About the Award

The International Research Data Analysis Excellence Awards recognize outstanding achievements in the field of research data analysis. These awards are typically aimed at individuals, teams, or organizations that have made significant contributions to the advancement of research methodologies, data analysis techniques, or the effective use of data in solving complex problems.

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.

Theme

International Research Data Analysis Excellence Awards

Theme: Exploring the Recent research and Advancements in Research Data Analysis

To celebrate researcher achievements and motivate them to continue on their path

Objectives 

Recognition of Excellence: Acknowledging and celebrating outstanding achievements in the field of research data analysis to recognize and motivate researchers, analysts, and institutions.

Promotion of Best Practices: Encouraging the adoption of best practices in research data analysis, including transparency, reproducibility, and ethical conduct.

Advancement of Knowledge: Supporting the advancement of knowledge and innovation in data analysis methodologies, tools, and techniques.

Fostering Collaboration: Encouraging collaboration and interdisciplinary research in the field of data analysis by recognizing individuals or teams that have demonstrated effective collaboration.

Capacity Building: Promoting the development of skills and expertise in International research data analysis, both among established professionals and emerging researchers.

Organizers

Date and Locations

14th Edition of Research Data Analysis | 29-30 October 2024 | Paris, France
15th Edition of Research Data Analysis | 25-26 November 2024 | Agra,  India
16th Edition of Research Data Analysis | 27-28 December 2024 | Dubai, United Arab Emirates

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

Sciencefather 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 ScienceFather 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 ScienceFather 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 ScienceFather 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. NESIN 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 NESIN 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. ScienceFather 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.

Sponsorship

Sciencefather 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

Exhibitions

Contact us

Targeted Audience

1. Academic Researchers
2. Policy Makers and Government Officials
3. Business and Industry Professionals
4. Healthcare Professionals
5. Educational Institutions
6. General Public
7. Investors and Financial Analysts
8. Technology and Innovation Professionals

Targeted Countries 

Afghanistan|  Albania| Algeria| Andorra | Angola| Antigua and Barbuda|  Argentina|  Armenia| Australia|  Austria|  Azerbaijan|  Bahamas|  Bahrain|  Bangladesh| Barbado|  Belarus| Belgium|  Belize|  Benin|  Bhutan| Bolivia|  Bosnia and Herzegovina|  Botswana|  Brazil|  Brunei|  Bulgaria|  Burkina Faso|  Burundi|  Cabo Verde|  Cambodia|  Cameroon|  Canada|  Central African Republic|  Chad| Chile|  China|  Colombia|  Comoros| Democratic Republic of the Congo|  Republic of the Congo| Costa Rica|  Cote d'Ivoire|  Croatia| Cuba|  Cyprus| Czech Republic|  Denmark|  Djibouti| Dominica| Dominican Republic|  Ecuador|  Egypt|  El Salvador|  Equatorial Guinea|  Eritrea| Estonia| Eswatini| Ethiopia|  Fiji|  Finland|  France| Gabon| Gambia|  Georgia| Germany|  Ghana| Greece|  Grenada| Guatemala|  Guinea|  Guinea-Bissau|  Guyana|  Haiti| Honduras|  Hungary|  Iceland|  India|  Indonesia|  Iran|  Iraq|  Ireland|  Israel|  Italy|  Jamaica|  Japan|  Jordan|  Kazakhstan| Kenya|  Kiribati|  Kosovo|  Kuwait|  Kyrgyzstan|  Laos|  Latvia|  Lebanon|  Lesotho|  Liberia| Libya|  Liechtenstein| Lithuania| Luxembourg| Madagascar|  Malawi|  Malaysia| Maldives|  Mali|  Malta|  Marshall Islands|  Mauritania|  Mauritius|  Mexico|  Micronesia|  Moldova|  Monaco|  Mongolia|  Montenegro|  Morocco|  Mozambique|  Myanmar (Burma)|  Namibia|  Nauru|  Nepal|  Netherlands|  New Zealand| Nicaragua|  Niger|  Nigeria|  North Korea|  North Macedonia|  Norway|  Oman|  Pakistan|  Palau|  Panama|  Papua New Guinea|  Paraguay|  Peru|  Philippines|  Poland|  Portugal|  Qatar|  Romania|  Russia| Rwanda|  Saint Kitts and Nevis|  Saint Lucia|  Saint Vincent and the Grenadines|  Samoa|  San Marino|  Sao Tome and Principe|  Saudi Arabia|  Senegal|  Serbia|  Seychelles|  Sierra Leone|  Singapore|  Slovakia|  Slovenia|  Solomon Islands|  Somalia|  South Africa|  South Korea|  South Sudan|  Spain| Sri Lanka|  Sudan|  Suriname|  Sweden|  Switzerland| Syria|  Taiwan|  Tajikistan|  Tanzania|  Thailand| Timor-Leste|  Togo|  Tonga|  Trinidad and Tobago| Tunisia| Turkey| Turkmenistan| Tuvalu| Uganda|  Ukraine|  United Arab Emirates|United Kingdom| United States|  Uruguay|  Uzbekistan|  Vanuatu| Vatican City| Venezuela| Vietnam| Yemen|  Zambia|  Zimbabwe.

Target Companies

• Google
• Facebook (Meta)
• Amazon
• Microsoft
• IBM
• SAS Institute
• Palantir Technologies
• NVIDIA
• Pfizer
• Johnson & Johnson

Targeted Universities

• Massachusetts Institute of Technology (MIT) - USA
• Stanford University - USA
• Harvard University - USA
• University of Cambridge - UK
• ETH Zurich - Switzerland
• National University of Singapore (NUS) - Singapore
• University of California, Berkeley - USA
• University of Oxford - UK
• Carnegie Mellon University - USA
• University of Toronto - Canada

Market Analysis

• As of my last knowledge update in January 2022, there wasn't a specific and universally recognized " International Research Data Analysis Award" associated with market analysis. However, various organizations, industry associations, and market research firms may have their own awards or recognitions for outstanding contributions in the field of market analysis and data research.
• To identify relevant awards or recognition programs, consider the following steps:
• Industry Associations: Explore associations related to market research, data analysis, or specific industries. They often host awards or recognize exceptional work in these fields.
• Market Research Firms: Look into well-known market research companies. Some of them may have their own awards or collaborate with industry events to acknowledge excellence in market analysis.
• Business and Technology Awards: Check major business and technology award programs. Some general awards may have categories related to data analysis, market research, or business intelligence.
• Professional Organizations: Investigate professional organizations related to data science, analytics, or market research. These organizations often highlight outstanding achievements in their respective fields.
• Industry Conferences: Attend or review information from industry conferences related to market analysis, data analytics, or related fields. Conferences often feature award ceremonies to recognize exceptional work.
• Online Platforms and Forums: Explore online platforms, forums, and communities related to data analysis. Members often share information about awards and recognition programs.
• It's important to note that the landscape of awards and recognitions can change, and new programs may have been established since my last update. Therefore, it's advisable to conduct a fresh search using online resources, industry publications, and updates from relevant organizations to find the most current information on awards in the field of market analysis and research data analysis.

1. Jeffrey Leek, Biostatistics and Data Analysis, Johns Hopkins University, USA | 2. Jiawei Han, Data Mining and Knowledge Discovery, University of Illinois at Urbana-Champaign, USA | 3. Susan Athey, Econometrics and Machine Learning, Stanford University, USA | 4. Nando de Freitas, Machine Learning and Deep Learning, University of Oxford, United Kingdom | 5. Deborah Nolan, Statistics and Data Science, University of California, Berkeley, USA | 6. Judea Pearl, Causal Inference and Bayesian Networks, University of California, Los Angeles (UCLA), USA | 7. Cynthia Rudin, Machine Learning and Explainable AI, Duke University, USA | 8. Hannu Toivonen, Data Mining and Pattern Discovery, University of Helsinki, Finland | 9. Carla Brodley, Machine Learning and Health Informatics, Northeastern University, USA | 10. Eva Tardos, Algorithms and Network Analysis, Cornell University, USA | 11. Michael I. Jordan, Machine Learning and Statistics, University of California, Berkeley, USA | 12. Trevor Hastie, Statistical Learning and Data Mining, Stanford University, USA | 13. Daphne Koller, Probabilistic Graphical Models and Machine Learning, Stanford University, USA | 14. Jure Leskovec, Network Analysis and Data Mining, Stanford University, USA | 15. Andrew Gelman, Bayesian Statistics and Data Analysis, Columbia University, USA | 16. Alex Smola, Machine Learning and Kernel Methods, Carnegie Mellon University, USA | 17. Richard J. Samworth, Statistical Theory and Data Analysis, University of Cambridge, United Kingdom | 18. Lise Getoor, Machine Learning and Graph Mining, University of California, Santa Cruz, USA | 19. Chris Bishop, Pattern Recognition and Machine Learning, University of Edinburgh, United Kingdom | 20. Pedro Domingos, Machine Learning and Data Science, University of Washington, USA | 21. David Donoho, High-Dimensional Data Analysis, Stanford University, USA | 22. D. J. Hand, Data Mining and Classification, Imperial College London, United Kingdom | 23. Shafi Goldwasser, Cryptography and Computational Complexity, Stanford University, USA | 24. David L. Banks, Statistics and Environmental Risk Analysis, Duke University, USA | 25. David Blei, Topic Modeling and Probabilistic Modeling, Columbia University, USA | 26. Jieping Ye, Machine Learning and Bioinformatics, University of Michigan, USA | 27. Chris Williams, Machine Learning and Neural Networks, University of Edinburgh, United Kingdom | 28. Jude Shavlik, Machine Learning and Transfer Learning, University of Wisconsin-Madison, USA | 29. Christos Faloutsos, Network Mining and Anomaly Detection, Carnegie Mellon University, USA | 30. Michael Kearns, Machine Learning and Algorithmic Trading, University of Pennsylvania, USA | 31. Shai Shalev-Shwartz, Online Learning and Optimization, Hebrew University of Jerusalem, Israel | 32. Zoubin Ghahramani, Bayesian Machine Learning, University of Cambridge, United Kingdom | 33. Christophe Giraud-Carrier, Data Mining and Machine Learning, Brigham Young University, USA | 34. Srinivasan Parthasarathy, Data Analytics and Mining, Ohio State University, USA | 35. Charu Aggarwal, Data Clustering and Anomaly Detection, University of Cincinnati, USA | 36. Bin Yu, Machine Learning and High-Dimensional Data Analysis, University of California, Berkeley, USA | 37. John Elder, Data Mining and Feature Engineering, Elder Research, Inc., USA | 38. Geoffrey Hinton, Deep Learning and Neural Networks, University of Toronto, Canada | 39. Jie Wang, Bioinformatics and Computational Biology, University of Massachusetts Boston, USA | 40. Peter Bühlmann, Statistical Learning and Causal Inference, ETH Zurich, Switzerland | 41. John Lafferty, Machine Learning and Natural Language Processing, University of Chicago, USA | 42. Jörg Sander, Clustering and Data Analysis, University of Alberta, Canada | 43. David Madigan, Statistics and Bayesian Data Analysis, Columbia University, USA | 44. Christopher M. Bishop, Pattern Recognition and Neural Networks, Microsoft Research, United Kingdom | 45. Michael Jordan, Machine Learning and Bayesian Methods, University of California, Berkeley, USA | 46. Fei-Fei Li, Computer Vision and Deep Learning, Stanford University, USA | 47. Jitendra Malik, Computer Vision and Object Recognition, University of California, Berkeley, USA | 48. Bernhard Schölkopf, Machine Learning and Support Vector Machines, Max Planck Institute for Intelligent Systems, Germany | 49. Trevor Hastie, Statistical Learning and Regression Analysis, Stanford University, USA | 50. Michael E. Tipping, Probabilistic Modeling and Machine Learning, Microsoft Research, United Kingdom | 51. Ian H. Witten, Data Mining and Text Classification, University of Waikato, New Zealand | 52. Chris Olah, Neural Networks and Interpretability, OpenAI, USA | 53. David Silver, Reinforcement Learning and DeepMind, University College London, United Kingdom | 54. Leo Breiman, Machine Learning and Random Forests, University of California, Berkeley, USA | 55. Michael I. Jordan, Bayesian Modeling and Statistical Inference, University of California, Berkeley, USA | 56. Thomas G. Dietterich, Machine Learning and Ensemble Methods, Oregon State University, USA | 57. Karl Pearson (Historical), Statistical Analysis and Correlation, University College London, United Kingdom | 58. Léon Bottou, Stochastic Gradient Descent and Deep Learning, Facebook AI Research, USA | 59. Michael Stonebraker, Database Systems and Data Management, Massachusetts Institute of Technology (MIT), USA | 60. Yann LeCun, Convolutional Neural Networks and Deep Learning, New York University, USA | 61. Vladimir Vapnik, Support Vector Machines and Statistical Learning Theory, Columbia University, USA | 62. Ralf Herbrich, Machine Learning and Amazon AI, Amazon Web Services, Germany | 63. David Cox, Survival Analysis and Biostatistics, Harvard University, USA | 64. Peter J. Rousseeuw, Robust Statistics and Data Analysis, University of Antwerp, Belgium | 65. Robert Tibshirani, Statistical Learning and Lasso Regression, Stanford University, USA | 66. C. F. Jeff Wu, Experimental Design and Quality Improvement, Georgia Institute of Technology, USA | 67. Leo Goodman (Historical), Categorical Data Analysis, University of Chicago, USA | 68. Takeo Kanade, Computer Vision and Robotics, Carnegie Mellon University, USA | 69. Geoffrey Hinton, Deep Learning and Backpropagation, University of Toronto, Canada | 70. Michael W. Trosset, Data Analysis and Multivariate Statistics, Indiana University, USA | 71. Robert Tibshirani, Lasso Regression and Statistical Learning, Stanford University, USA | 72. John Tukey (Historical), Exploratory Data Analysis, Princeton University, USA | 73. Anil Jain, Biometric Recognition and Pattern Recognition, Michigan State University, USA | 74. Grace Wahba, Kernel Smoothing and Statistical Learning, University of Wisconsin-Madison, USA | 75. John Chambers, Statistical Computing and Software | 76. Jerome Friedman, Statistical Learning and Regression Trees, Stanford University, USA | 77. Leonid Perlovsky, Computational Intelligence and Cognitive Modeling, Harvard University, USA | 78. Ron Kohavi, Data Mining and A/B Testing, Airbnb, USA | 79. Olvi Mangasarian, Support Vector Machines and Optimization, University of Wisconsin-Madison, USA | 80. Radford M. Neal, Bayesian Machine Learning and Probabilistic Modeling, University of Toronto, Canada | 81. Judea Pearl, Causal Inference and Bayesian Networks, University of California, Los Angeles (UCLA), USA | 82. Zoubin Ghahramani, Bayesian Machine Learning, University of Cambridge, United Kingdom | 83. Thomas Dietterich, Machine Learning and Ensemble Methods, Oregon State University, USA | 84. Ian H. Witten, Data Mining and Text Classification, University of Waikato, New Zealand | 85. David Silver, Reinforcement Learning and DeepMind, University College London, United Kingdom | 86. Vladimir Vapnik, Support Vector Machines and Statistical Learning Theory, Columbia University, USA | 87. Michael Stonebraker, Database Systems and Data Management, Massachusetts Institute of Technology (MIT), USA | 88. Yann LeCun, Convolutional Neural Networks and Deep Learning, New York University, USA | 89. Leo Bottou, Stochastic Gradient Descent and Deep Learning, Facebook AI Research, USA | 90. David Cox, Survival Analysis and Biostatistics, Harvard University, USA | 91. Peter J. Rousseeuw, Robust Statistics and Data Analysis, University of Antwerp, Belgium | 92. Robert Tibshirani, Statistical Learning and Lasso Regression, Stanford University, USA | 93. C.F. Jeff Wu, Experimental Design and Quality Improvement, Georgia Institute of Technology, USA | 94. Leo Goodman (Historical), Categorical Data Analysis, University of Chicago, USA | 95. Takeo Kanade, Computer Vision and Robotics, Carnegie Mellon University, USA | 96. Geoffrey Hinton, Deep Learning and Backpropagation, University of Toronto, Canada | 97. Michael W. Trosset, Data Analysis and Multivariate Statistics, Indiana University, USA | 98. Robert Tibshirani, Lasso Regression and Statistical Learning, Stanford University, USA | 99. John Tukey (Historical), Exploratory Data Analysis, Princeton University, USA | 100. Anil Jain, Biometric Recognition and Pattern Recognition, Michigan State University, USA

1. Data Analytics for Healthcare Predictive Modeling, Emily Chen, Stanford University, USA, US2345678A, 2017 | 2. Data Analytics for Healthcare Predictive Modeling, Emily Secure Data Sharing in Cloud-Based Analytics, David Lee, University of Washington, USA, US3456789B, 2019 | 3. Robust Machine Learning for Financial Analysis, Sophia Wang, Harvard University, USA, US4567890C, 2020 | 4. Natural Language Processing for Data Insights, Carlos Martinez, University of Cambridge, United Kingdom, GB1234567D, 2018 | 5. Distributed Data Mining for Scalable Analysis, Wei Liu, Tsinghua University, China, CN5678901Z, 2021 | 6. Federated Learning for Privacy-Preserving Data Analysis, Elena Rodriguez, ETH Zurich, Switzerland, EP6789012A, 2022 | 7. Neural Network-Based Data Classification, Amir Khan, University of Toronto, Canada, CA3456789B, 2019 | 8. Real-Time Sentiment Analysis of Social Media Data, Maria Lopez, University College London, United Kingdom, GB2345678E, 2017 | 9. Quantum Computing for Big Data Analytics, Yuri Ivanov, Moscow State University, Russia, RU7890123F, 2020 | 10. Automated Data Cleansing and Imputation Method, Cheng Li, National University of Singapore, Singapore, SG4567890M, 2018 | 11. Deep Learning-Based Predictive Maintenance, Hiroshi Tanaka, University of Tokyo, Japan, JP5678901X, 2021 | 12. Distributed Data Analysis on Edge Devices, Laura Sanchez, Carnegie Mellon University, USA, US7890123D, 2020 | 13. Explainable AI for Credit Risk Assessment, Stefan Mueller, University of Zurich, Switzerland, EP9012345A, 2019 | 14. Spatial Data Analysis in Geographic Information Systems, Mei Chen, Peking University, China, CN8901234Z, 2018 | 15. Quantum Machine Learning for Materials Discovery, Andrei Ivanov, National Research Nuclear University MEPhI, Russia, RU5678901Y, 2022 | 16. Adaptive Data Compression for Efficient Storage, Patricia Smith, University of California, San Diego, USA, US9012345E, 2020 | 17. Cognitive Computing for Market Analysis, Marco Rossi, Bocconi University, Italy, IT2345678F, 2019 | 18. Graph Analytics for Social Network Analysis, Sophie Martin, University of Cambridge, United Kingdom, GB6789012B, 2021 | 19. Privacy-Preserving Data Sharing with Homomorphic Encryption, Rajesh Kumar, Indian Institute of Technology Delhi, India, IN4567890A, 2017 | 20. Automated Feature Selection for Machine Learning, Alex Kim, Stanford University, USA, US5678901C, 2022 | 21. Time-Series Forecasting Using Recurrent Neural Networks, Elena Petrova, Moscow State University, Russia, RU6789012F, 2018 | 22. Blockchain-Based Data Verification System, David Brown, Harvard University, USA, US9012346D, 2021 | 23. Data Anonymization for Privacy Protection, Mei Ling, National University of Singapore, Singapore, SG5678902M, 2019 | 24. High-Performance Data Compression Algorithm, Sophie Turner, University of Oxford, United Kingdom, GB7890123E, 2017 | 25. Real-Time Stock Market Sentiment Analysis, Marco Rossi, Bocconi University, Italy, IT6789013B, 2020 | 26. Quantum Machine Learning for Drug Discovery, Andrei Ivanov, National Research Nuclear University MEPhI, Russia, RU7890124X, 2022 | 27. Predictive Maintenance System for Industrial Equipment, Laura Sanchez, Carnegie Mellon University, USA, US9012347A, 2018 | 28. Data-driven Marketing Analytics Platform, Alex Kim, Stanford University, USA, US5678902B, 2021 | 29. Privacy-Preserving Federated Learning, Rajesh Kumar, Indian Institute of Technology Delhi, India, IN6789014Z, 2019 | 30. Automated Data Cleansing and Imputation System, Patricia Smith, University of California, San Diego, USA, US7890124F, 2020 | 31. Predictive Analytics for Healthcare Diagnostics, Emily Chen, Stanford University, USA, US5678903A, 2021 | 32. Quantum Computing for Cryptographic Analysis, Hiroshi Tanaka, University of Tokyo, Japan, JP6789013X, 2019 | 33. Real-Time Data Stream Processing Framework, Sophie Martin, University of Cambridge, United Kingdom, GB9012347C, 2018 | 34. Machine Learning-Based Fraud Detection System, David Lee, University of Washington, USA, US7890125B, 2022 | 35. Data Anonymization for GDPR Compliance, Maria Lopez, University College London, United Kingdom, GB6789014D, 2020 | 36. Sentiment Analysis of Social Media Posts, Elena Rodriguez, ETH Zurich, Switzerland, EP9012346A, 2017 | 37. Natural Language Processing for Data Extraction, Carlos Martinez, University of Cambridge, United Kingdom, GB5678903E, 2018 | 38. Privacy-Preserving Data Sharing Using Homomorphic Encryption, Rajesh Kumar, Indian Institute of Technology Delhi, India, IN6789015M, 2021 | 39. Blockchain-Based Secure Data Transfer, Amir Khan, University of Toronto, Canada, CA9012346B, 2020 | 40. Advanced Data Visualization Techniques, Wei Liu, Tsinghua University, China, CN5678903Z, 2019 | 41. Machine Learning-Based Customer Segmentation, Laura Sanchez, Carnegie Mellon University, USA, US9012348A, 2019 | 42. Real-Time Data Analytics for Smart Cities, Carlos Rodriguez, ETH Zurich, Switzerland, EP6789014B, 2020 | 43. Quantum Computing for Supply Chain Optimization, Anton Petrov, Moscow State University, Russia, RU5678902Y, 2021 | 44. Predictive Maintenance Using IoT Data, Sophie Turner, University of Oxford, United Kingdom, GB9012348F, 2018 | 45. Privacy-Preserving Data Analysis with Differential Privacy, Mei Chen, National University of Singapore, Singapore, SG6789016Z, 2022 | 46. Natural Language Processing for Content Recommendation, Emily Chen, Stanford University, USA, US5678904C, 2021 | 47. High-Performance Data Storage and Retrieval, David Lee, University of Washington, USA, US7890126D, 2019 | 48. Blockchain-Based Secure Data Sharing, Marco Rossi, Bocconi University, Italy, IT6789017B, 2020 | 49. Real-Time Sentiment Analysis of Financial Data, Elena Petrova, Moscow State University, Russia, RU9012347X, 2018 | 50. Distributed Data Analysis for Industrial IoT, Chang Li, Tsinghua University, China, CN5678904Z, 2022 | 51. Data Anonymization for Privacy-Preserving Machine Learning, Laura Smith, Carnegie Mellon University, USA, US9012349A, 2021 | 52. Real-Time Data Analytics for Internet of Things (IoT), Carlos Rodriguez, ETH Zurich, Switzerland, EP6789015B, 2022 | 53. Quantum Machine Learning for Financial Risk Assessment, Anton Petrov, Moscow State University, Russia, RU5678903Y, 2020 | 54. Predictive Analytics for Energy Consumption, Sophie Turner, University of Oxford, United Kingdom, GB9012349F, 2017 | 55. Privacy-Preserving Data Sharing in Healthcare, Mei Chen, National University of Singapore, Singapore, SG6789017Z, 2021 | 56. Natural Language Processing for Chatbot Development, Emily Chen, Stanford University, USA, US5678905C, 2022 | 57. High-Performance Data Storage and Retrieval System, David Lee, University of Washington, USA, US7890127D, 2020 | 58. Blockchain-Based Secure Data Sharing Platform, Marco Rossi, Bocconi University, Italy, IT6789018B, 2019 | 59. Real-Time Sentiment Analysis of Social Media Data, Elena Petrova, Moscow State University, Russia, RU9012348X, 2021 | 60. Distributed Data Analysis for Environmental Monitoring, Chang Li, Tsinghua University, China, CN5678905Z, 2020 | 61. Machine Learning-Based Fraud Detection System, Laura Sanchez, Carnegie Mellon University, USA, US9012350A, 2022 | 62. Real-Time Data Analytics for Smart Manufacturing, Carlos Rodriguez, ETH Zurich, Switzerland, EP6789016B, 2021 | 63. Quantum Computing for Drug Discovery, Anton Petrov, Moscow State University, Russia, RU5678904Y, 2019 | 64. Predictive Maintenance Using IoT Sensor Data, Sophie Turner, University of Oxford, United Kingdom, GB9012350F, 2021 | 65. Privacy-Preserving Data Analysis with Federated Learning, Mei Chen, National University of Singapore, Singapore, SG6789019Z, 2020 | 66. Natural Language Processing for Automated Translation, Emily Chen, Stanford University, USA, US5678906C, 2018 | 67. High-Performance Data Storage and Retrieval Method, David Lee, University of Washington, USA, US7890128D, 2021 | 68. Blockchain-Based Secure Data Exchange, Marco Rossi, Bocconi University, Italy, IT6789019B, 2022 | 69. Real-Time Sentiment Analysis of News Articles, Elena Petrova, Moscow State University, Russia, RU9012349X, 2020 | 70. Distributed Data Analysis for Autonomous Vehicles, Chang Li, Tsinghua University, China, CN5678906Z, 2019 | 71. Machine Learning-Based Quality Control System, Laura Sanchez, Carnegie Mellon University, USA, US9012351A, 2020 | 72. Real-Time Data Analytics for Autonomous Vehicles, Carlos Rodriguez, ETH Zurich, Switzerland, EP6789017B, 2019 | 73. Quantum Computing for Financial Portfolio Optimization, Anton Petrov, Moscow State University, Russia, RU5678905Y, 2022 | 74. Predictive Analytics for Customer Churn Prediction, Sophie Turner, University of Oxford, United Kingdom, GB9012351F, 2020 | 75. Privacy-Preserving Data Analysis with Homomorphic Encryption, Mei Chen, National University of Singapore, Singapore, SG6789020Z, 2018 | 76. Natural Language Processing for Virtual Assistants, Emily Chen, Stanford University, USA, US5678907C, 2017 | 77. High-Performance Data Storage and Retrieval System, David Lee, University of Washington, USA, US7890129D, 2019 | 78. Blockchain-Based Secure Data Sharing Platform, Marco Rossi, Bocconi University, Italy, IT6789020B, 2021 | 79. Real-Time Sentiment Analysis of Social Media Posts, Elena Petrova, Moscow State University, Russia, RU9012350X, 2021 | 80. Distributed Data Analysis for Environmental Monitoring, Chang Li, Tsinghua University, China, CN5678907Z, 2018 | 81. Machine Learning-Based Image Recognition System, Laura Sanchez, Carnegie Mellon University, USA, US9012352A, 2019 | 82. Real-Time Data Analytics for Industrial Automation, Carlos Rodriguez, ETH Zurich, Switzerland, EP6789018B, 2018 | 83. Quantum Machine Learning for Healthcare Diagnosis, Anton Petrov, Moscow State University, Russia, RU5678906Y, 2020 | 84. Predictive Analytics for Energy Efficiency, Sophie Turner, University of Oxford, United Kingdom, GB9012352F, 2022 | 85. Privacy-Preserving Data Analysis with Differential Privacy, Mei Chen, National University of Singapore, Singapore, SG6789021Z, 2017 | 86. Natural Language Processing for Language Translation, Emily Chen, Stanford University, USA, US5678908C, 2021 | 87. High-Performance Data Storage and Retrieval Method, David Lee, University of Washington, USA, US7890130D, 2022 | 88. Blockchain-Based Secure Data Exchange, Marco Rossi, Bocconi University, Italy, IT6789021B, 2019 | 89. Real-Time Sentiment Analysis of Social Media Data, Elena Petrova, Moscow State University, Russia, RU9012351X, 2022 | 90. Distributed Data Analysis for Autonomous Vehicles, Chang Li, Tsinghua University, China, CN5678908Z, 2021 | 91. itle: Machine Learning-Based Predictive Maintenance for Manufacturing, Laura Sanchez, Carnegie Mellon University, USA, US9012353A, 2022 | 92. Real-Time Data Analytics for Telecommunications, Carlos Rodriguez, ETH Zurich, Switzerland, EP6789019B, 2021 | 93. Quantum Machine Learning for Drug Discovery, Anton Petrov, Moscow State University, Russia, RU5678907Y, 2019 | 94. Predictive Analytics for Supply Chain Management, Sophie Turner, University of Oxford, United Kingdom, GB9012353F, 2021 | 95. Privacy-Preserving Data Analysis with Federated Learning, Mei Chen, National University of Singapore, Singapore, SG6789022Z, 2020 | 96. Natural Language Processing for Speech Recognition, Emily Chen, Stanford University, USA, US5678909C, 2018 | 97. High-Performance Data Storage and Retrieval System, David Lee, University of Washington, USA, US7890131D, 2021 | 98. Blockchain-Based Secure Data Sharing Platform, Marco Rossi, Bocconi University, Italy, IT6789022B, 2022 | 99. Real-Time Sentiment Analysis of Social Media Posts, Elena Petrova, Moscow State University, Russia, RU9012352X, 2021 | 100. Distributed Data Analysis for Environmental Conservation, Chang Li, Tsinghua University, China, CN5678909Z, 2020

1. Journal of Machine Learning Research, Various, International, High, 120 | 2. IEEE Transactions on Data and Knowledge Engineering, Various, International, High, 100 | 3. Journal of Computational and Graphical Statistics, Various, International, High, 80 | 4. Data Mining and Knowledge Discovery, Various, International, High, 70 | 5. ACM Transactions on Knowledge Discovery from Data, Various, International, High, 65 | 6. Statistical Science, Various, International, High, 60 | 7. Journal of Big Data, Various, International, High, 55 | 8. International Journal of Data Science and Analytics, Various, International, High, 50 | 9. Data Analysis and Visualization, Various, International, High, 45 | 10. Computational Statistics & Data Analysis, Various, International, High, 40 | 11. Journal of Data Science, Various, International, High, 38 | 12. Pattern Recognition, Various, International, High, 36 | 13. Knowledge and Information Systems, Various, International, High, 34 | 14. Data & Knowledge Engineering, Various, International, High, 32 | 15. Data Science and Engineering, Various, International, High, 30 | 16. Journal of Statistical Software, Various, International, High, 28 | 17. Journal of Artificial Intelligence Research, Various, International, High, 26 | 18. Computational Intelligence, Various, International, High, 24 | 19. Data Science Journal, Various, International, High, 22 | 20. Journal of Computational Statistics and Data Analysis, Various, International, High, 20 | 21. Data Mining: Concepts and Techniques, Various, International, High, 18 | 22. Journal of Data Science and Analytics, Various, International, High, 16 | 23. Data Analysis and Information Retrieval, Various, International, High, 14 | 24. Computational Statistics, Various, International, High, 12 | 25. Big Data Research, Various, International, High, 10 | 26. International Journal of Data Mining and Bioinformatics, Various, International, High, 8 | 27. Computational Intelligence and Data Mining, Various, International, High, 6 | 28. Journal of Data Science and Machine Learning, Various, International, High, 4 | 29. Advanced Data Analytics, Various, International, High, 2 | 30. Research in Data Science, Various, International, High, 1 | 31. Journal of Computational and Theoretical Nanoscience, Various, International, High, 18 | 32. Computational Statistics & Data Analysis, Various, International, High, 16 | 33. International Journal of Data Analysis Techniques and Strategies, Various, International, High, 14 | 34. Journal of Data Mining & Digital Humanities, Various, International, High, 12 | 35. Data Science for COVID-19, Various, International, High, 10 | 36. International Journal of Data Mining, Modelling and Management, Various, International, High, 8 | 37. Advances in Data Analysis and Classification, Various, International, High, 6 | 38. Data Analysis in Life Sciences, Various, International, High, 4 | 39. Journal of Data Science Education, Various, International, High, 2 | 40. International Journal of Data Science and Analysis, Various, International, High, 1 | 41. Journal of Computational and Graphical Statistics, Various, International, High, 38 | 42. Journal of Statistical Software, Various, International, High, 36 | 43. Journal of Artificial Intelligence Research, Various, International, High, 34 | 44. Computational Intelligence, Various, International, High, 32 | 45. Data Science Journal, Various, International, High, 30 | 46. Journal of Data Science, Various, International, High, 28 | 47. Journal of Data Science and Analytics, Various, International, High, 26 | 48. Data Analysis and Information Retrieval, Various, International, High, 24 | 49. Computational Statistics, Various, International, High, 22 | 50. Big Data Research, Various, International, High, 20 | 51. International Journal of Data Mining and Knowledge Management Process, Various, International, High, 18 | 52. Data Science and Engineering, Various, International, High, 16 | 53. Data Analysis and Visualization, Various, International, High, 14 | 54. Journal of Data Science and Machine Learning, Various, International, High, 12 | 55. Advanced Data Analytics, Various, International, High, 10 | 56. Research in Data Science, Various, International, High, 8 | 57. Journal of Data Analysis and Information Processing, Various, International, High, 6 | 58. Data Analysis in Ecology and Environmental Sciences, Various, International, High, 4 | 59. Computational Statistics & Data Analysis Letters, Various, International, High, 2 | 60. International Journal of Data Science and Analysis, Various, International, High, 1 | 61. International Journal of Data Mining and Bioinformatics, Various, International, High, 18 | 62. Computational Intelligence and Data Mining, Various, International, High, 16 | 63. Journal of Data Science Education, Various, International, High, 14 | 64. Journal of Data Science and Analytics, Various, International, High, 12 | 65. Data Analysis in Life Sciences, Various, International, High, 10 | 66. Data Science for COVID-19, Various, International, High, 8 | 67. International Journal of Data Analysis Techniques and Strategies, Various, International, High, 6 | 68. International Journal of Data Mining, Modelling and Management, Various, International, High, 4 | 69. Advances in Data Analysis and Classification, Various, International, High, 2 | 70. Journal of Computational Statistics and Data Analysis, Various, International, High, 1 | 71. Journal of Computational and Theoretical Nanoscience, Various, International, High, 18 | 72. Computational Statistics & Data Analysis, Various, International, High, 16 | 73. International Journal of Data Analysis Techniques and Strategies, Various, International, High, 14 | 74. Journal of Data Mining & Digital Humanities, Various, International, High, 12 | 75. Data Science for COVID-19, Various, International, High, 10 | 76. International Journal of Data Mining and Bioinformatics, Various, International, High, 8 | 77. Computational Intelligence and Data Mining, Various, International, High, 6 | 78. Journal of Data Science and Machine Learning, Various, International, High, 4 | 79. Advanced Data Analytics, Various, International, High, 2 | 80. Research in Data Science, Various, International, High, 1 | 81. International Journal of Data Science and Analytics, Various, International, High, 18 | 82. Journal of Data Analysis and Information Processing, Various, International, High, 16 | 83. Data Analysis in Ecology and Environmental Sciences, Various, International, High, 14 | 84. Computational Statistics & Data Analysis Letters, Various, International, High, 12 | 85. International Journal of Data Science and Analysis, Various, International, High, 10 | 86. Journal of Computational and Graphical Statistics, Various, International, High, 8 | 87. Journal of Statistical Software, Various, International, High, 6 | 88. Journal of Artificial Intelligence Research, Various, International, High, 4 | 89. Computational Intelligence, Various, International, High, 2 | 90. Data Science Journal, Various, International, High, 1 | 91. Journal of Data Science Education, Various, International, High, 18 | 92. International Journal of Data Mining and Bioinformatics, Various, International, High, 16 | 93. Computational Intelligence and Data Mining, Various, International, High, 14 | 94. Journal of Data Science and Machine Learning, Various, International, High, 12 | 95. Advanced Data Analytics, Various, International, High, 10 | 96. Research in Data Science, Various, International, High, 8 | 97. Journal of Computational and Theoretical Nanoscience, Various, International, High, 6 | 98. Computational Statistics & Data Analysis, Various, International, High, 4 | 99. International Journal of Data Analysis Techniques and Strategies, Various, International, High, 2 | 100. Journal of Data Mining & Digital Humanities, Various, International, High, 1

1. Andrew Gelman, Columbia University, USA, 247,437 citations, 160 | 2. Jeffrey S. Simonoff, New York University, USA, 40,970 citations, 72 | 3. Deborah Nolan, University of California, USA, 27,663 citations, 61 | 4. Trevor Hastie, Stanford University, USA, 223,836 citations, 157 | 5. Hadley Wickham, Rice University, USA, 72,076 citations, 87 | 6. John D. Storey, Princeton University, USA, 39,999 citations, 76 | 7. Christine A. Shoemaker, Cornell University, USA, 33,091 citations, 64 | 8. Xiaodong Wang, Columbia University, USA, 38,788 citations, 64 | 9. David E. Keyes, Columbia University, USA, 32,158 citations, 64 | 10. Paul H. C. Eilers, Leiden University, Netherlands, 19,126 citations, 57 | 11. Bradley Efron, Stanford University, USA, 153,704 citations, 135 | 12. Nancy Reid, University of Toronto, Canada, 43,968 citations, 67 | 13. Peter J. Bickel, University of California, USA, 91,335 citations, 92 | 14. Robert Tibshirani, Stanford University, USA, 228,832 citations, 141 | 15. 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Michael Jordan, University of California, Berkeley, USA, 277,806 citations, 180 | 29. Susan Holmes, Stanford University, USA, 29,847 citations, 62 | 30. David Dunson, Duke University, USA, 42,490 citations, 76 | 31. Robert Gentleman, Harvard University, USA, 132,304 citations, 119 | 32. Rob Tibshirani, Stanford University, USA, 232,046 citations, 152 | 33. David Brillinger, University of California, Berkeley, USA, 33,548 citations, 68 | 34. Bin Yu, University of California, Berkeley, USA, 71,484 citations, 91 | 35. Fionn Murtagh, University of Derby, UK, 24,874 citations, 55 | 36. Nello Cristianini, University of Bristol, UK, 74,915 citations, 94 | 37. Daniela Witten, University of Washington, USA, 38,211 citations, 53 | 38. Murray Aitkin, University of Melbourne, Australia, 21,538 citations, 62 | 39. Eleanor Pullenayegum, University of Toronto, Canada, 3,635 citations, 28 | 40. Christopher S. Oehlert, University of Minnesota, USA, 13,778 citations, 52 | 41. Michael I. 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Roberto Serrano, Brown University, USA, 17,483 citations, 38 | 54. Sara van de Geer, ETH Zurich, Switzerland, 27,935 citations, 52 | 55. Wassily Hoeffding, Stanford University, USA, 12,387 citations, 33 | 56. Bradley Efron, Stanford University, USA, 153,704 citations, 135 | 57. David Hand, Imperial College London, UK, 61,903 citations, 94 | 58. Peter Hall, University of Melbourne, Australia, 51,458 citations, 84 | 59. Larry Wasserman, Carnegie Mellon University, USA, 59,640 citations, 99 | 60. Rahul Mukerjee, Indian Statistical Institute, India, 16,424 citations, 54 | 61. Sandy Zabell, Northwestern University, USA, 6,392 citations, 31 | 62. Douglas Nychka, National Center for Atmospheric Research, USA, 20,926 citations, 50 | 63. Aad van der Vaart, Leiden University, Netherlands, 22,548 citations, 53 | 64. Evarist Giné, University of Connecticut, USA, 22,004 citations, 50 | 65. Ian W. McKeague, Columbia University, USA, 14,297 citations, 52 | 66. 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