Track 10 Data Science & Artificial Intelligence (CDSA)
Key Details
Host Centre: Brij Disa Centre for Data Science and Artificial Intelligence (CDSA)
Submission Requirements: Extended Abstract (1000 words)
Submission Link: https://easychair.org/conferences/?conf=imrc2025
Awards: Two Best Papers: INR 10,000 each
Call for Papers
Business analytics is undergoing a profound transformation, propelled by breakthroughs in artificial intelligence, machine learning and real-time data processing. These advancements are redefining how organizations derive insights, refine strategies, and sustain a strategic edge in an increasingly data-driven world. The Brij Disa Centre for Data Science and Artificial Intelligence (CDSA), invites paper submissions for its track on Data Science & Artificial Intelligence, which explores cutting-edge advancements and methodologies that are redefining the future of analytics, with a particular emphasis on business applications.
The track encapsulates a broad range of topics such as predictive analytics, machine learning algorithms, deep learning frameworks, the use of optimization techniques for prescriptive analytics and upcoming technologies in AI & business analytics. Papers may focus on both theoretical foundations and practical applications with strong contributions in at least one of the two focus areas.
Participants can submit papers from various business research topics, including but not limited to big data analytics techniques, user and enterprise-generated content analytics, analytics for emerging technologies, business applications of deep learning, analytics for social good, ethical and legal issues in analytics, social media analytics, future of work, GenAI for business, image and video analytics in business, supply chain analytics, retail analytics, assortment optimization, dynamic pricing and nonlinear pricing, logistics optimization, supply chain optimization, algorithms for multi-period optimization, network algorithms, causal inference, high-dimensional data modelling and clustering approaches, risk modelling, fraud detection, and secure AI applications, hybrid AI and computational approaches for business decision-making, etc.
Categories include:
- Predictive Analytics: Theory and Methods
- Prescriptive Analytics: Theory and Methods
- Prescriptive Analytics Based on Prediction: Theory and Applications
- Predictive Analytics: Innovative Applications
- Prescriptive Analytics: Innovative Applications