Track 10: Data Science & Artificial Intelligence (CDSA)
Key Details
Host Centre: Brij Disa Centre for Data Science and Artificial Intelligence (CDSA) and Krishnamurthy Tandon School of Artificial Intelligence
Submission Requirements: Extended Abstract (1000 words)
Submission Link: https://easychair.org/conferences/?conf=imrc2026
Awards:
Oral Presentation:
1. Best Paper Award – INR 15,000/-
2. Runner-up Award – INR 10,000/-
Poster Presentation:
Best Poster Award – INR 5000/-
For any query related to Track 10, please write to: parthm@iima.ac.in
Call for Papers
Organizations are undergoing a profound transformation, propelled by advances in artificial intelligence, machine learning and real-time data processing. These advancements are redefining how organizations operate, compete and create value in an increasingly data-driven world. This track invites rigorous empirical, theoretical and methodological contributions that deepen our understanding of AI-driven transformation. We are particularly interested in advancements in data science and AI with a focus on business, policy and societal outcomes.
We invite submissions on a broad range of topics, including but not limited to the following:
AI and Organizational Transformation
• AI-driven business models and digital transformation
• Human–AI collaboration and augmentation of work
• AI in strategic decision-making and leadership
• Organizational design in the age of automation
Machine Learning and Advanced Analytics
• Predictive, prescriptive, and causal analytics
• Deep learning, reinforcement learning, and generative AI
• Explainable and interpretable AI
• Scalable and real-time analytics systems
Data-Driven Decision-Making
• Data governance, data quality, and data infrastructure
• Decision intelligence and algorithmic management
• A/B testing, experimentation, and causal inference
• Behavioural implications of data-driven systems
AI Applications Across Domains
• Marketing analytics and personalization
• Finance, fintech, and risk modeling
• Operations, supply chain, and logistics optimization
• Healthcare analytics and digital health
• Public policy, governance, and smart cities
Ethics, Fairness, and Responsible AI
• Bias, fairness, and accountability in AI systems
• Privacy, security, and regulatory frameworks
• Societal and economic implications of AI adoption
• Responsible innovation and AI governance
Emerging Frontiers
• Generative AI and large language models in organizations
• AI for sustainability and ESG outcomes
• Platform ecosystems and data marketplaces
• AI in emerging markets and developing economies