Papers
11
Total Citations
346
H-Index
8
About
Harish Garg is a prolific researcher whose work sits at the dynamic intersection of fuzzy set theory, decision-making frameworks, and intelligent robotics systems. His scholarship has made substantial contributions to the development and application of advanced fuzzy mathematical structures — including T-spherical fuzzy sets, Fermatean fuzzy information, neutrosophic sets, and complex vague soft sets — primarily directed toward solving real-world uncertainty and decision-making problems. Garg's most celebrated work, on T-spherical fuzzy Hamacher aggregation operators applied to search-and-rescue robot evaluation, has garnered over 136 citations, reflecting the field's recognition of his innovative approach to multi-attribute decision-making under uncertainty. His research consistently bridges abstract mathematical theory with practical engineering challenges, including industrial robot selection, robotic sensor design, wireless sensor network optimization, and micro-robotic position control via hybrid meta-heuristic algorithms. Beyond robotics, Garg has contributed meaningfully to fuzzy graph theory and shortest-path problems in interval-valued fuzzy networks, demonstrating impressive breadth. His body of work, spanning entropy measures, risk assessment methodologies like FMEA-LOPCOW-ARAS, and complex intuitionistic fuzzy relations, has positioned him as an authoritative voice in computational intelligence. With hundreds of cumulative citations across diverse venues, Garg's research continues to meaningfully shape how uncertainty is modeled and managed across engineering and technology domains.
Research Focus
Key Achievements
Top Papers
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- 3Vague Entropy Measure for Complex Vague Soft Sets37 citations · 2018
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