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

Marc Böhlen, Professor, Department of ART, Emerging Practices in Computational Media, University at Buffalo, New York, USA

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

Dr. Manar Alalfi, Associate Professor in Software Engineering, Ryerson University, Toronto, Ontario M5B 2K3, Canada; Adjunct Assistant Professor, Queen's University School of Computing, Kingston, Ontario K7L 3N6, Canada

Dr. Sebastian Tomczak, Department of Operations Research and Business Intelligence, Faculty of Management, Wroclaw University of Science and Technology, Wrocław, Poland

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

Dr. Renzhi Cao, Assistant Professor, Department of Computer Science, Pacific Lutheran University, Washington, USA

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

Dr. Hoa Trung Dinh, Assistant Professor, Troy University, Alabama, USA

Dr. Kim Phuc Tran, Associate Professor, University of Lille, Lille, France

Dr. Lan Vu, Professor, Department Head and Chair at Hanoi University of Public Health, Vietnam

Dr. Duy Nguyen, Assistant Professor, Marist College, New York, USA

Dr. Hoan Nguyen, Computer Scientist, Jackson Lab, Connecticut, USA

Dr. Bay Dinh Vo, Associate Professor, HUTECH University of Technology, Vietnam

Dr. Son P Nguyen, Lecturer at University of Economics and Law, Vietnam

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. Loan Nguyen, Associate Professor at International 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. Quang Hieu Vu, Head of Data Platform, ZaloPay

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

 

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: Fashion and Beauty Review Classification

Committee Chairs:

Dr. Renzhi Cao, Assistant Professor at the Department of Computer Science, Pacific Lutheran University (Washington, USA)

Dr. Phu Vu, Regional Research Director at WorldQuant

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

Dr. Jianmo Ni, Software Engineer, Google

Dr. Christopher Do, ISODS President

Dr. Nam Nguyen, ISODS Vice President

Mr. Cory Wang, ISODS Vice President

Problem: Classification of plants of Southeast Asia

Committee Chairs:

Dr. Shaima Ali, Assistant Professor (Software Engineering), Electrical and Computer Engineering Department, Western University (Canada)

Marc Böhlen, Professor, Department of ART, Emerging Practices in Computational Media, University at Buffalo, New York, USA

Dr. Quang Hieu Vu, Head of Data Platform at ZaloPay

Dr. Christopher Do, ISODS President

Dr. Nam Nguyen, ISODS Vice President

Mr. Cory Wang, ISODS Vice President

Problem: Company Bankruptcy Prediction

Committee Chairs:

Dr. Sebastian Tomczak, Department of Operations Research and Business Intelligence, Faculty of Management, Wroclaw University of Science and Technology, Wrocław, Poland

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

Dr. Christopher Do, ISODS President

Dr. Nam Nguyen, ISODS Vice President

Mr. Cory Wang, ISODS Vice President

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).

We would like to thank Addison Howard and Laurie White at Google, who help during the setting-up phase.

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