Manzar Abbas
Papers
2
Total Citations
37
H-Index
2
About
Manzar Abbas is a researcher at the forefront of integrating artificial intelligence into agriculture and robotics. His work primarily focuses on leveraging machine and deep learning to address critical challenges in plant science, particularly the management of biotic and abiotic stresses. In his highly cited 2024 paper, "Machine and Deep Learning: Artificial Intelligence Application in Biotic and Abiotic Stress Management in Plants," Abbas explores how AI can decode the complex effects of environmental and biological stressors on plant fitness, from metabolite biosynthesis to gene expression. This work, which has already garnered 32 citations, underscores the transformative potential of AI in safeguarding global food production. Beyond agriculture, Abbas is pioneering advances in multirobot exploration. His 2025 study, "Population‐Based Optimization With Decentralized Method," tackles the real-time dynamic allocation of exploratory missions in uncertain environments, introducing a novel hybrid stochastic optimization approach. This dual expertise—bridging agricultural resilience with autonomous systems—positions Abbas as a versatile innovator whose contributions are shaping both sustainable farming and intelligent robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2Population‐Based Optimization With Decentralized Method5 citations · 2025