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Jason Cong

D-Index & Metrics

Computer Science

D-Index
101
Citations
37401
World Ranking
353
National Ranking
194

Jason Cong 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 Jason Cong 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: 250 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: 560 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: 424 scientists 242–251 publications: 408 scientists 252–261 publications: 378 scientists 262–271 publications: 300 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: 650 publications — 97th percentile

97% of scientists in this discipline score the same or lower.

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

Jason Cong 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 Jason Cong sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 984 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 969 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 765 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 517 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: 101 D-Index — 98th percentile

98% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2020 - Fellow, National Academy of Inventors
  • 2019 - Semiconductor Industry Association University Researcher Award
  • 2017 - Member of the National Academy of Engineering For pioneering contributions to application-specific programmable logic via innovations in field-programmable gate array synthesis.
  • 2008 - ACM Fellow For contributions to electronic design automation.
  • 2001 - IEEE Fellow For contributions to the computer-aided design of integrated circuits, especially in physical design automation, interconnect optimization, and synthesis of field-programmable gate-arrays.

Overview

Jason Cong is affiliated with the University of California, Los Angeles in the United States. Their research spans multiple scientific disciplines, including Computer Science, Biochemistry, Genetics and Molecular Biology, and Engineering. Key subfields of their work include Biophysics, Molecular Biology, Artificial Intelligence, Computational Theory and Mathematics, and Media Technology.

The scientist's main research topics cover a variety of areas, with notable focus on Cell Image Analysis Techniques, Image Processing Techniques and Applications, Computational Drug Discovery Methods, Machine Learning in Materials Science, Advanced Fluorescence Microscopy Techniques, Quantum Computing Algorithms and Architecture, and Embedded Systems Design Techniques.

Jason Cong has contributed to numerous publications across several venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • SAR and QSAR in environmental research
  • IEEE Design and Test
  • bioRxiv (Cold Spring Harbor Laboratory)

Representative recent papers authored or coauthored by Jason Cong include:

  • "A Survey on Graph Neural Network Acceleration: Algorithms, Systems, and Customized Hardware" (2023), published in arXiv (Cornell University)
  • "Molecular mechanism underlying effect of D93 and D289 protonation states on inhibitor-BACE1 binding: exploration from multiple independent Gaussian accelerated molecular dynamics and deep learning" (2024), published in SAR and QSAR in environmental research
  • "Binding mechanism of inhibitors to DFG-in and DFG-out P38α deciphered using multiple independent Gaussian accelerated molecular dynamics simulations and deep learning" (2025), published in SAR and QSAR in environmental research
  • "2019 DAC Roundtable" (2020), published in IEEE Design and Test
  • "Gossamer: Scaling Image Processing and Reconstruction to Whole Brains" (2024), published in bioRxiv (Cold Spring Harbor Laboratory)

Jason Cong collaborates regularly with several researchers, including:

  • Yizhou Sun
  • Karl Marrett
  • Keivan Moradi
  • Chris Sin Park
  • Ming Yan

The scientist's work has been recognized with multiple awards. These include:

  • Fellow, National Academy of Inventors (2020)
  • Semiconductor Industry Association University Researcher Award (2019)
  • Member of the National Academy of Engineering (2017) for pioneering contributions to application-specific programmable logic via innovations in field-programmable gate array synthesis
  • ACM Fellow (2008) for contributions to electronic design automation
  • IEEE Fellow (2001) for contributions to the computer-aided design of integrated circuits, especially in physical design automation, interconnect optimization, and synthesis of field-programmable gate-arrays

Best Publications

  • Optimizing FPGA-based Accelerator Design for Deep Convolutional Neural Networks

    Chen Zhang;Peng Li;Guangyu Sun;Yijin Guan

  • High-Level Synthesis for FPGAs: From Prototyping to Deployment

    Jason Cong;Bin Liu;Stephen Neuendorffer;Juanjo Noguera

  • FlowMap: an optimal technology mapping algorithm for delay optimization in lookup-table based FPGA designs

    J. Cong;Yuzheng Ding

  • Caffeine: Toward Uniformed Representation and Acceleration for Deep Convolutional Neural Networks

    Chen Zhang;Guangyu Sun;Zhenman Fang;Peipei Zhou

  • A thermal-driven floorplanning algorithm for 3D ICs

    J. Cong;Jie Wei;Yan Zhang

  • Scaling for edge inference of deep neural networks

    Xiaowei Xu;Yukun Ding;Sharon Xiaobo Hu;Michael Niemier

  • Minimizing Computation in Convolutional Neural Networks

    Jason Cong;Bingjun Xiao

  • Automated Systolic Array Architecture Synthesis for High Throughput CNN Inference on FPGAs

    Xuechao Wei;Cody Hao Yu;Peng Zhang;Youxiang Chen

  • Performance optimization of VLSI interconnect layout

    Jason Cong;Lei He;Cheng-Kok Koh;Patrick H. Madden

  • On area/depth trade-off in LUT-based FPGA technology mapping

    J. Cong;Yuzheng Ding

  • An interconnect-centric design flow for nanometer technologies

    J. Cong

  • CMP network-on-chip overlaid with multi-band RF-interconnect

    M.F. Chang;J. Cong;A. Kaplan;M. Naik

  • FP-DNN: An Automated Framework for Mapping Deep Neural Networks onto FPGAs with RTL-HLS Hybrid Templates

    Yijin Guan;Hao Liang;Ningyi Xu;Wenqiang Wang

  • Application-specific instruction generation for configurable processor architectures

    Jason Cong;Yiping Fan;Guoling Han;Zhiru Zhang

  • Combinational logic synthesis for LUT based field programmable gate arrays

    Jason Cong;Yuzheng Ding

  • SACNN: Self-Attention Convolutional Neural Network for Low-Dose CT Denoising With Self-Supervised Perceptual Loss Network

    Meng Li;William Hsu;Xiaodong Xie;Jason Cong

  • Caffeine: towards uniformed representation and acceleration for deep convolutional neural networks

    Chen Zhang;Zhenman Fang;Peipei Zhou;Peichen Pan

  • Provably good performance-driven global routing

    J. Cong;A.B. Kahng;G. Robins;M. Sarrafzadeh

  • Interconnect design for deep submicron ICs

    Jason Cong;Zhigang Pan;Lei He;Cheng-Kok Koh

  • Routability-Driven Placement and White Space Allocation

    Chen Li;Min Xie;Cheng-Kok Koh;J. Cong

  • A scalable micro wireless interconnect structure for CMPs

    Suk-Bok Lee;Sai-Wang Tam;Ioannis Pefkianakis;Songwu Lu

  • Three Dimensional Integrated Circuit Design

    Yuan Xie;Jason Cong;Sachin Sapatnekar

Frequent Co-Authors

Glenn Reinman
Glenn Reinman University of California, Los Angeles
Deming Chen
Deming Chen University of Illinois at Urbana-Champaign
Mau-Chung Frank Chang
Mau-Chung Frank Chang University of California, Los Angeles
Andrew B. Kahng
Andrew B. Kahng University of California, San Diego
Cheng-Kok Koh
Cheng-Kok Koh Purdue University West Lafayette
Lei He
Lei He University of California, Los Angeles
Guangyu Sun
Guangyu Sun Peking University
Tony F. Chan
Tony F. Chan University of California, Los Angeles
Yun Liang
Yun Liang Peking University
Majid Sarrafzadeh
Majid Sarrafzadeh University of California, Los Angeles

External Links

Wikipedia of Jason Cong Personal website of Jason Cong Google Scholar page

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Best Scientists Citing Jason Cong

Andrew B. Kahng

Andrew B. Kahng

University of California, San Diego

Publications: 121

Yao-Wen Chang

Yao-Wen Chang

National Taiwan University

Publications: 106

Charles J. Alpert

Charles J. Alpert

Cadence Design Systems

Publications: 92

Deming Chen

Deming Chen

University of Illinois at Urbana-Champaign

Publications: 84

Sachin S. Sapatnekar

Sachin S. Sapatnekar

University of Minnesota

Publications: 81

Lei He

Lei He

University of California, Los Angeles

Publications: 79

Sung Kyu Lim

Sung Kyu Lim

Georgia Institute of Technology

Publications: 76

Igor L. Markov

Igor L. Markov

Synopsys (United States)

Publications: 73

Jiang Hu

Jiang Hu

Texas A&M University

Publications: 72

Yuan Xie

Yuan Xie

Hong Kong University of Science and Technology

Publications: 60

D. F. Wong

D. F. Wong

University of Illinois at Urbana-Champaign

Publications: 60

Malgorzata Marek-Sadowska

Malgorzata Marek-Sadowska

University of California, Santa Barbara

Publications: 58

Wayne Luk

Wayne Luk

Imperial College London

Publications: 57

Chung-Kuan Cheng

Chung-Kuan Cheng

University of California, San Diego

Publications: 56

Chris Chu

Chris Chu

Iowa State University

Publications: 56

Luca Benini

Luca Benini

ETH Zurich

Publications: 56

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