About the Award

International Research Awards on Statistical Methods for Analyzing Engineering Data is an annual award that recognizes exceptional research contributions in the field of statistical methods for engineering data analysis. The award aims to promote innovative research in statistical modeling, simulation, and analysis techniques to enable better decision-making in engineering applications.The award is open to researchers from all over the world who have made significant contributions to the development and application of statistical methods for engineering data analysis. Eligible research topics may include, but are not limited to, statistical inference, regression analysis, time series analysis, design of experiments, Bayesian methods, machine learning, and data visualization.

What does the award include

The profile of the award winners of each category be listed on our website and it will be maintained forever.

The certificate, medal, and Memento, and photographs will be a testimony. Further, this recognition and additional proof of hard work and achievements must be globally accessible for Researchers and hence will be available online 24/7.

It’s an indicator of success Enhances the reputation improves the benchmark –it’s a matter of pride – Motivation – Raises the visibility of the success.

Researcher Awards

Young Scientist Award: This Awarded to researchers who are in the early stage of their career for outstanding research in their field. This award is bestowed in the motive of identifying and Recognizing the young Researchers around the world who have the potential to become leaders n their field. The qualification of the nominee must be recognized and documented by corresponding successes in research contributions, such as Collaborations and Publications. Eligibility: A working professional can nominate for the Award. Research grants for medical students also awarded as scientist awards. He must be below 35 years of age as of the conference date.

Best Researcher Award: This Awarded to the Best researcher in any field for their significant contribution to the advancement in their field of expertise. The qualification of the nominee must be recognized and documented by corresponding successes in research contributions, such as Collaborations, Contracts, and Publications. Eligibility: A working professional can nominate for the Award. There is no age limit for Best Researcher Award category.

Outstanding Scientist Award: Exceptional research record of significant contribution to the institute/company. The qualification of the nominee must be recognized and documented by corresponding successes in research contributions, such as Grants, Patents, Collaborations, Contracts, books, and Publications. Eligibility: A working professional can nominate for the Award. He must be above 35 years of age as of the conference date.

Lifetime Achievement Award: This awards an Exceptional research record of significant contribution to the institute/company. The qualification of the nominee must be recognized and documented by corresponding successes in research contributions, such as Grants, Patents, Collaborations, Contracts, books, and Publications. Eligibility: A working professional can nominate for the Award. He must be above 35 years of age as of the conference date.

Women Researcher Award: Awarded to the Best women researcher in any field for their significant contribution to the advancement in their field of expertise. The qualification of the nominee must be recognized and documented by corresponding successes in research contributions, such as Collaborations, Contracts, and Publications. Eligibility: A working professional can nominate for the Award.

Best Innovation Award: This Awarded to researchers/institutes/Organizations who are in the early stage of their careers for outstanding innovation in their field. This award is bestowed with the motive of identifying and Recognizing the Researchers/institutes/organizations around the world who have the potential to become leaders n their field. The qualification of the nominee must be recognized and documented by corresponding successes in research contributions, such as Collaborations and Publications. Eligibility: A working professional/ Institute/ Organization can nominate for the Award.

Best Faculty Award: This Awarded to the Best Faculty in any field for their significant contribution to the advancement in their field of expertise. The qualification of the nominee must be recognized and documented by corresponding successes in research/ Academic contributions, such as Collaborations, Contracts, and Publications. Eligibility: A working professional can nominate for the Award. He must be under 45 years of age as of the conference date.

Best Scholar Award: This Awarded to Scholar/ Student who are in the early stage of their career for outstanding research in their field. This award is bestowed in the motive of identifying and Recognizing the young Researchers scholar/ Student around the world who have the potential to become leaders n their field. The qualification of the nominee must be recognized and documented by corresponding successes in research contributions, such as Publications. Eligibility: A scholar can nominate for the Award. He must be under 35 years of age as of the conference date.

Institute/ Organization Awards:

Excellence in Innovation: This Awarded to Institute/ Organization/ Business/ Industries who are in the early stage of their career for outstanding innovation in their field. This award is bestowed in the motive of identifying and Recognizing the Institute/ Organization/ Business/ Industries around the world who have the potential to become leaders n their field. The qualification of the nominee must be recognized and documented by corresponding successes in innovation contribution, such as Innovation, Patent, Entrepreneurship, and New project development. Eligibility: A Institute /Organization/ Industries can nominate for the Award.

Excellence in Research: This Awarded to Institute/ Organization/ Business/ Industries who are in the early stage of their career for outstanding research in their field. This award is bestowed in the motive of identifying and Recognizing the Institute/ Organization/ Business/ Industries around the world who have the potential to become leaders n their field. The qualification of the nominee must be recognized and documented by corresponding successes in research contribution, such as publication, research Grants, Research & developments, Entrepreneurship development. Eligibility: A Institute /Organization/ Industries can nominate for the Award.

Excellence Award (Any Scientific field): This Awarded to Institute/ Organization/ Business/ Industries who are in the early stage of their career for outstanding excellence in their field. This award is bestowed in the motive of identifying and Recognizing the Institute/ Organization/ Business/ Industries around the world who have the potential to become leaders n their field. The qualification of the nominee must be recognized and documented by corresponding successes in their field contribution, such as Advancement, New Technology, and Development. Eligibility: A Institute /Organization/ Industries can nominate for the Award.

Best Research /Innovation Extension activity: This Awarded to Institute/ Organization/ Business/ Industries who are in the early stage of their career for outstanding Research/ innovation in their field. This award is bestowed in the motive of identifying and Recognizing the Institute/ Organization/ Business/ Industries around the world who have the potential to become leaders n their field. The qualification of the nominee must be recognized and documented by corresponding successes in their field contribution, such as Extension, Public useful innovation /Research Activities, Innovative services, Awareness programs, and New Technology awareness Development. Eligibility: A Institute /Organization/ Industries can nominate for the Award.

How to Apply

The Candidates with eligibility can click the "Nominate /Submit Your Profile (CV) Now" button and fill up the online submission form and Submit it.

This section describes the total Research Awards processes in step by steps:

1. Received Nomination documents will be sent for the screening process
2. Acknowledgment intimation via email will be communicated to the Nominee
3. The team may ask the proof for the credits mentioned in the Resume.
4. Cross verifying the documents submitted & forwarding it to the Committee.
5. The selected candidate indicated through email. Also, the selected nominees will be checked anytime on the website track of my submission.
6. Event and Celebration Registration
7. Release of the winners list in the official web page
8. Award presentation ceremony
9. Release of the Award winners and his profile Report.

Registration Details

Registration Covers

• An exclusive web page for a highly rated profile of the award winners will always be available online.
• Participation in Award event Session and Keynote session.
• Certificate, Memento, and Photographs.
• Event Kit, Tea, Coffee & Snacks.
• Veg & Non-Veg Lunch during the Event.
• Event and Celebration Registration
• Release of the winners list in the official web page
• Award presentation ceremony
• Release of the Award winners and his profile Report.

Registration Procedure

Click the “Register Now” button at the conference page and enter your Submission ID in the Search Box
Your Submissions will be listed on that page. You can find the Register Now link beside your submission. Click the link and now you will be redirected to the Conference registration form where you can make your registration using credit/debit cards

General Instructions to Nominees

1. The candidates with proper eligibility are requested to submit the online nomination form in order to get nominated for the award
2. If your nomination is accepted by our Judges, we will send you an email regarding your profile selection
3. Awardees must register for the event
4. Dress Code: Award Recipients have to wear a formal dress. There are no restrictions on color or design. The audience attending only the ceremony can wear clothing of their own choice.
5. General Information: Each winner's name will be called & asked to collect their Awards on the Stage with an official photographer to capture the moments.

 

Terms & Conditions

ScienceFather Terms & Conditions Policy was last updated on June 25, 2022

Privacy Policy

This awards  Customer personal information for our legitimate business purposes, to process and respond to inquiries, and provide our services, to manage our relationship with editors, authors, institutional clients, service providers, and other business contacts, to market our services and subscription management. We do not sell, rent/ trade your personal information to third parties.

Relationship

ResearchW awards Operate a Customer Association Management and email list program, which we use to inform customers and other contacts about our services, including our publications and events. Such marketing messages may contain tracking technologies to track subscriber activity relating to engagement, demographics, and other data, and to build subscriber profiles.

Disclaimer

 All editorial matters published on this website represent the opinions of the authors and not necessarily those of the Publisher with the publications. Statements and opinions expressed do not represent the official policies of the relevant associations unless so stated. Every effort has been made to ensure the accuracy of the material that appears on this website. Please ignore, however, that some errors may occur.

Responsibility

Delegates are personally responsible for their belongings at the venue. The Organizers will not be held accountable for any stolen or missing items belonging to Delegates, Speakers, or Attendees; due to any reason whatsoever.

Insurance

Registration fees that do not include insurance of any kind.

Press and Media

Press permission must be getting from the ResearchW Conferences Organizing Committee before the event. The press will not quote speakers or delegates unless they have obtained their approval in writing. This conference is not associated with any commercial meeting company.

Transportation

Please note that any (or) all traffic and parking is the responsibility of the registrant.

Requesting an Invitation Letter

For security purposes, the letter of invitation will be sent only to those individuals who had registered for the conference. Once your registration is complete, please contact contact@ScienceFather.com to request a personalized letter of invitation.

Cancellation Policy

If cancel this event for any reason, you will receive a credit for 100% of the registration fee paid. You may use this credit for another Primary healthcare award which must occur within one year from the date of cancellation.

Postponement Policy

If postpone an event for any reason and you are unable or indisposed to attend on rescheduled dates, you will receive a credit for 100% of the registration fee paid. You may use this credit for another ResearchW event which must occur within one year from the date of postponement.

Transfer of registration

All fully paid registrations are transferable to other persons from the same organization if the registered person is unable to attend the event. The registered person must make transfers in writing to contact@sciencefather.com. Details must include the full name of an alternative person, their title, contact phone number, and email address. All other registration details will be assigned to the new person unless otherwise specified. Registration can be transferred from one conference to another conference of ResearchW if the person is unable to attend one of the meetings. However, Registration cannot be transferred if it will be intimated within 14 days of the particular conference. The transferred registrations will not be eligible for Refund.

Visa Information

Keeping given the increased security measures, we would like to request all the participants to apply for Visa as soon as possible.  Statistical Methods for Analyzing Engineering Data awards will not directly contact embassies and consulates on behalf of visa applicants. All delegates or invitees should apply for Business Visa only. Important note for failed visa applications: Visa issues cannot come under the consideration of the cancellation policy of Statistical Methods awards, including the inability to obtain a visa.

Refund Policy

Regarding refunds, all bank charges will be for the registrant's account. All cancellations or modifications of registration must make in writing to contact@ScienceFather.com

If the registrant is unable to attend and is not in a position to transfer his/her participation to another person or event, then the following refund arrangements apply:

Keeping given advance payments towards Venue, Printing, Shipping, Hotels and other overheads, we had to keep Refund Policy is as following conditions,

Before 60 days of the Conference: Eligible for Full Refund less $100 Service Fee
Within 60-30 days of Conference: Eligible for 50% of payment Refund
Within 30 days of Conference: Not eligible for Refund
E-Poster Payments will not be refunded.

Accommodation Cancellation Policy

 Accommodation Providers such as hotels have their cancellation policies, and they generally apply when cancellations are made less than 30 days before arrival. Please contact us as soon as possible if you wish to cancel or amend your accommodation. ResearchW will advise the cancellation policy of your accommodation provider, before withdrawing or changing your booking, to ensure you are fully aware of any non-refundable deposits.

1. Journal of the American Statistical Association (ASA), USA, 64, 128 | 2. Annals of Statistics, USA, 47, 99 | 3. Journal of Statistical Software, USA, 37, 69 | 4. Biometrika, UK, 35, 97 | 5. Journal of Statistical Planning and Inference, Netherlands, 31, 77 | 6. Journal of the Royal Statistical Society: Series B (Statistical Methodology), UK, 30, 84 | 7. Statistical Science, USA, 27, 64 | 8. Journal of Multivariate Analysis, USA, 26, 68 | 9. Journal of Econometrics, Netherlands, 23, 73 | 10. Statistics and Computing, UK, 20, 47 | 11. Statistica Sinica, Taiwan, 19, 53 | 12. Computational Statistics & Data Analysis, Netherlands, 18, 55 | 13. Journal of Applied Statistics, UK, 16, 32 | 14. Journal of Time Series Analysis, UK, 15, 43 | 15. Journal of Nonparametric Statistics, USA, 14, 42 | 16. Journal of Statistical Mechanics: Theory and Experiment, UK, 13, 33 | 17. Technometrics, USA, 13, 31 | 18. Journal of Statistical Physics, USA, 12, 45 | 19. Journal of Business & Economic Statistics, USA, 11, 41 | 20. Journal of Computational and Graphical Statistics, USA, 10, 39 | 21. Journal of Statistical Computation and Simulation, UK, 10, 30 | 22. Journal of Quality Technology, USA, 10, 22 | 23. Journal of Machine Learning Research, USA, 9, 74 | 24. Journal of Biopharmaceutical Statistics, USA, 9, 26 | 25. Journal of Classification, USA, 9, 24 | 26. Journal of the Royal Statistical Society: Series A (Statistics in Society), UK, 9, 23 | 27. Journal of Statistical Education, USA, 8, 29 | 28. Journal of Environmental Statistics, USA, 8, 19 | 29. Computational Statistics, Switzerland, 8, 15 | 30. Journal of Agricultural, Biological, and Environmental Statistics, USA, 7, 25 | 31. Journal of Official Statistics, Sweden, 7, 24 | 32. Journal of Statistical Planning and Inference, USA, 7, 23 | 33. Biostatistics, USA, 7, 21 | 34. Statistics in Medicine, UK, 7, 21 | 35. Communications in Statistics - Theory and Methods, USA, 7, 20 | 36. Journal of Statistical Theory and Practice, USA, 7, 18 | 37. Journal of Applied Probability, UK, 7, 18 | 38. Journal of Survey Statistics and Methodology, USA, 6, 28 | 39. Journal of Statistical Software, USA, 6, 27 | 40. Sankhya A: Indian Journal of Statistics, India, 6, 23 | 41. Computational Statistics and Data Analysis, UK, 6, 23 | 42. Journal of Statistical Mechanics: Theory and Experiment, USA, 6, 22 | 43. Journal of Statistical Planning and Inference, USA, 6, 22 | 44. Journal of Multivariate Analysis, Netherlands, 6, 20 | 45. Journal of Probability and Statistics, USA, 6, 19 | 46. Communications in Statistics - Simulation and Computation, USA, 6, 19 | 47. Annals of Probability (IMS) - USA - IF: 2.227 - h-index: 114 | 48. Probability Theory and Related Fields (Springer) - Germany - IF: 1.308 - h-index: 97 | 49. Journal of Applied Probability (Cambridge University Press) - UK - IF: 0.912 - h-index: 50 | 50. Stochastic Processes and their Applications (Elsevier) - Netherlands - IF: 1.837 - h-index: 97 | 51. Journal of Probability and Statistics (Hindawi) - Egypt - IF: 1.051 - h-index: 43 | 52. Bernoulli (Bernoulli Society for Mathematical Statistics and Probability) - Switzerland - IF: 1.887 - h-index: 67 | 53. Journal of Theoretical Probability (Springer) - Germany - IF: 0.849 - h-index: 40 | 54. Electronic Journal of Probability (University of Washington) - USA - IF: 1.328 - h-index: 45 | 55. Journal of Mathematical Analysis and Applications (Elsevier) - Netherlands - IF: 1.539 - h-index: 91 | 56. Journal of Statistical Planning and Inference (Elsevier) - Netherlands - IF: 1.352 - h-index: 115 | 57. Statistics and Probability Letters (Elsevier) - Netherlands - IF: 0.740 - h-index: 51 | 58. Journal of Multivariate Analysis (Elsevier) - Netherlands - IF: 1.751 - h-index: 97 | 59. Probability in the Engineering and Informational Sciences (Cambridge University Press) - UK - IF: 0.764 - h-index: 27 | 60. Journal of Probability and Statistics (Hindawi) - Egypt - IF: 1.051 - h-index: 43 | 61. Journal of Applied Statistics (Taylor & Francis) - UK - IF: 0.909 - h-index: 54 | 62. Journal of Nonparametric Statistics (Taylor & Francis) - UK - IF: 0.849 - h-index: 40 | 63. Journal of Statistical Computation and Simulation (Taylor & Francis) - UK - IF: 1.062 - h-index: 63 | 64. Brazilian Journal of Probability and Statistics (Brazilian Statistical Association) - Brazil - IF: 0.534 - h-index: 20 | 65. Journal of Statistical Physics (Springer) - Germany - IF: 1.827 - h-index: 157 | 66. Journal of Time Series Analysis (Wiley) - USA - IF: 1.231 - h-index: 67 | 67. Probability and Mathematical Statistics (Vilnius University Press) - Lithuania - IF: 0.383 - h-index: 7 | 68. Methodology and Computing in Applied Probability (Springer) - Germany - IF: 1.550 - h-index: 33 | 69. Journal of Applied Probability and Statistics (Universidad Nacional de Colombia) - Colombia - IF: 0.321 - h-index: 4 | 70. Journal of Statistical Distributions and Applications (Springer) - Germany - IF: 1.180 - h-index: 20 | 71. Journal of Statistical Theory and Practice (Taylor & Francis) - UK - IF: 0.516 - h-index: 18 | 72. Scandinavian Journal of Statistics (Wiley) - USA - IF: 1.508 - h-index: 63 | 73. Journal of Quality Technology - American Society for Quality, USA - 82.7, 57 | 74. Quality and Reliability Engineering International - Wiley, UK - 31.9, 32 | 75. Journal of Applied Statistics - Taylor & Francis, UK - 29.3, 53 | 76. Technometrics - Taylor & Francis, USA - 28.6, 48 | 77. Journal of Quality Assurance in Hospitality & Tourism - Taylor & Francis, USA - 28.4, 16 | 78. Journal of Statistical Planning and Inference - Elsevier, Netherlands - 26.8, 89 | 79. Communications in Statistics - Taylor & Francis, USA - 25.1, 50 | 80. Journal of Process Control - Elsevier, Netherlands - 24.9, 63 | 81. Quality Engineering - Taylor & Francis, USA - 24.2, 37 | 82. Journal of Statistical Computation and Simulation - Taylor & Francis, UK - 21.8, 54 | 83. Journal of Statistical Software - UCLA Statistics, USA - 21.1, 87 | 84. Journal of Quality in Maintenance Engineering - Emerald, UK - 19.5, 16 | 85. International Journal of Production Research - Taylor & Francis, UK - 19.3, 110 | 86. Journal of Applied Probability - Cambridge University Press, UK - 18.9, 30 | 87. Journal of Quality Management - Elsevier, Netherlands - 18.1, 28 | 88. Journal of the Royal Statistical Society: Series C (Applied Statistics) - Wiley, UK - 17.7, 85 | 89. Journal of Quality Research - Taylor & Francis, USA - 16.9, 17 | 90. Quality Management Journal - ASQ, USA - 16.8, 15 | 91. Journal of Statistical Theory and Practice - Taylor & Francis, USA - 16.2, 23 | 92. Journal of Statistical Mechanics: Theory and Experiment - Institute of Physics Publishing, UK - 15.4, 30 | 93. Quality Engineering and Management - Wiley, USA - 15.2, 10 | 94. Journal of Applied Probability and Statistics - Department of Applied Mathematics, Russia - 14.9, 9 | 95. Statistical Methods and Applications - Springer, Germany - 14.8, 27 | 96. Quality and Quantity - Springer, Netherlands - 14.3, 33 | 97. Quality Innovation Prosperity - University of Maribor, Slovenia - 13.9, 10 | 98. Quality Management and Business Excellence - Taylor & Francis, UK - 13.8, 28 | 99. Journal of Applied Mathematics and Stochastic Analysis - Hindawi, Egypt - 13.5, 15 | 100. Journal of Reliability and Statistical Studies - Journal of Reliability and Statistical Studies, Malaysia - 13.4, 4

1. American Statistical Association (ASA) - United States | 2. International Statistical Institute (ISI) - Netherlands | 3. Royal Statistical Society (RSS) - United Kingdom | 4. International Biometric Society (IBS) - Canada | 5. Institute of Mathematical Statistics (IMS) - United States | 6. Statistical Society of Canada (SSC) - Canada | 7. Bernoulli Society for Mathematical Statistics and Probability - Switzerland | 8. Japan Statistical Society (JSS) - Japan | 9. Italian Statistical Society (SIS) - Italy | 10. Australian Statistical Society (AuSS) - Australia | 11. Korean Statistical Society (KSS) - South Korea | 12. Belgian Statistical Society (BVS-ABDS) - Belgium | 13. Brazilian Society of Statistics (Sociedade Brasileira de Estatística) - Brazil | 14. German Statistical Society (Deutsche Statistische Gesellschaft) - Germany | 15. Finnish Statistical Society (Tilastoseura) - Finland | 16. Croatian Statistical Association (Hrvatsko statističko društvo) - Croatia | 17. Hungarian Statistical Association (Magyar Statisztikai Társaság) - Hungary | 18. Indian Society for Probability and Statistics (ISPS) - India | 19. Iranian Statistical Society (ISS) - Iran | 20. Statistical Society of Australia (SSA) - Australia | 21. Mexican Statistical Association (AMEXEST) - Mexico | 22. Norwegian Statistical Association (Norsk statistisk forening) - Norway | 23. Pakistan Statistical Association (PSA) - Pakistan | 24. Polish Statistical Association (Polskie Towarzystwo Statystyczne) - Poland | 25. Portuguese Statistical Society (Sociedade Portuguesa de Estatística) - Portugal | 26. Romanian Statistical Society (Societatea Română de Statistică) - Romania | 27. Serbian Statistical Society (Statističko društvo Srbije) - Serbia | 28. Slovenian Statistical Society (Statistično društvo Slovenije) - Slovenia | 29. Spanish Society of Statistics and Operations Research (Sociedad de Estadística e Investigación Operativa) - Spain | 30. Swedish Statistical Association (Statistiska föreningen) - Sweden | 31. Swiss Statistical Society (Schweizerische Statistische Gesellschaft) - Switzerland | 32. Taiwan Statistical Association (TSA) - Taiwan | 33. Turkish Statistical Association (Türkiye İstatistik Kurumu) - Turkey | 34. Ukrainian Statistical Association (Ukrainian Statistical Association) - Ukraine | 35. Vietnamese Statistical Association (Vietnamese Statistical Association) - Vietnam | 36. Austrian Statistical Society (Österreichische Statistische Gesellschaft) - Austria | 37. Chilean Statistical Society (Sociedad Chilena de Estadística) - Chile | 38. Colombian Statistical Society (Sociedad Colombiana de Estadística) - Colombia | 39. Danish Statistical Society (Dansk Selskab for Teoretisk Statistik) - Denmark | 40. Dutch Society for Statistics and Operations Research (Vereniging voor Statistiek en Operations Research) - Netherlands | 41. Estonian Statistical Society (Eesti Statistikaselts) - Estonia | 42. French Statistical Society (Société française de statistique) - France | 43. Georgian Statistical Society (Georgian Statistical Society) - Georgia | 44. Greek Statistical Institute (Ελληνικό Στατιστικό Ινστιτούτο) - Greece | 45. Institute of Mathematical Statistics (IMS) - United States | 46. Bernoulli Society for Mathematical Statistics and Probability - Switzerland | 47. International Statistical Institute (ISI) - Netherlands | 48. American Statistical Association (ASA) - United States | 49. International Society for Bayesian Analysis (ISBA) - Spain | 50. International Association for Statistical Computing (IASC) - Canada | 51. Mathematical Association of America (MAA) - United States | 52. Statistical Society of Canada (SSC) - Canada | 53. International Biometric Society (IBS) - Canada | 54. Royal Statistical Society (RSS) - United Kingdom | 55. European Mathematical Society (EMS) - Switzerland | 56. Society for Industrial and Applied Mathematics (SIAM) - United States | 57. Society for Risk Analysis (SRA) - United States | 58. Institute of Mathematical Statistics of the Czech Republic (IMS CZ) - Czech Republic | 59. Society for Applied and Industrial Mathematics (GAMM) - Germany | 60. Society for Mathematical Biology (SMB) - United States | 61. Belgian Statistical Society (BVS-ABDS) - Belgium | 62. Brazilian Society of Probability and Statistics (SBPE) - Brazil | 63. Canadian Society for Statistics and Probability (CSSP) - Canada | 64. Croatian Mathematical Society (CMS) - Croatia | 65. Czech Statistical Society (CSS) - Czech Republic | 66. Danish Statistical Society (DSS) - Denmark | 67. Deutsche Mathematiker-Vereinigung (DMV) - Germany | 68. European Society for Mathematical and Theoretical Biology (ESMTB) - United Kingdom | 69. Finnish Statistical Society (FSS) - Finland | 70. French Society of Statistics (SFdS) - France | 71. German Mathematical Society (DMV) - Germany | 72. Hellenic Mathematical Society (HMS) - Greece | 73. Hungarian Statistical Association (HSA) - Hungary | 74. Indian Society for Probability and Statistics (ISPS) - India | 75. Indonesian Statistical Society (ISS) - Indonesia | 76. International Association for Statistical Education (IASE) - United Kingdom | 77. International Society for Clinical Biostatistics (ISCB) - Germany | 78. International Society for Nonparametric Statistics (ISNPS) - United States | 79. Iranian Statistical Society (ISS) - Iran | 80. Irish Statistical Association (ISA) - Ireland | 81. Israeli Statistical Association (ISA) - Israel | 82. Italian Statistical Society (SIS) - Italy | 83. Japan Statistical Society (JSS) - Japan | 84. Kenyan Statistical Society (KSS) - Kenya | 85. Korean Statistical Society (KSS) - South Korea | 86. Lithuanian Statistical Society (LSS) - Lithuania | 87. Luxembourgish Statistical Society (LSS) - Luxembourg | 88. Malaysian Society of Statistical and Probability (MSSP) - Malaysia | 89. Mexican Statistical Association (AMEXEST) - Mexico | 90. Mongolian Statistical Society (MSS) - Mongolia | 91. Moroccan Statistical Society (SMS) - Morocco | 92. Nepal Statistical Society (NSS) - Nepal | 93. Norwegian Statistical Association (NSF) - Norway | 94. Pakistan Statistical Association (PSA) - Pakistan | 95. Philippine Statistical Association (PSA) - Philippines | 96. Polish Statistical Association (PTS) - Poland | 97. Portuguese Statistical Society (SPE) - Portugal | 98. Romanian Statistical Society (SRS) - Romania | 99. Russian Statistical Society (RSS) - Russia | 100. Serbian Statistical Society (SSD) - Serbia

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1. Bradley Efron - Bootstrap methods, Stanford University, United States | 2. David Cox - Survival analysis, Oxford University, United Kingdom | 3. Grace Wahba - Smoothing methods, University of Wisconsin-Madison, United States | 4. Jianqing Fan - High-dimensional statistics, Princeton University, United States | 5. Donald Rubin - Causal inference, Harvard University, United States | 6. Peter McCullagh - Generalized linear models, University of Chicago, United States | 7. Terry Speed - Bioinformatics, University of California, Berkeley, United States | 8. Andrew Gelman - Bayesian statistics, Columbia University, United States | 9. Richard Samworth - Nonparametric statistics, University of Cambridge, United Kingdom | 10. Stephen Senn - Clinical trials, University of Glasgow, United Kingdom | 11. Bradley Carlin - Bayesian hierarchical models, University of Minnesota, United States | 12. Trevor Hastie - Machine learning, Stanford University, United States | 13. David Dunson - Bayesian methods, Duke University, United States | 14. Edward George - Bayesian hierarchical models, University of Pennsylvania, United States | 15. David Spiegelhalter - Bayesian statistics, University of Cambridge, United Kingdom | 16. Ian McKeague - Nonparametric regression, Columbia University, United States | 17. Aad van der Vaart - Asymptotic statistics, Leiden University, Netherlands | 18. Marie Davidian - Longitudinal data analysis, North Carolina State University, United States | 19. Jon Wakefield - Spatial statistics, University of Washington, United States | 20. Nanny Wermuth - Graphical models, Chalmers University of Technology, Sweden | 21. David Brillinger - Time series analysis, University of California, Berkeley, United States | 22. Joseph Ibrahim - Missing data, University of North Carolina at Chapel Hill, United States | 23. Michael Jordan - Machine learning, University of California, Berkeley, United States | 24. Bruce Lindsay - Nonparametric statistics, Pennsylvania State University, United States | 25. Alan Agresti - Categorical data analysis, University of Florida, United States | 26. Dimitris Politis - Bootstrap methods, University of California, San Diego, United States | 27. Antonio Lijoi - Bayesian nonparametrics, University of Pavia, Italy | 28. Martin Wainwright - High-dimensional statistics, University of California, Berkeley, United States | 29. Hélène Massam - Graphical models, York University, Canada | 30. Larry Wasserman - Nonparametric statistics, Carnegie Mellon University, United States | 31. Yoav Benjamini - Multiple testing, Tel Aviv University, Israel | 32. Valérie Chavez-Demoulin - Extreme value theory, EPFL, Switzerland | 33. Bani Mallick - Bayesian methods, Texas A&M University, United States | 34. Mark van der Laan - Causal inference, University of California, Berkeley, United States | 35. Luc Devroye - Nonparametric statistics, McGill University, Canada | 36. Anirban DasGupta - Asymptotic statistics, Purdue University, United States | 37. Xiao-Li Meng - Bayesian statistics, Harvard University, United States | 38. Richard Smith - Stochastic processes, University of Cambridge, United Kingdom | 39. Robert Tibshirani - Statistical learning, Stanford University, United States | 40. Geert Molenberghs - Longitudinal data analysis, Hasselt University, Belgium | 41. Andrew Raftery - Bayesian demographic methods, University of Washington, United States | 42. David Cox - Survival analysis, Nuffield College, University of Oxford, United Kingdom | 43. Peter McCullagh - Generalized linear models, University of Chicago, United States | 44. Norman Breslow - Logistic regression, University of Washington, United States | 45. Bradley Efron - Bootstrap methods, Stanford University, United States | 46. John Nelder - Generalized linear models, Imperial College London, United Kingdom | 47. Terry Speed - Bioinformatics, University of California, Berkeley, United States | 48. David Spiegelhalter - Bayesian statistics, University of Cambridge, United Kingdom | 49. Grace Wahba - Smoothing methods, University of Wisconsin-Madison, United States | 50. Nanny Wermuth - Graphical models, Chalmers University of Technology, Sweden | 51. Leo Breiman - Classification and regression trees, University of California, Berkeley, United States | 52. David Donoho - High-dimensional data analysis, Stanford University, United States | 53. Alan Agresti - Categorical data analysis, University of Florida, United States | 54. Jerome H. Friedman - Regression trees, Stanford University, United States | 55. Bradley P. Carlin - Bayesian hierarchical models, University of Minnesota, United States | 56. David Dunson - Bayesian nonparametrics, Duke University, United States | 57. Thomas K. Landauer - Latent semantic analysis, University of Colorado Boulder, United States | 58. John Tukey - Exploratory data analysis, Princeton University, United States | 59. Adrian Raftery - Bayesian model selection, University of Washington, United States | 60. Joseph B. Kadane - Bayesian statistics, Carnegie Mellon University, United States | 61. Andrew Gelman - Bayesian statistics, Columbia University, United States | 62. Jianqing Fan - High-dimensional statistics, Princeton University, United States | 63. Simon Jackman - Bayesian analysis, Stanford University, United States | 64. Edward L. Gelfand - Bayesian statistics, Duke University, United States | 65. Donald Rubin - Causal inference, Harvard University, United States | 66. Trevor Hastie - Penalized regression, Stanford University, United States | 67. Charles J. Geyer - Markov chain Monte Carlo, University of Minnesota, United States | 68. Michael I. Jordan - Bayesian nonparametrics, University of California, Berkeley, United States | 69. Ming Yuan - High-dimensional statistics, Columbia University, United States | 70. Richard Berk - Criminology statistics, University of Pennsylvania, United States | 71. Jianhua Huang - Nonparametric regression, University of Iowa, United States | 72. Nicholas J. Horton - Bayesian methods, Amherst College, United States | 73. Paul Embrechts - Extreme value theory, ETH Zurich, Switzerland | 74. Luis A. Escobar - Nonparametric statistics, Arizona State University, United States | 75. Sir David Cox - Generalized linear models, Nuffield College, University of Oxford, United Kingdom | 76. Bruce G. Lindsay - Nonparametric statistics, Pennsylvania State University, United States | 77. Lutz Dümbgen - Distribution-free statistics, University of Bern, Switzerland | 78. Efron, B. - Bootstrap methods, Stanford University, United States | 79. Gershenfeld, N. - Data science, Massachusetts Institute of Technology, United States | 80. Gelman, A. - Bayesian statistics, Columbia University, United States | 81. Ghosh, J. K. - Bayesian statistics, University of Florida, United States | 82. Ronald Fisher - Classical hypothesis testing, University of Cambridge, United Kingdom | 83. Jerzy Neyman - Neyman-Pearson hypothesis testing, University of California, Berkeley, United States | 84. Egon Pearson - Neyman-Pearson hypothesis testing, University College London, United Kingdom | 85. William Gosset - Student\'s t-test, Guinness brewery, Ireland | 86. Jerzy G. Székely - Nonparametric hypothesis testing, Bowling Green State University, United States | 87. George Casella - Theory of hypothesis testing, University of Florida, United States | 88. Joseph L. Gastwirth - Nonparametric hypothesis testing, George Washington University, United States | 89. William Cochran - Sampling theory and hypothesis testing, University of North Carolina, United States | 90. Frank Wilcoxon - Nonparametric hypothesis testing, Princeton University, United States | 91. Samuel S. Wilks - Distribution theory and hypothesis testing, Princeton University, United States | 92. Harold Hotelling - Multivariate hypothesis testing, University of North Carolina, United States | 93. Henry Scheffé - Multiple comparison procedures, University of California, Berkeley, United States | 94. Bradley Efron - Bootstrap methods and hypothesis testing, Stanford University, United States | 95. David Cox - Hypothesis testing and model selection, Nuffield College, University of Oxford, United Kingdom | 96. Bradley P. Carlin - Bayesian hypothesis testing, University of Minnesota, United States | 97. Emanuel Parzen - Nonparametric hypothesis testing, Texas A&M University, United States | 98. George P. Box - Experimental design and hypothesis testing, University of Wisconsin-Madison, United States | 99. John W. Tukey - Exploratory data analysis and hypothesis testing, Princeton University, United States | 100. John Aitchison - Nonparametric hypothesis testing, University of Glasgow, United Kingdom

1. Bradley Efron - Stanford University, USA - 230,000+ citations, H-index: 164 | 2. Peter Bickel - University of California, Berkeley, USA - 80,000+ citations, H-index: 96 | 3. Grace Wahba - University of Wisconsin-Madison, USA - 45,000+ citations, H-index: 74 | 4. David Cox - University of Oxford, UK - 140,000+ citations, H-index: 139 | 5. Emmanuel Candès - Stanford University, USA - 140,000+ citations, H-index: 104 | 6. Trevor Hastie - Stanford University, USA - 140,000+ citations, H-index: 105 | 7. David Donoho - Stanford University, USA - 130,000+ citations, H-index: 105 | 8. Persi Diaconis - Stanford University, USA - 50,000+ citations, H-index: 71 | 9. Terry Speed - Walter and Eliza Hall Institute, Australia - 70,000+ citations, H-index: 89 | 10. S. James Press - University of California, Berkeley, USA - 70,000+ citations, H-index: 83 | 11. Donald Rubin - Harvard University, USA - 180,000+ citations, H-index: 124 | 12. Jianqing Fan - Princeton University, USA - 75,000+ citations, H-index: 87 | 13. David Spiegelhalter - University of Cambridge, UK - 120,000+ citations, H-index: 106 | 14. Bradley Carlin - University of Minnesota, USA - 50,000+ citations, H-index: 68 | 15. John Tukey - Princeton University, USA - 260,000+ citations, H-index: 166 | 16. David Dunson - Duke University, USA - 55,000+ citations, H-index: 81 | 17. Mark Geyer - University of California, Los Angeles, USA - 30,000+ citations, H-index: 58 | 18. Richard Samworth - University of Cambridge, UK - 35,000+ citations, H-index: 54 | 19. Paul Embrechts - ETH Zurich, Switzerland - 40,000+ citations, H-index: 59 | 20. Larry Wasserman - Carnegie Mellon University, USA - 70,000+ citations, H-index: 86 | 21. Ian McKeague - Columbia University, USA - 13,000+ citations, H-index: 36 | 22. Richard J. Smith - University of North Carolina, USA - 50,000+ citations, H-index: 76 | 23. Nanny Wermuth - Chalmers University of Technology, Sweden - 15,000+ citations, H-index: 35 | 24. Joseph Hilbe - University of Hawaii at Manoa, USA - 30,000+ citations, H-index: 54 | 25. Gareth James - University of Southern California, USA - 70,000+ citations, H-index: 88 | 26. David Spiegel - Stanford University, USA - 75,000+ citations, H-index: 96 | 27. Natesh Pillai - Harvard University, USA - 10,000+ citations, H-index: 31 | 28. Persi Diaconis, Stanford University, USA, 96, 129 | 29. David Aldous, University of California, Berkeley, USA, 70, 91 | 30. Yuval Peres, Microsoft Research and Hebrew University, Israel, 46, 86 | 31. Peter Bickel, University of California, Berkeley, USA, 50, 85 | 32. Donald Geman, Johns Hopkins University, USA, 56, 82 | 33. Persi W. Diaconis, Harvard University, USA, 57, 79 | 34. David Donoho, Stanford University, USA, 89, 77 | 35. Michael Jordan, University of California, Berkeley, USA, 108, 76 | 36. Sara van de Geer, ETH Zurich, Switzerland, 60, 75 | 37. Peter Hall, University of Melbourne, Australia, 84, 75 | 38. Jianqing Fan, Princeton University, USA, 85, 73 | 39. Lucien Le Cam, University of California, Berkeley, USA, 73, 72 | 40. Lawrence D. Brown, University of Pennsylvania, USA, 60, 70 | 41. Richard Samworth, University of Cambridge, UK, 50, 70 | 42. Susan Murphy, Harvard University, USA, 48, 69 | 43. Terence Tao, University of California, Los Angeles, USA, 136, 68 | 44. Bin Yu, University of California, Berkeley, USA, 69, 67 | 45. Martin Wainwright, University of California, Berkeley, USA, 64, 67 | 46. Christian Houdré, Georgia Institute of Technology, USA, 63, 67 | 47. Richard J. Cook, University of Waterloo, Canada, 63, 66 | 48. Richard Davis, Columbia University, USA, 59, 66 | 49. Edward L. Gelfand, Colorado State University, USA, 54, 65 | 50. Stephen M. Stigler, University of Chicago, USA, 55, 65 | 51. Adrian Raftery, University of Washington, USA, 67, 65 | 52. Marc Hallin, Université Libre de Bruxelles, Belgium, 68, 65 | 53. Peter J. Diggle, Lancaster University, UK, 57, 65 | 54. Sir David Cox, University of Oxford, UK, 81, 65 | 55. Tilmann Gneiting, Heidelberg University, Germany, 53, 64 | 56. George Casella, University of Florida, USA, 65, 64 | 57. James O. Berger, Duke University, USA, 61, 64 | 58. Andrew Gelman, Columbia University, USA, 119, 63 | 59. John Rice, University of California, Berkeley, USA, 61, 63 | 60. Emmanuel Candès, Stanford University, USA, 90, 63 | 61. Thomas Mikosch, University of Copenhagen, Denmark, 54, 62 | 62. Marc K. C. van Lieshout, Delft University of Technology, Netherlands, 50, 62 | 63. Richard D. Gill, Leiden University, Netherlands, 57, 62 | 64. Michael Stein, University of Chicago, USA, 77, 61 | 65. Alexander Aue, University of California, Davis, USA, 50, 61 | 66. Jean-Michel Loubes, Université de Toulouse, France, 63, 60 | 67. Frederick Mosteller, Harvard University, USA, 45,700 citations, H-Index 82 | 68. David Freedman, University of California, Berkeley, USA, 33,200 citations, H-Index 68 | 69. Ronald Fisher, University of Cambridge, UK, 113,400 citations, H-Index 68 | 70. Bradley Efron, Stanford University, USA, 162,500 citations, H-Index 114 | 71. John Tukey, Princeton University, USA, 118,200 citations, H-Index 77 | 72. Edward Tufte, Yale University, USA, 52,500 citations, H-Index 57 | 73. William Cleveland, Purdue University, USA, 47,200 citations, H-Index 65 | 74. Rob Tibshirani, Stanford University, USA, 286,600 citations, H-Index 150 | 75. Leo Breiman, University of California, Berkeley, USA, 72,500 citations, H-Index 69 | 76. Alan Stuart, Lancaster University, UK, 16,900 citations, H-Index 44 | 77. Frank Anscombe, Yale University, USA, 21,300 citations, H-Index 46 | 78. John W. Tukey, Bell Labs, USA, 114,800 citations, H-Index 77 | 79. J. Scott Armstrong, The Wharton School, University of Pennsylvania, USA, 23,700 citations, H-Index 59 | 80. Robert A. Stine, University of Pennsylvania, USA, 17,200 citations, H-Index 51 | 81. Clifford Spiegelman, Texas A&M University, USA, 18,500 citations, H-Index 47 | 82. Andrew Gelman, Columbia University, USA, 205,500 citations, H-Index 121 | 83. Emanuel Parzen, Texas A&M University, USA, 29,100 citations, H-Index 59 | 84. Willem R. van Zwet, VU University Amsterdam, Netherlands, 6,250 citations, H-Index 35 | 85. David J. Hand, Imperial College London, UK, 31,200 citations, H-Index 69 | 86. Peter J. Huber, Swiss Federal Institute of Technology Zurich, Switzerland, 38,500 citations, H-Index 61 | 87. Kjell A. Doksum, University of California, Berkeley, USA, 9,750 citations, H-Index 39 | 88. Bradley P. Carlin, University of Minnesota, USA, 47,800 citations, H-Index 83 | 89. David Ruppert, Cornell University, USA, 70,700 citations, H-Index 89 | 90. Michael Woodroofe, University of Michigan, USA, 13,500 citations, H-Index 48 | 91. Peter Bickel, University of California, Berkeley, USA, 70,500 citations, H-Index 86 | 92. V. K. Rohatgi, University of California, Riverside, USA, 13,200 citations, H-Index 43 | 93. Dennis Cook, University of Minnesota, USA, 52,900 citations, H-Index 72 | 94. C. R. Rao, Pennsylvania State University, USA, 166,200 citations, H-Index 93 | 95. Stephen Fienberg, Carnegie Mellon University, USA, 56,300 citations, H-Index 69 | 96. Sir David Cox, University of Oxford, UK, 143,800 citations, H-Index 91 | 97. Bradley Efron - Stanford University, USA - 176,297 citations - h-index 161 | 98. David Cox - University of Oxford, UK - 92,238 citations - h-index 95 | 99. Leo Breiman - University of California, Berkeley, USA - 102,839 citations - h-index 89 | 100. Jerome H. Friedman - Stanford University, USA - 89,320 citations - h-index 87

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Eliuk, PricewaterhouseCoopers LLP, US, Patent No. 7,937,373, May 3, 2011. | 49. \"Method and system for hypothesis testing based on the false discovery rate,\" Yuji Iwasaki, Tokyo Institute of Technology, Japan, Patent No. 8,145,585, March 27, 2012. | 50. \"Method and system for adaptive hypothesis testing in a sensor network,\" Peng Ning, North Carolina State University, US, Patent No. 8,229,526, July 24, 2012. | 51. \"Method and system for hypothesis testing using a conditional entropy measure,\" Richard M. Winters, AT&T Corp., US, Patent No. 6,542,975, April 1, 2003. | 52. \"Method and system for hypothesis testing in a distributed database system,\" Srivatsan Ramanujam, IBM Corporation, US, Patent No. 9,559,920, January 31, 2017. | 53. \"Method for adaptive hypothesis testing based on independent components analysis,\" Yi Huang, University of Texas at Austin, US, Patent No. 8,870,734, October 28, 2014. | 54. \"Method and system for hypothesis testing using hierarchical models,\" Murali Krishna Manthripragada, University of California, US, Patent No. 8,849,175, September 30, 2014. | 55. \"Method and system for hypothesis testing in association analysis,\" S. Michal Jankowski, National Institutes of Health, US, Patent No. 7,944,958, May 17, 2011. | 56. \"Method and apparatus for hypothesis testing in distributed networks,\" Michael P. Wellman, University of Michigan, US, Patent No. 6,397,200, June 4, 2002. | 57. \"Method and apparatus for non-parametric hypothesis testing,\" Anirban DasGupta, Purdue University, US, Patent No. 6,272,481, August 7, 2001. | 58. \"Method and apparatus for statistical hypothesis testing of virtual assets,\" Steven A. Eliuk, PricewaterhouseCoopers LLP, US, Patent No. 7,937,373, May 3, 2011. | 59. \"Method and system for hypothesis testing based on the false discovery rate,\" Yuji Iwasaki, Tokyo Institute of Technology, Japan, Patent No. 8,145,585, March 27, 2012. | 60. \"Method and system for adaptive hypothesis testing in a sensor network,\" Peng Ning, North Carolina State University, US, Patent No. 8,229,526, July 24, 2012. | 61. \"Method and system for hypothesis testing using a conditional entropy measure,\" Richard M. Winters, AT&T Corp., US, Patent No. 6,542,975, April 1, 2003. | 62. \"System and Method for Analyzing Probability Distributions of Data\", T. Wu, University of North Carolina, USA, US20190312884A1, 2019. | 63. \"System and Method for Probability Distributions Estimation Based on Historical Data\", F. Zhang, Zhejiang University, China, CN111470991A, 2020. | 64. \"Estimation of Probability Distributions in Quantum Systems\", R. W. Spekkens, Perimeter Institute for Theoretical Physics, Canada, US20190289533A1, 2019. | 65. \"Methods and Systems for Probability Distributions Calculation Using Confidence Intervals\", R. T. Qiu, Amazon Technologies, Inc., USA, US20180177472A1, 2018. | 66. \"System and Method for Constructing Probability Distributions of Return Periods and Its Application in Precipitation Extreme Events\", Q. Wang, Beijing Normal University, China, CN110450901A, 2019. | 67. \"Estimation of Probability Distributions Using a Deep Neural Network\", B. Nadler, Hebrew University of Jerusalem, Israel, US20200078613A1, 2020. | 68. \"Method for Probability Distributions Estimation for Nonlinear Systems with Multiplicative Noise\", C. Zhang, Beijing Institute of Technology, China, CN109886385A, 2019. | 69. \"System and Method for Estimating Probability Distributions from Sparse Data\", R. Chen, Amazon Technologies, Inc., USA, US20180239334A1, 2018. | 70. \"Systems and Methods for Analyzing Probability Distributions\", D. E. Carlson, California Institute of Technology, USA, US20190231608A1, 2019. | 71. \"Method for Estimating Probability Distributions of a Stochastic Process by Correlation Functions\", F. Bonetto, University of California, USA, US20180201723A1, 2018. | 72. \"Probability Distributions Estimation Method for Multi-dimensional Data Based on Bayesian Nonparametric Statistics\", J. Cao, South China University of Technology, China, CN108907242A, 2018. | 73. \"System and Method for Probability Distributions Estimation Based on Fuzzy Clustering and Maximum Entropy Principle\", L. Wang, Harbin Institute of Technology, China, CN106556262A, 2017. | 74. \"Method and System for Constructing Probability Distributions with Application in Traffic Prediction\", L. Cheng, Southeast University, China, CN108640710A, 2018. | 75. \"Method and System for Estimating Probability Distributions of Random Variables in Data Sets\", S. M. Moses, IBM Corporation, USA, US20180293771A1, 2018. | 76. \"Method for Constructing Probability Distributions of Large Datasets Based on Constrained Optimization\", Y. Jiang, Wuhan University, China, CN106311315A, 2017. | 77. \"System and Method for Probability Distributions Estimation Based on Wavelet Analysis and Entropy Theory\", H. Chen, China University of Mining and Technology, China, CN105216639A, 2015. | 78. \"System and Method for Estimating Probability Distributions from Incomplete Data\", G. V. Nakamura, The Regents of the University of California, USA, US20180153651A1, 2018. | 79. \"Method and System for Probability Distributions Estimation of Electromagnetic Fields\", X. Li, Beijing Institute of Technology, China, CN105568053A, 2016. | 80. Patent valuation: This involves using Bayesian models to estimate the value of a particular patent or patent portfolio based on factors such as the potential market size, the strength of the patent claims, and the likelihood of infringement. | 81. Patent litigation: Bayesian statistics can be used to assess the probability of winning or losing a patent litigation case based on factors such as the strength of the patent claims, the prior art in the field, and the potential damages at stake. | 82. Patent prosecution: Bayesian statistics can be used to guide patent prosecution strategies by identifying potential weaknesses in the patent claims and assessing the likelihood of success in obtaining patent protection. | 83. Patent landscaping: Bayesian statistics can be used to identify potential opportunities for innovation by analyzing the patent landscape in a particular technology area and identifying areas of white space or unexplored potential. | 84. Prior art search: Bayesian statistics can be used to optimize the prior art search process by identifying the most relevant prior art based on a combination of expert knowledge and probabilistic models. | 85. Patent valuation: This involves using Bayesian models to estimate the value of a particular patent or patent portfolio based on factors such as the potential market size, the strength of the patent claims, and the likelihood of infringement. | 86. Patent litigation: Bayesian statistics can be used to assess the probability of winning or losing a patent litigation case based on factors such as the strength of the patent claims, the prior art in the field, and the potential damages at stake. | 87. Patent prosecution: Bayesian statistics can be used to guide patent prosecution strategies by identifying potential weaknesses in the patent claims and assessing the likelihood of success in obtaining patent protection. | 88. Patent landscaping: Bayesian statistics can be used to identify potential opportunities for innovation by analyzing the patent landscape in a particular technology area and identifying areas of white space or unexplored potential. | 89. Prior art search: Bayesian statistics can be used to optimize the prior art search process by identifying the most relevant prior art based on a combination of expert knowledge and probabilistic models. | 90. Patent counts: This refers to the number of patents in a particular portfolio or dataset. Patent counts can provide insights into the size and scope of a particular patent portfolio or technology area. | 91. Patent classification: This refers to the categorization of patents into different technology areas based on their content. Patent classification can provide insights into the distribution of patent activity across different technology areas, as well as the trends and patterns in patent activity within specific technology areas. | 92. Patent citation analysis: This involves analyzing the citations between patents to identify the most influential patents in a particular area. Patent citation analysis can provide insights into the most important technologies and innovations in a particular area, as well as the influence and impact of different inventors and companies. | 93. Patent family analysis: This involves analyzing the different patent applications that are related to a particular invention, known as patent families. Patent family analysis can provide insights into the international scope of a particular invention, as well as the different legal jurisdictions in which patent protection has been sought. | 94. Patent age: This refers to the age of a particular patent, measured from the date of filing. Patent age can provide insights into the lifecycle of a particular technology area, as well as the potential expiration and renewal of patent protection. | 95. Prior art search: This involves searching for existing patents and published literature in the field to identify potential sources of prior art that could be used to challenge the novelty and inventiveness of the invention. By identifying potential sources of prior art, patent applicants can refine their claims and increase their chances of success. | 96. Patentability opinions: These are legal opinions provided by patent attorneys or agents that assess the likelihood that a patent application will be granted. Patentability opinions can be based on a variety of factors, including the novelty and inventiveness of the invention, the clarity and specificity of the patent claims, and the strength of the prior art in the field. | 97. Patent analytics: These are statistical techniques used to analyze patent data to identify patterns and trends in patent activity. Patent analytics can be used to identify the most innovative companies and inventors in a particular field, as well as the most active patent offices and technology areas. | 98. Patent prosecution history: This is the record of all communications between the patent applicant and the patent office during the examination process. By reviewing the patent prosecution history, patent attorneys or agents can identify potential issues with the application and develop strategies to address them. | 99. Patent counts: This method involves simply counting the number of patents granted in a particular technology area over time. This method can provide insights into the overall level of innovation in a particular area, as well as the trends and patterns in patent activity over time. | 100. Patent citation analysis: This method involves analyzing the citations between patents to identify the most influential patents in a particular area. This method can provide insights into the most important technologies and innovations in a particular area, as well as the influence and impact of different inventors and companies.

Sponsorship

ResearchW warmly invites you to sponsor or exhibit at International Conference. We expect participants more than 200 numbers for our International conference will provide an opportunity to hear and meet/ads to Researchers, Practitioners, and Business Professionals to share expertise, foster collaborations, and assess rising innovations across the world in the core area of mechanical engineering.

Sponsorship Details

Diamond Sponsorship

1. Acknowledgment during the opening of the conference
2. Complimentary Booth of size 10 meters square
3. Four (4) delegate’s complimentary registrations with lunch
4. Include marketing document in the delegate pack
5. Logo on Conference website, Banners, Backdrop, and conference proceedings
6. One exhibition stand (1×1 meters) for the conference
7. One full cover page size ad in conference proceedings
8. Opportunities for Short speech at events
9. Opportunity to sponsors conference kit
10. Opportunity to sponsors conference lanyards, ID cards
11. Opportunity to sponsors conference lunch
12. Recognition in video ads
13. 150-word company profile and contact details in the delegate pack

Platinum Sponsorship

1. Three (3) delegate’s complimentary registrations with lunch
2. Recognition in video ads
3. Opportunity to sponsors conference lunch
4. Opportunity to sponsors conference lanyards, ID cards
5. Opportunity to sponsors conference kit
6. Opportunities for Short speech at events
7. One full-page size ad in conference proceedings
8. One exhibition stand (1×1 meters) for the conference
9. Logo on Conference website, Banners, Backdrop, and conference proceedings
10. Include marketing document in the delegate pack
11. Complimentary Booth of size 10 meters square
12. Acknowledgment during the opening of the conference
13. 100-word company profile and contact details in the delegate pack

Gold Sponsorship

1. Two (2) delegate’s complimentary registrations with lunch
2. Opportunities for Short speech at events
3. Logo on Conference website, Banners, Backdrop, and conference proceedings
4. Include marketing document in the delegate pack
5. Complimentary Booth of size 10 meters square
6. Acknowledgment during the opening of the conference
7. 100-word company profile and contact details in the delegate pack
8. ½ page size ad in conference proceedings

Silver Sponsorship

1. Acknowledgment during the opening of the conference
2. One(1) delegate’s complimentary registrations with lunch
3. Include marketing document in the delegate pack
4. Logo on Conference website, Banners, Backdrop, and conference proceedings
5. ¼ page size ad in conference proceedings
6. 100-word company profile and contact details in the delegate pack

Individual Sponsorship

1. Acknowledgment during the opening of the conference
2. One(1) delegate’s complimentary registrations with lunch

 

Sponsorship Registration Fees

Details	Registration fees
Diamond Sponsorship	USD 2999
Platinum Sponsorship	USD 2499
Gold Sponsorship	USD 1999
Silver Sponsorship	USD 1499
Individual Sponsorship	USD 999

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