Mayank Lunayach
Papers
1
Total Citations
2
H-Index
1
About
Dr. Mayank Lunayach is a rising researcher in artificial intelligence, specializing in continual learning, few-shot learning, and embodied AI. His most notable contribution is the introduction of **Lifelong Wandering**, a realistic few-shot online continual learning setting that challenges models to learn emerging object classes from a continuous stream of data in dynamic environments—moving beyond static indoor datasets. This work, published in 2022, has already garnered attention for bridging the gap between controlled benchmarks and real-world deployment, where agents must adapt on the fly with minimal supervision. By emphasizing online, few-shot constraints, Lunayach addresses critical limitations in prior continual learning approaches, which often assume batch updates or stable environments. His research has implications for autonomous robotics and lifelong learning systems, pushing the field toward more practical, scalable solutions. With early citations reflecting growing interest, Lunayach is establishing himself as a forward-thinking voice in next-generation machine learning, particularly for agents that must learn continuously in the wild.
Research Focus
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Top Papers
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