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Li-Ta Hsu

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Engineering and Technology 43 6243 6024 1176 1170 288 6618

Li-Ta Hsu publications per year

The chart shows the history of publications by Li-Ta Hsu between 2001 and 2026, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Li-Ta Hsu published across 26 years, from 2001 to 2026, averaging 12 papers a year. Output peaked at 48 publications in 2023. 31 of the 313 publications appeared in the last two years.

No. of publications
10 20 30 40
Bar chart. Horizontal axis: year, 2001 to 2026. Vertical axis: number of publications, 0 to 48. Peak 48 publications in 2023. 2001: 1 publication 2002: 0 publications 2003: 1 publication 2004: 0 publications 2005: 0 publications 2006: 1 publication 2007: 0 publications 2008: 0 publications 2009: 1 publication 2010: 3 publications 2011: 1 publication 2012: 0 publications 2013: 1 publication 2014: 2 publications 2015: 17 publications 2016: 13 publications 2017: 9 publications 2018: 12 publications 2019: 21 publications 2020: 30 publications 2021: 46 publications 2022: 32 publications 2023: 48 publications 2024: 43 publications 2025: 30 publications 2026: 1 publication
2001 2026

313 publications in total across all disciplines

View publications per year as a table
Li-Ta Hsu: publications per year, 2001 to 2026
Year Publications
2001 1
2002 0
2003 1
2004 0
2005 0
2006 1
2007 0
2008 0
2009 1
2010 3
2011 1
2012 0
2013 1
2014 2
2015 17
2016 13
2017 9
2018 12
2019 21
2020 30
2021 46
2022 32
2023 48
2024 43
2025 30
2026 1
Total 313
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Li-Ta Hsu 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 Li-Ta Hsu sits on this spectrum.

No. of scientists
100 200 300 400
Bar chart with 78 bars. Horizontal axis: publications, 38–47 to 804+. Vertical axis: number of scientists, 0 to 457. Most scientists, 457, have 148–157 publications. The last bar groups every scientist with 804 publications or more. The highlighted bar, 288–297 publications, is where this scientist sits. 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
38–47 publications 804+

This scientist: 288 publications — 74th percentile

74% of scientists in this discipline score the same or lower.

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

View publications distribution as a table
Number of Engineering and Technology scientists by publication count, Research.com 2026 ranking edition. Based on 9,796 ranked scientists.
Publications Scientists This scientist
38–47 20
48–57 35
58–67 96
68–77 135
78–87 190
88–97 259
98–107 283
108–117 369
118–127 341
128–137 386
138–147 372
148–157 457
158–167 415
168–177 407
178–187 421
188–197 378
198–207 403
208–217 317
218–227 346
228–237 321
238–247 260
248–257 280
258–267 240
268–277 214
278–287 242
288–297 203 288
298–307 166
308–317 154
318–327 175
328–337 159
338–347 99
348–357 131
358–367 106
368–377 118
378–387 97
388–397 108
398–407 82
408–417 71
418–427 64
428–437 55
438–447 54
448–457 60
458–467 47
468–477 40
478–487 30
488–497 29
498–507 38
508–517 40
518–527 32
528–537 23
538–547 28
548–557 23
558–567 19
568–577 16
578–587 17
588–597 18
598–607 22
608–617 15
618–627 9
628–637 11
638–647 21
648–657 12
658–667 9
668–677 11
678–687 9
688–697 6
698–707 14
708–717 7
718–727 8
728–737 10
738–747 9
748–757 5
758–767 5
768–777 11
778–787 7
788–797 2
798–803 4
804+ 100
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Li-Ta Hsu 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 Li-Ta Hsu sits on this spectrum.

No. of scientists
100 200 300 400
Bar chart with 78 bars. Horizontal axis: D-Index, 30 to 107+. Vertical axis: number of scientists, 0 to 426. Most scientists, 426, have 42 D-Index. The last bar groups every scientist with 107 D-Index or more. The highlighted bar, 43 D-Index, is where this scientist sits. 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.

View D-Index distribution as a table
Number of Engineering and Technology scientists by D-index, Research.com 2026 ranking edition. Based on 9,796 ranked scientists.
D-Index Scientists This scientist
30 59
31 114
32 129
33 189
34 200
35 262
36 311
37 312
38 350
39 385
40 348
41 362
42 426
43 380 43
44 310
45 341
46 301
47 306
48 271
49 246
50 210
51 253
52 213
53 221
54 195
55 186
56 170
57 167
58 166
59 144
60 152
61 141
62 138
63 131
64 118
65 114
66 119
67 95
68 87
69 77
70 89
71 69
72 54
73 46
74 55
75 54
76 49
77 53
78 46
79 28
80 39
81 36
82 24
83 26
84 36
85 18
86 25
87 19
88 26
89 27
90 23
91 15
92 12
93 9
94 15
95 10
96 13
97 13
98 9
99 7
100 7
101 8
102 7
103 7
104 9
105 6
106 9
107+ 99
Download as CSV

Overview

Li-Ta Hsu is affiliated with the Hong Kong Polytechnic University in China and has contributed extensively to the field of engineering, with a particular focus on aerospace engineering, electrical and electronic engineering, environmental engineering, computer vision and pattern recognition, and artificial intelligence.

Their research primarily addresses topics in localization technologies, GNSS positioning and interference, inertial sensor and navigation systems, robotics and sensor-based localization, as well as remote sensing and LiDAR applications. Additional topics include 3D surveying and cultural heritage, and target tracking and data fusion in sensor networks.

Recent publications by Li-Ta Hsu illustrate a broad range of interests and impacts. Notable papers include:

  • Factor graph optimization for GNSS/INS integration: A comparison with the extended Kalman filter, 2021, NAVIGATION Journal of the Institute of Navigation
  • UrbanNav:An Open-Sourced Multisensory Dataset for Benchmarking Positioning Algorithms Designed for Urban Areas, 2021, Proceedings of the Satellite Division's International Technical Meeting (Online)/Proceedings of the Satellite Division's International Technical Meeting (CD-ROM)
  • Improving GPS Code Phase Positioning Accuracy in Urban Environments Using Machine Learning, 2020, IEEE Internet of Things Journal
  • Machine learning based LOS/NLOS classifier and robust estimator for GNSS shadow matching, 2020, Satellite Navigation
  • Prediction on the Urban GNSS Measurement Uncertainty Based on Deep Learning Networks With Long Short-Term Memory, 2021, IEEE Sensors Journal

Li-Ta Hsu frequently collaborates with researchers such as Weisong Wen, Guohao Zhang, Hoi-Fung Ng, Bing Xu, and Feng Huang, reflecting ongoing partnerships in their research community.

They often publish in venues such as the Proceedings of the Satellite Division's International Technical Meeting (Online)/Proceedings of the Satellite Division's International Technical Meeting (CD-ROM), arXiv, NAVIGATION Journal of the Institute of Navigation, IEEE Transactions on Intelligent Vehicles, and Proceedings of the Institute of Navigation International Technical Meeting. These venues represent a consistent engagement with both conference proceedings and journal publications related to navigation and intelligent systems.

Best Publications

  • 3D building model-based pedestrian positioning method using GPS/GLONASS/QZSS and its reliability calculation

    Li-Ta Hsu;Yanlei Gu;Shunsuke Kamijo

  • Analysis and modeling GPS NLOS effect in highly urbanized area

    Li Ta Hsu

  • Factor graph optimization for GNSS/INS integration: A comparison with the extended Kalman filter

    Weisong Wen;Tim Pfeifer;Xiwei Bai;Li Ta Hsu

  • GNSS multipath detection using a machine learning approach

    Li-Ta Hsu

  • A gradient boosting decision tree based GPS signal reception classification algorithm

    Rui Sun;Rui Sun;Guanyu Wang;Wenyu Zhang;Li-Ta Hsu

  • Tightly Coupled GNSS/INS Integration via Factor Graph and Aided by Fish-Eye Camera

    Weisong Wen;Xiwei Bai;Yin Chiu Kan;Li-Ta Hsu

  • GPS Error Correction With Pseudorange Evaluation Using Three-Dimensional Maps

    Shunsuke Miura;Li-Ta Hsu;Feiyu Chen;Shunsuke Kamijo

  • Multipath mitigation and NLOS detection using vector tracking in urban environments

    Li-Ta Hsu;Shau-Shiun Jan;Paul D. Groves;Nobuaki Kubo

  • Intelligent GNSS/INS integrated navigation system for a commercial UAV flight control system

    Guohao Zhang;Li Ta Hsu

  • UrbanLoco: A Full Sensor Suite Dataset for Mapping and Localization in Urban Scenes

    Weisong Wen;Yiyang Zhou;Guohao Zhang;Saman Fahandezh-Saadi

  • GNSS/Onboard Inertial Sensor Integration With the Aid of 3-D Building Map for Lane-Level Vehicle Self-Localization in Urban Canyon

    Yanlei Gu;Li-Ta Hsu;Shunsuke Kamijo

  • Multiple Faulty GNSS Measurement Exclusion Based on Consistency Check in Urban Canyons

    Li-Ta Hsu;Hiroko Tokura;Nobuaki Kubo;Yanlei Gu

  • NLOS Correction/Exclusion for GNSS Measurement Using RAIM and City Building Models.

    Li Ta Hsu;Yanlei Gu;Shunsuke Kamijo

  • UrbanNav:An Open-Sourced Multisensory Dataset for Benchmarking Positioning Algorithms Designed for Urban Areas

    Li-Ta Hsu;Nobuaki Kubo;Weisong Wen;Wu Chen

  • Urban Pedestrian Navigation Using Smartphone-Based Dead Reckoning and 3-D Map-Aided GNSS

    Li-Ta Hsu;Yanlei Gu;Yuyang Huang;Shunsuke Kamijo

  • Towards Robust GNSS Positioning and Real-time Kinematic Using Factor Graph Optimization

    Weisong Wen;Li-Ta Hsu

  • Improving GPS Code Phase Positioning Accuracy in Urban Environments Using Machine Learning

    Rui Sun;Guanyu Wang;Qi Cheng;Linxia Fu

  • GNSS NLOS Exclusion Based on Dynamic Object Detection Using LiDAR Point Cloud

    Weisong Weisong Wen;Guohao Zhang;Li-Ta Hsu

  • Prediction on the Urban GNSS Measurement Uncertainty Based on Deep Learning Networks With Long Short-Term Memory

    Guohao Zhang;Penghui Xu;Haosheng Xu;Li-Ta Hsu

  • Machine learning based LOS/NLOS classifier and robust estimator for GNSS shadow matching

    Haosheng Xu;Antonio Angrisano;Salvatore Gaglione;Li-Ta Hsu

  • A New Path Planning Algorithm Using a GNSS Localization Error Map for UAVs in an Urban Area

    Guohao Zhang;Li Ta Hsu

  • Passive Sensor Integration for Vehicle Self-Localization in Urban Traffic Environment

    Yanlei Gu;Li Ta Hsu;Shunsuke Kamijo

  • Vector Tracking Loop-Based GNSS NLOS Detection and Correction: Algorithm Design and Performance Analysis

    Bing Xu;Qiongqiong Jia;Li-Ta Hsu

  • Human-like motion planning model for driving in signalized intersections

    Yanlei Gu;Yoriyoshi Hashimoto;Li-Ta Hsu;Miho Iryo-Asano

  • 3D Mapping Database Aided GNSS Based Collaborative Positioning Using Factor Graph Optimization

    Guohao Zhang;Hoi-Fung Ng;Weisong Wen;Li-Ta Hsu

  • Intelligent GPS L1 LOS/Multipath/NLOS Classifiers Based on Correlator-, RINEX- and NMEA-Level Measurements

    Bing Xu;Qiongqiong Jia;Qiongqiong Jia;Yiran Luo;Yiran Luo;Li Ta Hsu

  • GPS signal reception classification using adaptive neuro-fuzzy inference system

    Rui Sun;Li-Ta Hsu;Dabin Xue;Guohao Zhang

  • Extending Shadow Matching to Tightly-Coupled GNSS/INS Integration System

    Guohao Zhang;Weisong Wen;Bing Xu;Li-Ta Hsu

  • Performance Comparison of GNSS/INS Integrations Based on EKF and Factor Graph Optimization

    Weisong Wen;Yin Chiu Kan;Li Ta Hsu

  • Time-correlated Window Carrier-phase Aided GNSS Positioning Using Factor Graph Optimization for Urban Positioning.

    Xiwei Bai;Weisong Wen;Li-Ta Hsu

  • A GPS spoofing generator using an open sourced vector tracking-based receiver

    Qian Meng;Li Ta Hsu;Bing Xu;Xiapu Luo

Frequent Co-Authors

Washington Y. Ochieng
Washington Y. Ochieng Imperial College London
Masayoshi Tomizuka
Masayoshi Tomizuka University of California, Berkeley
Naser El-Sheimy
Naser El-Sheimy University of Calgary

External Links

Personal website of Li-Ta Hsu

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Best Scientists Citing Li-Ta Hsu

John K. Tsotsos

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Ling Pei

Ling Pei

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Publications: 4

Upamanyu Madhow

Upamanyu Madhow

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Publications: 4

Washington Y. Ochieng

Washington Y. Ochieng

Imperial College London

Publications: 4

Dariu M. Gavrila

Dariu M. Gavrila

Delft University of Technology

Publications: 4

Xiaoji Niu

Xiaoji Niu

Wuhan University

Publications: 4

Mohammad Reza Mosavi

Mohammad Reza Mosavi

Iran University of Science and Technology

Publications: 4

Françoise Clavel-Chapelon

Françoise Clavel-Chapelon

Institut Gustave Roussy

Publications: 3

Marie-Christine Boutron-Ruault

Marie-Christine Boutron-Ruault

University of Paris-Saclay

Publications: 3

Masayoshi Tomizuka

Masayoshi Tomizuka

University of California, Berkeley

Publications: 3

Gérard Lachapelle

Gérard Lachapelle

University of Calgary

Publications: 3

Ching-Yao Chan

Ching-Yao Chan

University of California, Berkeley

Publications: 3

Asad J. Khattak

Asad J. Khattak

University of Tennessee at Knoxville

Publications: 3

Luc Van Gool

Luc Van Gool

Institute for Computer Science, Artificial Intelligence and Technology (INSAIT)

Publications: 3

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Dengxin Dai

Huawei Zurich

Publications: 3

Hugo Ledoux

Hugo Ledoux

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Publications: 3

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