| Discipline name | D-Index | World Ranking | Current World Ranking | National Ranking | Current National Ranking | Publications | Citations |
|---|---|---|---|---|---|---|---|
| Rising Stars | 40 | 643 | 643 | 226 | 226 | 142 | 9143 |
| Computer Science | 47 | 6368 | 6184 | 846 | 840 | 185 | 12211 |
The chart shows the history of publications by Hong Ren between 2013 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Hong Ren published across 13 years, from 2013 to 2025, averaging 15.5 papers a year. Output peaked at 40 publications in 2024. 66 of the 201 publications appeared in the last two years.
201 publications in total across all disciplines
| Year | Publications |
|---|---|
| 2013 | 3 |
| 2014 | 2 |
| 2015 | 7 |
| 2016 | 3 |
| 2017 | 4 |
| 2018 | 4 |
| 2019 | 15 |
| 2020 | 30 |
| 2021 | 35 |
| 2022 | 16 |
| 2023 | 16 |
| 2024 | 40 |
| 2025 | 26 |
| Total | 201 |
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 Hong Ren sits on this spectrum.
This scientist: 185 publications — 41st percentile
41% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 991 publications or more.
| 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 | 185 |
| 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 | |
| 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 |
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 Hong Ren sits on this spectrum.
This scientist: 47 D-Index — 56th percentile
56% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 131 D-Index or more.
| 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 | 47 |
| 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 | |
| 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 |
Hong Ren is affiliated with Southeast University in China and specializes in Engineering, with a focus on Electrical and Electronic Engineering, Aerospace Engineering, and Computer Networks and Communications among other subfields.
Their research predominantly covers topics related to advanced wireless communication technologies, including advanced MIMO systems optimization, antenna design and analysis, wireless communication security techniques, satellite communication systems, millimeter-wave propagation and modeling, and indoor and outdoor localization technologies.
Hong Ren has contributed extensively to the academic literature, with frequent publications in venues such as:
Their recent papers include:
The scientist frequently collaborates with several co-authors, including Cunhua Pan, Kezhi Wang, Jiangzhou Wang, Maged Elkashlan, and Kangda Zhi, reflecting a collaborative approach across multiple research projects.
Cunhua Pan;Hong Ren;Kezhi Wang;Wei Xu
Cunhua Pan;Hong Ren;Kezhi Wang;Jonas Florentin Kolb
Cunhua Pan;Hong Ren;Kezhi Wang;Maged Elkashlan
Cunhua Pan;Hong Ren;Kezhi Wang;Maged Elkashlan
Gui Zhou;Cunhua Pan;Hong Ren;Kezhi Wang
Gui Zhou;Cunhua Pan;Hong Ren;Kezhi Wang
Sheng Hong;Cunhua Pan;Hong Ren;Kezhi Wang
Gui Zhou;Cunhua Pan;Hong Ren;Kezhi Wang
Gui Zhou;Cunhua Pan;Hong Ren;Petar Popovski
Kangda Zhi;Cunhua Pan;Hong Ren;Kezhi Wang
Sheng Hong;Cunhua Pan;Hong Ren;Kezhi Wang
Tong Bai;Cunhua Pan;Hong Ren;Yansha Deng
Cunhua Pan;Hong Ren;Yansha Deng;Maged Elkashlan
Wence Zhang;Hong Ren;Cunhua Pan;Ming Chen
Unknown
Hong Ren;Cunhua Pan;Yansha Deng;Maged Elkashlan
Hong Ren;Kezhi Wang;Cunhua Pan
Gui Zhou;Cunhua Pan;Hong Ren;Kezhi Wang
Hong Ren;Cunhua Pan;Yansha Deng;Maged Elkashlan
Hong Ren;Cunhua Pan;Yansha Deng;Maged Elkashlan
Cunhua Pan;Hong Ren;Kezhi Wang;Wei Xu
Hong Ren;Cunhua Pan;Yansha Deng;Maged Elkashlan
If you think any of the details on this page are incorrect, let us know.
Exploring a Computer Science journey in the USA opens up numerous online learning opportunities. Many students now choose the fastest online degree paths to quickly launch a high-paying tech career. Whether you’re aiming to upskill or change industries, accelerated programs let you earn credentials faster while balancing work and studies.
Specializations like artificial intelligence are increasingly popular. Securing an ai online degree can position you at the cutting edge of innovation—this field is growing rapidly and demand for AI talent remains high.
Choosing the right degree is essential. Reviewing the majors that offer strong job prospects and earning potential can help you make a smart, future-ready decision. If you’re seeking further study, you might also be interested in learning about what is the easiest masters degree to get, streamlining your educational experience without sacrificing professional opportunities.
These options empower students to build flexible career pathways within and beyond computer science, no matter your starting point.
University of California, Irvine
Carnegie Mellon University
Simon Fraser University
Sapienza University of Rome
University of New South Wales
Spanish National Research Council
Northwestern University
University of California, San Francisco
New Mexico Institute of Mining and Technology
Cold Spring Harbor Laboratory
University of Chicago
University of Pisa
Spanish National Research Council
Autonomous University of Barcelona
Centers for Disease Control and Prevention
University of Palermo