World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
44
Citations
11664
World Ranking
1549
National Ranking
669

Computer Science

D-Index
46
Citations
14157
World Ranking
6686
National Ranking
2952

Han Liu publication distribution in Mathematics in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mathematics in 2026. The highlighted bar marks where Han Liu sits on this spectrum.

42–46 publications: 3 scientists 47–51 publications: 5 scientists 52–56 publications: 7 scientists 57–61 publications: 20 scientists 62–66 publications: 14 scientists 67–71 publications: 25 scientists 72–76 publications: 19 scientists 77–81 publications: 35 scientists 82–86 publications: 50 scientists 87–91 publications: 60 scientists 92–96 publications: 86 scientists 97–101 publications: 84 scientists 102–106 publications: 83 scientists 107–111 publications: 90 scientists 112–116 publications: 99 scientists 117–121 publications: 90 scientists 122–126 publications: 91 scientists 127–131 publications: 109 scientists 132–136 publications: 110 scientists 137–141 publications: 98 scientists 142–146 publications: 112 scientists 147–151 publications: 102 scientists 152–156 publications: 88 scientists 157–161 publications: 106 scientists 162–166 publications: 83 scientists 167–171 publications: 102 scientists 172–176 publications: 77 scientists 177–181 publications: 81 scientists 182–186 publications: 78 scientists 187–191 publications: 71 scientists 192–196 publications: 92 scientists 197–201 publications: 64 scientists 202–206 publications: 69 scientists 207–211 publications: 64 scientists 212–216 publications: 62 scientists 217–221 publications: 58 scientists 222–226 publications: 53 scientists 227–231 publications: 50 scientists 232–236 publications: 46 scientists 237–241 publications: 46 scientists 242–246 publications: 46 scientists 247–251 publications: 43 scientists 252–256 publications: 29 scientists 257–261 publications: 45 scientists 262–266 publications: 30 scientists 267–271 publications: 33 scientists 272–276 publications: 34 scientists 277–281 publications: 30 scientists 282–286 publications: 31 scientists 287–291 publications: 21 scientists 292–296 publications: 34 scientists 297–301 publications: 26 scientists 302–306 publications: 10 scientists 307–311 publications: 17 scientists 312–316 publications: 23 scientists 317–321 publications: 13 scientists 322–326 publications: 16 scientists 327–331 publications: 26 scientists 332–336 publications: 13 scientists 337–341 publications: 13 scientists 342–346 publications: 16 scientists 347–351 publications: 17 scientists 352–356 publications: 12 scientists 357–361 publications: 18 scientists 362–366 publications: 18 scientists 367–371 publications: 9 scientists 372–376 publications: 11 scientists 377–381 publications: 8 scientists 382–386 publications: 8 scientists 387–391 publications: 9 scientists 392–396 publications: 9 scientists 397–401 publications: 8 scientists 402–406 publications: 11 scientists 407–411 publications: 6 scientists 412–416 publications: 6 scientists 417–421 publications: 9 scientists 422–426 publications: 8 scientists 427–431 publications: 5 scientists 432–436 publications: 8 scientists 437–441 publications: 8 scientists 442–446 publications: 4 scientists 447–451 publications: 4 scientists 452–456 publications: 4 scientists 457–461 publications: 2 scientists 462–466 publications: 2 scientists 467–471 publications: 4 scientists 472–476 publications: 3 scientists 477–481 publications: 3 scientists 482–486 publications: 6 scientists 487–491 publications: 3 scientists 492–496 publications: 5 scientists 497–501 publications: 5 scientists 502–506 publications: 1 scientists 507–511 publications: 6 scientists 512–516 publications: 4 scientists 517–521 publications: 1 scientists 522–526 publications: 3 scientists 527–531 publications: 1 scientists 532–536 publications: 4 scientists 537+ publications: 100 scientists
42 publications 537+

This scientist: 189 publications — 57th percentile

57% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 537 publications or more.

Han Liu D-index placement in Mathematics in 2026

The chart shows the D-index (discipline H-index) distribution of Mathematics scientists ranked by Research.com in 2026. The highlighted bar marks where Han Liu sits on this spectrum.

30 D-Index: 174 scientists 31 D-Index: 151 scientists 32 D-Index: 174 scientists 33 D-Index: 117 scientists 34 D-Index: 136 scientists 35 D-Index: 127 scientists 36 D-Index: 145 scientists 37 D-Index: 153 scientists 38 D-Index: 150 scientists 39 D-Index: 150 scientists 40 D-Index: 138 scientists 41 D-Index: 136 scientists 42 D-Index: 93 scientists 43 D-Index: 108 scientists 44 D-Index: 115 scientists 45 D-Index: 112 scientists 46 D-Index: 103 scientists 47 D-Index: 75 scientists 48 D-Index: 59 scientists 49 D-Index: 67 scientists 50 D-Index: 60 scientists 51 D-Index: 57 scientists 52 D-Index: 59 scientists 53 D-Index: 62 scientists 54 D-Index: 60 scientists 55 D-Index: 50 scientists 56 D-Index: 42 scientists 57 D-Index: 54 scientists 58 D-Index: 50 scientists 59 D-Index: 42 scientists 60 D-Index: 41 scientists 61 D-Index: 35 scientists 62 D-Index: 40 scientists 63 D-Index: 21 scientists 64 D-Index: 31 scientists 65 D-Index: 27 scientists 66 D-Index: 29 scientists 67 D-Index: 19 scientists 68 D-Index: 25 scientists 69 D-Index: 17 scientists 70 D-Index: 18 scientists 71 D-Index: 12 scientists 72 D-Index: 14 scientists 73 D-Index: 13 scientists 74 D-Index: 18 scientists 75 D-Index: 9 scientists 76 D-Index: 11 scientists 77 D-Index: 10 scientists 78 D-Index: 9 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 10 scientists 82 D-Index: 5 scientists 83 D-Index: 5 scientists 84 D-Index: 13 scientists 85 D-Index: 6 scientists 86+ D-Index: 99 scientists
30 D-Index 86+

This scientist: 44 D-Index — 58th percentile

58% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 86 D-Index or more.

Overview

Han Liu is a researcher affiliated with Northwestern University in the United States, specializing primarily in the field of Computer Science with a focus on Artificial Intelligence. Their scholarly contributions span multiple subfields, including Computer Vision and Pattern Recognition, Signal Processing, Radiology, Nuclear Medicine and Imaging, and Information Systems.

Their research topics cover a variety of areas related to machine intelligence and data analysis. These include:

  • Topic Modeling
  • Machine Learning and Data Classification
  • Advanced Neural Network Applications
  • Anomaly Detection Techniques and Applications
  • Natural Language Processing Techniques
  • Machine Learning and Algorithms
  • Domain Adaptation and Few-Shot Learning

Han Liu has published numerous papers in well-recognized venues. Notable recent publications include:

  • "Deep Learning Based Fusion Approach for Hate Speech Detection," 2020, IEEE Access
  • "A survey on epistemic (model) uncertainty in supervised learning: Recent advances and applications," 2021, Neurocomputing
  • "Human posture recognition based on multiple features and rule learning," 2020, International Journal of Machine Learning and Cybernetics
  • "Multi-Feature Input Deep Forest for EEG-Based Emotion Recognition," 2021, Frontiers in Neurorobotics
  • "Feature Selection Using Enhanced Particle Swarm Optimisation for Classification Models," 2021, Sensors

Their work has appeared frequently in journals and conferences such as arXiv, the International Journal of Machine Learning and Cybernetics, Sensors, the Proceedings of the AAAI Conference on Artificial Intelligence, and IEEE Access. Among these venues, arXiv has been the platform for 24 of their publications.

Collaborations with other researchers form an important component of Han Liu's work. Frequent co-authors include İpek Oğuz, Dewei Hu, Benoît M. Dawant, Qin Zhang, and Xizhao Wang, with collaborative counts ranging from three to eight papers.

Best Publications

  • Patterns and rates of exonic de novo mutations in autism spectrum disorders

    Benjamin M. Neale;Yan Kou;Li Liu;Avi Ma'Ayan

  • Challenges of Big Data analysis

    Jianqing Fan;Fang Han;Han Liu

  • The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs

    Han Liu;John Lafferty;Larry Wasserman

  • Sparse Additive Models

    Pradeep Ravikumar;John Lafferty;Han Liu;Larry Wasserman

  • High Dimensional Semiparametric Gaussian Copula Graphical Models.

    Han Liu;Fang Han;Ming Yuan;John D. Lafferty

  • The huge package for high-dimensional undirected graph estimation in R

    Tuo Zhao;Han Liu;Kathryn Roeder;John Lafferty

  • Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models

    Han Liu;Kathryn Roeder;Larry Wasserman

  • An overview of the estimation of large covariance and precision matrices

    Jianqing Fan;Yuan Liao;Han Liu

  • Fully decentralized multi-agent reinforcement learning with networked agents

    Kaiqing Zhang;Zhuoran Yang;Han Liu;Tong Zhang

  • A general theory of hypothesis tests and confidence regions for sparse high dimensional models

    Yang Ning;Yang Ning;Han Liu

  • Blockwise coordinate descent procedures for the multi-task lasso, with applications to neural semantic basis discovery

    Han Liu;Mark Palatucci;Jian Zhang

  • Stochastic compositional gradient descent: algorithms for minimizing compositions of expected-value functions

    Mengdi Wang;Ethan X. Fang;Han Liu

  • OPTIMAL COMPUTATIONAL AND STATISTICAL RATES OF CONVERGENCE FOR SPARSE NONCONVEX LEARNING PROBLEMS.

    Zhaoran Wang;Han Liu;Tong Zhang

  • A STRICTLY CONTRACTIVE PEACEMAN-RACHFORD SPLITTING METHOD FOR CONVEX PROGRAMMING.

    Bingsheng He;Han Liu;Zhaoran Wang;Xiaoming Yuan

  • DISTRIBUTED TESTING AND ESTIMATION UNDER SPARSE HIGH DIMENSIONAL MODELS.

    Heather Battey;Heather Battey;Jianqing Fan;Jianqing Fan;Han Liu;Junwei Lu

  • SpAM: Sparse Additive Models

    Han Liu;Larry Wasserman;John D. Lafferty;Pradeep K. Ravikumar

  • Automated diagnoses of attention deficit hyperactive disorder using magnetic resonance imaging.

    Ani Eloyan;John Muschelli;John Muschelli;Mary Beth Nebel;Han Liu

  • A nonconvex optimization framework for low rank matrix estimation

    Tuo Zhao;Zhaoran Wang;Han Liu

  • Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Space

    Jiechao Xiong;Qing Wang;Zhuoran Yang;Peng Sun

  • A PARTIALLY LINEAR FRAMEWORK FOR MASSIVE HETEROGENEOUS DATA.

    Tianqi Zhao;Guang Cheng;Han Liu

  • An Overview on the Estimation of Large Covariance and Precision Matrices

    Jianqing Fan;Yuan Liao;Han Liu

  • The Nonparanormal SKEPTIC

    Han Liu;Fang Han;Ming Yuan;Larry Wasserman

Frequent Co-Authors

Larry Wasserman
Larry Wasserman Carnegie Mellon University
Tong Zhang
Tong Zhang University of Illinois at Urbana-Champaign
John Lafferty
John Lafferty Yale University
Jianqing Fan
Jianqing Fan Princeton University
Quanquan Gu
Quanquan Gu University of California, Los Angeles
Kathryn Roeder
Kathryn Roeder Carnegie Mellon University
Xi Chen
Xi Chen Columbia University
Tok Wang Ling
Tok Wang Ling National University of Singapore
Ming Yuan
Ming Yuan Columbia University
Ji Liu
Ji Liu Facebook (United States)

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

For students studying Mathematics in the USA, exploring related online degrees can enhance career options. Many professionals combine math skills with business knowledge by pursuing an easiest mba to enter management fields quickly. These programs often offer flexible schedules ideal for working students.

Online education has expanded access to advanced qualifications. Those seeking convenience and quality may consider the easiest online mba degree programs, which provide a streamlined curriculum without sacrificing depth. This path suits math graduates aiming for leadership roles.

For those interested in research and academia, pursuing a Doctor of Business Administration (DBA) can be a goal. Opting for the cheapest dba online programs allows candidates to minimize debt while advancing their expertise in data-driven business strategies.

Mathematics graduates with finance interest may also explore affordable master's options. The cheapest masters in finance can open doors to careers in investment analysis, quantitative finance, or actuarial science, leveraging strong analytical backgrounds.

Best Scientists Citing Han Liu

Trending Scientists

Recently Published Articles