World's Best Scientists 2026 revealed!
Paul J. Rullkoetter

Paul J. Rullkoetter

D-Index & Metrics

Mechanical and Aerospace Engineering

D-Index
40
Citations
5012
World Ranking
2071
National Ranking
768

Paul J. Rullkoetter publication distribution in Mechanical and Aerospace Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mechanical and Aerospace Engineering in 2026. The highlighted bar marks where Paul J. Rullkoetter sits on this spectrum.

47–56 publications: 10 scientists 57–66 publications: 23 scientists 67–76 publications: 32 scientists 77–86 publications: 62 scientists 87–96 publications: 67 scientists 97–106 publications: 91 scientists 107–116 publications: 113 scientists 117–126 publications: 115 scientists 127–136 publications: 130 scientists 137–146 publications: 140 scientists 147–156 publications: 155 scientists 157–166 publications: 132 scientists 167–176 publications: 133 scientists 177–186 publications: 130 scientists 187–196 publications: 140 scientists 197–206 publications: 115 scientists 207–216 publications: 125 scientists 217–226 publications: 117 scientists 227–236 publications: 99 scientists 237–246 publications: 92 scientists 247–256 publications: 100 scientists 257–266 publications: 95 scientists 267–276 publications: 88 scientists 277–286 publications: 77 scientists 287–296 publications: 74 scientists 297–306 publications: 74 scientists 307–316 publications: 62 scientists 317–326 publications: 70 scientists 327–336 publications: 59 scientists 337–346 publications: 58 scientists 347–356 publications: 45 scientists 357–366 publications: 44 scientists 367–376 publications: 36 scientists 377–386 publications: 41 scientists 387–396 publications: 32 scientists 397–406 publications: 23 scientists 407–416 publications: 28 scientists 417–426 publications: 27 scientists 427–436 publications: 25 scientists 437–446 publications: 23 scientists 447–456 publications: 23 scientists 457–466 publications: 20 scientists 467–476 publications: 12 scientists 477–486 publications: 24 scientists 487–496 publications: 18 scientists 497–506 publications: 12 scientists 507–516 publications: 13 scientists 517–526 publications: 21 scientists 527–536 publications: 12 scientists 537–546 publications: 8 scientists 547–556 publications: 16 scientists 557–566 publications: 3 scientists 567–576 publications: 11 scientists 577–586 publications: 6 scientists 587–596 publications: 5 scientists 597–606 publications: 6 scientists 607–616 publications: 7 scientists 617–626 publications: 7 scientists 627–636 publications: 10 scientists 637–646 publications: 4 scientists 647–656 publications: 3 scientists 657–658 publications: 2 scientists 659+ publications: 100 scientists
47 publications 659+

This scientist: 149 publications — 24th percentile

24% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 659 publications or more.

Paul J. Rullkoetter D-index placement in Mechanical and Aerospace Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Mechanical and Aerospace Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Paul J. Rullkoetter sits on this spectrum.

30 D-Index: 83 scientists 31 D-Index: 113 scientists 32 D-Index: 144 scientists 33 D-Index: 153 scientists 34 D-Index: 189 scientists 35 D-Index: 158 scientists 36 D-Index: 139 scientists 37 D-Index: 127 scientists 38 D-Index: 130 scientists 39 D-Index: 126 scientists 40 D-Index: 104 scientists 41 D-Index: 100 scientists 42 D-Index: 107 scientists 43 D-Index: 101 scientists 44 D-Index: 103 scientists 45 D-Index: 79 scientists 46 D-Index: 88 scientists 47 D-Index: 70 scientists 48 D-Index: 83 scientists 49 D-Index: 44 scientists 50 D-Index: 64 scientists 51 D-Index: 56 scientists 52 D-Index: 50 scientists 53 D-Index: 48 scientists 54 D-Index: 58 scientists 55 D-Index: 52 scientists 56 D-Index: 48 scientists 57 D-Index: 42 scientists 58 D-Index: 34 scientists 59 D-Index: 42 scientists 60 D-Index: 37 scientists 61 D-Index: 42 scientists 62 D-Index: 44 scientists 63 D-Index: 22 scientists 64 D-Index: 33 scientists 65 D-Index: 29 scientists 66 D-Index: 23 scientists 67 D-Index: 29 scientists 68 D-Index: 24 scientists 69 D-Index: 19 scientists 70 D-Index: 34 scientists 71 D-Index: 26 scientists 72 D-Index: 19 scientists 73 D-Index: 18 scientists 74 D-Index: 19 scientists 75 D-Index: 14 scientists 76 D-Index: 19 scientists 77 D-Index: 8 scientists 78 D-Index: 18 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 17 scientists 82 D-Index: 11 scientists 83 D-Index: 16 scientists 84 D-Index: 7 scientists 85 D-Index: 9 scientists 86 D-Index: 8 scientists 87 D-Index: 6 scientists 88 D-Index: 6 scientists 89 D-Index: 7 scientists 90 D-Index: 10 scientists 91 D-Index: 4 scientists 92 D-Index: 4 scientists 93+ D-Index: 100 scientists
30 D-Index 93+

This scientist: 40 D-Index — 43rd percentile

43% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 93 D-Index or more.

Overview

Paul J. Rullkoetter is affiliated with the University of Denver in the United States and has contributed extensively to the fields of medicine and engineering, with a focus on surgery and biomedical engineering. Their research encompasses a wide range of topics related to orthopedics, biomechanics, and arthroplasty.

The primary fields of study for Paul J. Rullkoetter include:

  • Medicine
  • Engineering

In terms of subfields, their work is concentrated in:

  • Surgery
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Endocrinology, Diabetes and Metabolism
  • Orthopedics and Sports Medicine

The main research topics Paul J. Rullkoetter has explored are:

  • Total Knee Arthroplasty Outcomes
  • Orthopaedic implants and arthroplasty
  • Orthopedic Infections and Treatments
  • Lower Extremity Biomechanics and Pathologies
  • Knee injuries and reconstruction techniques
  • Muscle activation and electromyography studies
  • Hip disorders and treatments

Paul J. Rullkoetter has published in several academic venues, with the most frequent publication outlets including:

  • Journal of Biomechanics
  • Journal of Orthopaedic Research®
  • Journal of the mechanical behavior of biomedical materials/Journal of mechanical behavior of biomedical materials
  • Frontiers in Bioengineering and Biotechnology
  • Computers in Biology and Medicine

Frequent collaborators in Paul J. Rullkoetter's research include:

  • Casey A. Myers
  • Chadd W. Clary
  • Kevin B. Shelburne
  • William Burton
  • Huizhou Yang

Some recent papers authored by or involving Paul J. Rullkoetter are:

  • Machine learning for rapid estimation of lower extremity muscle and joint loading during activities of daily living (2021, Journal of Biomechanics)
  • Semi-supervised learning for automatic segmentation of the knee from MRI with convolutional neural networks (2020, Computer Methods and Programs in Biomedicine)
  • Joint Track Machine Learning: An Autonomous Method of Measuring Total Knee Arthroplasty Kinematics From Single-Plane X-Ray Images (2023, The Journal of Arthroplasty)
  • Validation and sensitivity of model-predicted proximal tibial displacement and tray micromotion in cementless total knee arthroplasty under physiological loading conditions (2020, Journal of the mechanical behavior of biomedical materials/Journal of mechanical behavior of biomedical materials)
  • Supine leg press as an alternative to standing lunge in high-speed stereo radiography (2022, Journal of Biomechanics)

Best Publications

  • Explicit finite element modeling of total knee replacement mechanics

    Jason P. Halloran;Anthony J. Petrella;Paul J. Rullkoetter

  • The effect of valgus/varus malalignment on load distribution in total knee replacements

    Frederick W. Werner;David C. Ayers;Lorin P. Maletsky;Paul J. Rullkoetter

  • Dynamic finite element knee simulation for evaluation of knee replacement mechanics.

    Mark A. Baldwin;Chadd W. Clary;Chadd W. Clary;Clare K. Fitzpatrick;James S. Deacy

  • Comparison of long-term numerical and experimental total knee replacement wear during simulated gait loading.

    Lucy A. Knight;Saikat Pal;John C. Coleman;Fred Bronson

  • Development of subject-specific and statistical shape models of the knee using an efficient segmentation and mesh-morphing approach

    Mark A. Baldwin;Joseph E. Langenderfer;Paul J. Rullkoetter;Peter J. Laz

  • The influence of total knee arthroplasty geometry on mid-flexion stability: an experimental and finite element study.

    Chadd W. Clary;Chadd W. Clary;Clare K. Fitzpatrick;Lorin P. Maletsky;Paul J. Rullkoetter

  • Comparison of Deformable and Elastic Foundation Finite Element Simulations for Predicting Knee Replacement Mechanics

    Jason P. Halloran;Sarah K. Easley;Anthony J. Petrella;Paul J. Rullkoetter

  • Finite element simulation of early creep and wear in total hip arthroplasty.

    Scott L. Bevill;Grant R. Bevill;Janaki R. Penmetsa;Anthony J. Petrella

  • Finite element-based probabilistic analysis tool for orthopaedic applications

    Sarah K. Easley;Saikat Pal;Paul R. Tomaszewski;Anthony J. Petrella

  • Verification of predicted specimen-specific natural and implanted patellofemoral kinematics during simulated deep knee bend

    Mark A. Baldwin;Chadd Clary;Lorin P. Maletsky;Paul J. Rullkoetter

  • Development of a statistical shape model of the patellofemoral joint for investigating relationships between shape and function.

    Clare K. Fitzpatrick;Mark A. Baldwin;Peter J. Laz;David P. FitzPatrick

  • A statistical finite element model of the knee accounting for shape and alignment variability

    Chandreshwar Rao;Clare K. Fitzpatrick;Paul J. Rullkoetter;Lorin P. Maletsky

  • Verification of predicted knee replacement kinematics during simulated gait in the Kansas knee simulator

    Jason P. Halloran;Chadd W. Clary;Lorin P. Maletsky;Mark Taylor

  • Specimen-specific modeling of hip fracture pattern and repair

    Azhar A. Ali;Luca Cristofolini;Enrico Schileo;Haixiang Hu

  • Incorporating uncertainty in mechanical properties for finite element-based evaluation of bone mechanics

    Peter J. Laz;Joshua Q. Stowe;Mark A. Baldwin;Anthony J. Petrella

  • The role of patient, surgical, and implant design variation in total knee replacement performance

    Clare K. Fitzpatrick;Chadd W. Clary;Paul J. Rullkoetter

  • Probabilistic computational modeling of total knee replacement wear

    Saikat Pal;Hani Haider;Peter J. Laz;Lucy A. Knight

  • Computational analysis of factors contributing to patellar dislocation.

    Clare K. Fitzpatrick;Robert N. Steensen;Aruna Tumuluri;Thai Trinh

  • Validation of predicted patellofemoral mechanics in a finite element model of the healthy and cruciate-deficient knee.

    Azhar A. Ali;Sami S. Shalhoub;Adam J. Cyr;Clare K. Fitzpatrick

  • Probabilistic finite element prediction of knee wear simulator mechanics.

    Peter J. Laz;Saikat Pal;Jason P. Halloran;Anthony J. Petrella

  • A Combined Experimental and Computational Approach to Subject-Specific Analysis of Knee Joint Laxity.

    Michael D. Harris;Adam J. Cyr;Azhar A. Ali;Clare K. Fitzpatrick

Frequent Co-Authors

Mark Taylor
Mark Taylor Flinders University
Darryl D. D'Lima
Darryl D. D'Lima Scripps Health
Scott A. Banks
Scott A. Banks University of Florida
Richard D. Komistek
Richard D. Komistek University of Tennessee at Knoxville
Richard L. Whitman
Richard L. Whitman United States Geological Survey
Luca Cristofolini
Luca Cristofolini University of Bologna
Fulvia Taddei
Fulvia Taddei Istituto Ortopedico Rizzoli
Mohamed R. Mahfouz
Mohamed R. Mahfouz University of Tennessee at Knoxville

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

Pursuing Mechanical and Aerospace Engineering can open diverse career pathways beyond traditional engineering roles. Many students explore related online degrees to complement their skills or transition into specialized fields. For instance, understanding how much does an online speech pathology degree cost can benefit those interested in the intersection of engineering and healthcare technologies.

Veterans seeking to advance their education will find valuable options, as evidenced by the tailored programs for speech pathology degrees designed with veterans in mind. These programs offer flexibility and support, helping service members transition into civilian careers smoothly.

Accelerated programs also exist for motivated learners. Investigating the best 5 year speech pathology programs can reveal routes to complete degrees faster while still gaining robust practical experience. This approach maximizes time efficiency, ideal for those intent on entering the workforce quickly.

Furthermore, engineering graduates may consider unique career paths such as criminal profiling. Learning about the profiler job, including education, salary, and job outlook, can inspire a shift toward roles that combine analytical skills and investigative work in law enforcement.

Exploring these related degrees and careers expands opportunities, ensuring a well-rounded professional future for those in Mechanical and Aerospace Engineering.

Best Scientists Citing Paul J. Rullkoetter

Trending Scientists

Recently Published Articles