmin Rho 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 Seungmin Rho sits on this spectrum.

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 publications 991+

This scientist: 371 publications — 84th percentile

84% of scientists in this discipline score the same or lower.

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

Seungmin Rho 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 Seungmin Rho sits on this spectrum.

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 D-Index 131+

This scientist: 52 D-Index — 65th percentile

65% of scientists in this discipline score the same or lower.

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

Overview

Seungmin Rho is affiliated with Sungkyul University in South Korea and has contributed extensively to the fields of Computer Science and Engineering. Their research spans multiple subfields, including Electrical and Electronic Engineering, Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications, and Biomedical Engineering.

The main research topics addressed by Seungmin Rho include:

  • Energy Load and Power Forecasting
  • Anomaly Detection Techniques and Applications
  • Video Surveillance and Tracking Methods
  • Smart Grid Energy Management
  • Stock Market Forecasting Methods
  • Solar Radiation and Photovoltaics
  • Gait Recognition and Analysis

Seungmin Rho has published papers in several scientific venues multiple times. The most frequent publication outlets include:

  • The Journal of Supercomputing
  • IEEE Access
  • Sensors
  • Alexandria Engineering Journal
  • Complexity

Recent selected papers by Seungmin Rho include:

  • Towards Efficient Electricity Forecasting in Residential and Commercial Buildings: A Novel Hybrid CNN with a LSTM-AE based Framework (2020, Sensors)
  • Combination of short-term load forecasting models based on a stacking ensemble approach (2020, Energy and Buildings)
  • A deep feature-based real-time system for Alzheimer disease stage detection (2020, Multimedia Tools and Applications)
  • Long-Term Wind Power Forecasting Using Tree-Based Learning Algorithms (2020, IEEE Access)
  • A Survey on blockchain for industrial Internet of Things (2021, Alexandria Engineering Journal)

The scientist collaborates frequently with a group of coauthors including Jihoon Moon, Muazzam Maqsood, Maryam Bukhari, Eenjun Hwang, and Sung Wook Baik.

In addition to journal articles, Seungmin Rho has contributed to books, including a publication in 2021 titled "Big Data Technologies and Applications," published in the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering series.

Best Publications

  • Urban planning and building smart cities based on the Internet of Things using Big Data analytics

    M. Mazhar Rathore;Awais Ahmad;Anand Paul;Seungmin Rho

  • Convolutional Neural Networks Based Fire Detection in Surveillance Videos

    Khan Muhammad;Jamil Ahmad;Irfan Mehmood;Seungmin Rho

  • Deep Learning Based Multi-Channel Intelligent Attack Detection for Data Security

    Feng Jiang;Yunsheng Fu;B. B. Gupta;Yongsheng Liang

  • Improving electric energy consumption prediction using CNN and Bi-LSTM

    Tuong Le;Minh Thanh Vo;Bay Vo;Eenjun Hwang

  • Medical image denoising using convolutional neural network: a residual learning approach

    Worku Jifara;Feng Jiang;Seungmin Rho;Maowei Cheng

  • Traffic Engineering in Software-Defined Networking: Measurement and Management

    Zhaogang Shu;Jiafu Wan;Jiaxiang Lin;Shiyong Wang

  • Music emotion classification and context-based music recommendation

    Byeong-Jun Han;Seungmin Rho;Sanghoon Jun;Eenjun Hwang

  • A novel magic LSB substitution method (M-LSB-SM) using multi-level encryption and achromatic component of an image

    Khan Muhammad;Muhammad Sajjad;Irfan Mehmood;Seungmin Rho

  • Towards Efficient Electricity Forecasting in Residential and Commercial Buildings: A Novel Hybrid CNN with a LSTM-AE based Framework

    Zulfiqar Ahmad Khan;Tanveer Hussain;Amin Ullah;Seungmin Rho

  • Short-Term Prediction of Residential Power Energy Consumption via CNN and Multi-Layer Bi-Directional LSTM Networks

    Fath U Min Ullah;Amin Ullah;Ijaz Ul Haq;Seungmin Rho

  • Cooperative Cognitive Intelligence for Internet of Vehicles

    Anand Paul;Alfred Daniel;Awais Ahmad;Seungmin Rho

  • Energy Aware Cluster-Based Routing in Flying Ad-Hoc Networks.

    Farhan Aadil;Ali Raza;Muhammad Fahad Khan;Muazzam Maqsood

  • Fog Computing-Based IoT for Health Monitoring System

    Anand Paul;Hameed Pinjari;Won-Hwa Hong;Hyun Cheol Seo

  • A deep feature-based real-time system for Alzheimer disease stage detection

    Hina Nawaz;Muazzam Maqsood;Sitara Afzal;Farhan Aadil

  • Combination of short-term load forecasting models based on a stacking ensemble approach

    Jihoon Moon;Seungwon Jung;Jehyeok Rew;Seungmin Rho

  • Medical image semantic segmentation based on deep learning

    Feng Jiang;Aleksei Grigorev;Seungmin Rho;Zhihong Tian;Zhihong Tian

  • A Fog Based Middleware for Automated Compliance With OECD Privacy Principles in Internet of Healthcare Things

    Ahmed M. Elmisery;Seungmin Rho;Dmitri Botvich

  • Leukocytes Classification and Segmentation in Microscopic Blood Smear: A Resource-Aware Healthcare Service in Smart Cities

    Muhammad Sajjad;Siraj Khan;Zahoor Jan;Khan Muhammad

  • Image steganography using uncorrelated color space and its application for security of visual contents in online social networks

    Khan Muhammad;Muhammad Sajjad;Irfan Mehmood;Seungmin Rho

  • Long-Term Wind Power Forecasting Using Tree-Based Learning Algorithms

    Amirhossein Ahmadi;Mojtaba Nabipour;Behnam Mohammadi-Ivatloo;Ali Moradi Amani

  • SMERS: Music emotion recognition using support vector regression

    Byeong Jun Han;Seungmin Rho;Roger B. Dannenberg;Eenjun Hwang

Frequent Co-Authors

Anand Paul
Anand Paul Kyungpook National University
Sung Wook Baik
Sung Wook Baik Sejong University
Irfan Mehmood
Irfan Mehmood University of Bradford
Naveen Chilamkurti
Naveen Chilamkurti La Trobe University
Feng Jiang
Feng Jiang Harbin Institute of Technology
Muhammad Sajjad
Muhammad Sajjad Islamia College University
Awais Ahmad
Awais Ahmad University of Milan
Yunyoung Nam
Yunyoung Nam Soonchunhyang University
Khan Muhammad
Khan Muhammad Sungkyunkwan University
Sohail Jabbar
Sohail Jabbar Manchester Metropolitan University

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