Ganeshsree Selvachandran

UCSI University, Monash University Malaysia

Papers

Total Citations

H-Index

About

Ganeshsree Selvachandran is a leading researcher in computational intelligence, specializing in fuzzy set theory, soft computing, and decision-making under uncertainty. Her most influential work introduces the **complex vague soft set (CVSS) model**, a groundbreaking hybrid of complex fuzzy sets and soft sets that captures two-dimensional, periodic information—enabling more accurate representations of real-world phenomena like seasonal trends or cyclical data. This foundational paper has garnered **37 citations**, underscoring its impact on advancing uncertainty modeling. More recently, Selvachandran has expanded into reinforcement learning, co-authoring a comprehensive 2025 review on **inverse reinforcement learning** that synthesizes advances in reward function learning—a critical challenge for autonomous systems. With a growing citation footprint, her work bridges theoretical innovation and practical application, from vague entropy measures to AI-driven decision frameworks. Her contributions are shaping how researchers handle complex, time-varying data and design intelligent agents, making her a key voice in the evolution of soft computing and machine learning.