World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
40
Citations
8035
World Ranking
7217
National Ranking
1974

Mark Lawley 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 Mark Lawley sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 134 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: 117 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: 59 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 publications 804+

This scientist: 120 publications — 15th percentile

15% of scientists in this discipline score the same or lower.

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

Mark Lawley 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 Mark Lawley sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 128 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: 349 scientists 41 D-Index: 362 scientists 42 D-Index: 425 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: 94 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: 24 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: 40 D-Index — 27th percentile

27% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Mark Lawley is affiliated with Texas A&M University in the United States. Their research primarily focuses on Medicine, with a body of work addressing several subfields including Cardiology and Cardiovascular Medicine, Endocrinology, Diabetes and Metabolism, Public Health, Environmental and Occupational Health, Emergency Medicine, and General Health Professions.

The scientist's research topics include Diabetes Management and Research, Mosquito-borne Diseases and Control, Blood Pressure and Hypertension Studies, Healthcare Operations and Scheduling Optimization, Healthcare Policy and Management, Diabetes and Associated Disorders, and Heart Rate Variability and Autonomic Control.

Major recent papers authored by or involving Mark Lawley include:

  • Feature-Based Machine Learning Model for Real-Time Hypoglycemia Prediction (2020), Journal of Diabetes Science and Technology
  • Improved Low-Glucose Predictive Alerts Based on Sustained Hypoglycemia: Model Development and Validation Study (2021), JMIR Diabetes
  • Making Gene Drive Biodegradable (2020), Philosophical Transactions of the Royal Society B Biological Sciences
  • Predictive Model for Microclimatic Temperature and Its Use in Mosquito Population Modeling (2021), Scientific Reports
  • Economic Evaluation of Blood Pressure Monitoring Techniques in Patients With Hypertension (2023), JAMA Network Open

Mark Lawley's frequent coauthors include Madhav Erraguntla, Hye-Chung Kum, Sulki Park, Darpit Dave, and Kevin M. Myles.

The scientist commonly publishes in the following venues:

  • Journal of Medical Internet Research
  • Scientific Reports
  • Journal of Diabetes Science and Technology
  • JMIR Diabetes
  • JAMA Network Open

Best Publications

  • Residual-life distributions from component degradation signals: A Bayesian approach

    Nagi Z. Gebraeel;Mark A. Lawley;Rong Li;Jennifer K. Ryan

  • EXECUTING PRODUCTION SCHEDULES IN THE FACE OF UNCERTAINTIES: A REVIEW AND SOME FUTURE DIRECTIONS

    Haldun Aytug;Mark A. Lawley;Kenneth McKay;Shantha Mohan

  • Residual life predictions from vibration-based degradation signals: a neural network approach

    N. Gebraeel;M. Lawley;R. Liu;V. Parmeshwaran

  • A stochastic overbooking model for outpatient clinical scheduling with no-shows

    Kumar Muthuraman;Mark Lawley

  • A Neural Network Integrated Decision Support System for Condition-Based Optimal Predictive Maintenance Policy

    Sze-jung Wu;N. Gebraeel;M.A. Lawley;Y. Yih

  • A Neural Network Degradation Model for Computing and Updating Residual Life Distributions

    N.Z. Gebraeel;M.A. Lawley

  • Polynomial-complexity deadlock avoidance policies for sequential resource allocation systems

    S.A. Reveliotis;M.A. Lawley;P.M. Ferreira

  • Clinic scheduling models with overbooking for patients with heterogeneous no-show probabilities

    Bo Zeng;Ayten Turkcan;Ji Lin;Mark A. Lawley

  • Using no-show modeling to improve clinic performance.

    Joanne K. Daggy;Mark A. Lawley;Deanna Willis;Debra Thayer

  • Effects of clinical characteristics on successful open access scheduling.

    Renata Kopach;Po Ching DeLaurentis;Mark Lawley;Kumar Muthuraman

  • A correct and scalable deadlock avoidance policy for flexible manufacturing systems

    M.A. Lawley;S.A. Reveliotis;P.M. Ferreira

  • Sequential clinical scheduling with patient no-shows and general service time distributions

    Santanu Chakraborty;Kumar Muthuraman;Mark Lawley

  • Chemotherapy Operations Planning and Scheduling

    Ayten Turkcan;Bo Zeng;Mark Lawley

  • Deadlock avoidance for production systems with flexible routing

    M.A. Lawley

  • Applying Systems Engineering Principles in Improving Health Care Delivery

    Renata Kopach-Konrad;Mark Lawley;Mike Criswell;Imran Hasan

  • Deadlock Avoidance for Sequential Resource Allocation Systems: Hard and Easy Cases

    Mark Lawley;Spyros Reveliotis

  • No-shows to primary care appointments: subsequent acute care utilization among diabetic patients

    Lynn A Nuti;Mark Lawley;Ayten Turkcan;Zhiyi Tian

  • Design Guidelines for Deadlock-Handling Strategies in Flexible Manufacturing Systems

    Mark Lawley;Spiridon Reveliotis;Placid Mathew Ferreira

  • Robust supervisory control policies for manufacturing systems with unreliable resources

    M.A. Lawley;W. Sulistyono

  • Barriers to Remote Health Interventions for Type 2 Diabetes: A Systematic Review and Proposed Classification Scheme

    Michelle M Alvarado;Hye-Chung Kum;Hye-Chung Kum;Karla Gonzalez Coronado;Margaret J Foster

  • The Application and Evaluation of Banker's Algorithm for Deadlock-Free Buffer Space Allocation in Flexible Manufacturing Systems

    Mark Lawley;Spyros Reveliotis;Placid Ferreira

Frequent Co-Authors

Placid Mathew Ferreira
Placid Mathew Ferreira University of Illinois at Urbana-Champaign
Yuehwern Yih
Yuehwern Yih Purdue University West Lafayette
José A. Pagán
José A. Pagán New York University
Khalid A. Qaraqe
Khalid A. Qaraqe Hamad bin Khalifa University
Qammer H. Abbasi
Qammer H. Abbasi University of Glasgow
Reha Uzsoy
Reha Uzsoy North Carolina State University
William M. Tierney
William M. Tierney The University of Texas at Austin
Michael A. Morrisey
Michael A. Morrisey Texas A&M University
Makoto Kaneko
Makoto Kaneko Osaka University
László Monostori
László Monostori Budapest University of Technology and Economics

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:

Best Scientists Citing Mark Lawley

Trending Scientists

Recently Published Articles