Artificial Intelligence and Machine Learning Competition

Competition Submission Deadline: June 10, 2025

Submission Link: https://www.xcdsystem.com/IEOM/abstract/index.cfm?ID=7g4uDnr
Registration Link: https://www.xcdsystem.com/IEOM/attendee/index.cfm?ID=FmpG68d

The AI and Data Analytics discusses the latest advancements, trends, and applications of AI and data-driven strategies across various industries, including higher education. By highlighting cutting-edge research, real-world case studies, and emerging technologies, the discussion aims to provide invaluable insights into how businesses can leverage AI and data analytics to drive innovation, enhance decision-making, and maintain a competitive edge in an increasingly data-centric world.

• Trends in AI and Data Analytics
• AI in Education Transformation
• Big Data Management and IA Business Transformation
• Ethics and Governance in AI
• Challenges in AI Deployment
• Future of AI and Data Analytics

IEOM Competition Rubrics

• Overall content: 1-5 points
• Data analysis and results: 1-5 points
• Presentation skills: 1-5 points
• Knowledge of the topic / confident: 1-5 points
• Answering questions: 1-5 points

IEOM Publication Ethics and Malpractice Statement

Each paper must present a significant research contribution, encompassing:

1. Motivation of the Research: Clearly state the relevance of the research and its importance within the field.
2. Problem Statements and Objectives: Identify the specific problem(s) addressed and outline clear, measurable objectives.
3. Literature Review: Provide a comprehensive review of relevant research to establish the context and background.
4. Data: Describe the data sources, collection methods, and any preprocessing steps undertaken.
5. Methods: Detail the methodologies used, including the rationale behind their selection.
6. Results: Include both numerical and graphical results, effectively presenting key findings.
7. Statistical Analysis and Hypothesis Tests: Perform appropriate statistical tests to validate findings, presenting results with proper interpretation.
8. Research Validation: Demonstrate that each objective has been met through quantitative or qualitative analysis, confirming the reliability of the results.
9. Technical Writing Quality: Ensure the paper is well-written, free from spelling and grammatical errors, and follows a clear, logical structure.

Each paper and its abstract must strictly adhere to the IEOM Template for consistent formatting, including fonts, headings, and layout.