The committee includes Professors and Industry Leaders in Data Science & Artificial Intelligence from all over the world. The committee composition is as follows:

Dr. Krishna R. Pattipati, Board of Trustees Distinguished Professor & UTC Professor in Systems Engineering, Department of Electrical and Computer Engineering, University of Connecticut, Connecticut, USA

Dr. Rajakumar Arul, Assistant Professor, School of Computer Science and Engineering (SCOPE), Vellore Institute of Technology (VIT) Chennai Campus, India

Dr. Mohammad Soltanieh-ha, Assistant Professor, Questrom School of Business, Boston University, Massachusetts, USA

Dr. Shaimaa Ali, Assistant Professor (Software Engineering) at the Electrical and Computer Engineering Department, Western University, London, Ontario N6A 3K7, Canada

Dr. Adisak Sukul, Associate Teaching Professor at Department of Computer Science, Iowa State University, Iowa, USA

Dr. Haiyang Kong, Assistant Professor, Business School of Beijing Normal University, Beijing, China

Dr. Vinh Dang, Lecturer, Information Technology Faculty, Industrial University of HCM City, Vietnam

Dr. Gia Nhu Nguyen, Associate Professor & Dean of School of Computer Science, Duy Tan University, Vietnam

Dr. Bao The Pham, Associate Professor at Saigon University, Vietnam

Dr. Christopher Do, ISODS President, Massachusetts, USA

Dr. Nam Nguyen, ISODS Vice President and Staff Data Scientist at Wayfair, Texas, USA

Mr. Cory Wang, ISODS Vice President, Connecticut, USA

Dr. Phu Vu, Regional Research Director, WorldQuant, Vietnam

Dr. Nam Thanh Nguyen, FUNiX Founder, Former FPT CEO, Vietnam

This year ISODS organizes three competition tracks based on Kaggle platform, including Natural Language Processing, Computer Vision, and Structured Data tracks. Tentatively, a separate track in Statistical Data Science for highschool students will be held separately (to be announced later).

Problem: Build your Data Science or AI projects, present it to the committee.

Delivery: Each team will record a 3-minute video of the presentation, and post it on Youtube. The submission will include the links to the presentation video, as well as the GitHub repository   

Problem set: 2-3 problems hosted on LightOJ platform.

The International Society of Data Scientists is calling for Statistical Analysis project submissions from young Data Scientists. Participants should be high school students or last year middle school students. Submissions are reports for projects that have been pursued in courses, training, and camps. Projects may be team-based or individual-based. Participants should be able to provide evidence that the projects were supervised, or graded by their instructors. 

Committee Chairs:

Dr. Nguyet Nguyen, Associate Professor, Youngstown State University, Ohio, USA

Dr. Nam Nguyen, ISODS Vice President

Mr. Cory Wang, ISODS Vice President

The committee will judge the reports on the following:

Question to answer using statistical analysis: The statistical question that you try to solve should be clearly stated, and data that supports the analysis should be attainable.

Data Collection: Candidates should be able to provide evidence that the data was collected by themselves. Candidates should explore the data to determine if the data quality is adequate to answer the question, and demonstrate the understanding of the data. A data quality report that includes data summaries may be provided.

Data Visualization/Exploration: Relevant well-labeled, and accurate graphs and tables of the data should be included.

Data Analysis: Expected level of statistical methods should be found in an introductory statistics course, which may include descriptive statistics, basic sampling methods, designed experiments, probability, confidence intervals (parametric and non-parametric approaches), hypothesis testing, simple or multiple linear regression, one- or two-factor ANOVA, simulation-based inference (randomization tests or bootstrapping), and other nonparametric methods.

Strength and Weakness: Candidates are required to evaluate the strength and weakness of the project.

Conclusion: The conclusion should reprise the questions and the answer, and should provide an overall picture of the project. Candidates should note what have been done or haven't, what may be the next steps for further study.

Final report: Details for the steps described above form the final report. The final report should be well-organized, and well-written.

Please submit your project using this form. For minors ( <18 years old), the submitter should be the parents or teachers. The sender email address should be of the parents or teachers if the student is a minor.

Currently the entry fee is waived for all participants for this track this year.

Top performers will be selected to submit their reports as conference papers in the related conference by ISODS.

Top performers in track 1 are considered passing the ISODS Machine Learning exam; in track 2 as passing the Deep Learning 1 (DL1) exam; in track 3 as passing the Deep Learning 2 (DL2) exam.

See more about ISODS Professional Exams organized by the International Institute of Data Science and Artificial Intelligence at ISODS website (https://www.isods.org).

Please write to contact@isods.org if you would like to sponsor the event