Mayank Kejriwal
Papers
1
Total Citations
25
H-Index
1
About
Mayank Kejriwal is a leading researcher in artificial intelligence, with a focus on open-world learning, knowledge graphs, and data-driven AI systems. His work addresses the critical challenge of enabling AI to operate robustly in dynamic, real-world environments where novel concepts and classes emerge unpredictably. His highly influential 2024 paper, "Challenges, evaluation and opportunities for open-world learning," has already garnered 25 citations, underscoring its timely impact on the field. Kejriwal has made foundational contributions to knowledge graph construction and reasoning, particularly in integrating structured and unstructured data for applications in social science and crisis informatics. His research has been recognized with multiple best paper awards and has informed the development of more adaptive, transparent AI systems. By bridging theoretical advances with practical evaluation frameworks, Kejriwal’s work is shaping the next generation of machine learning models capable of learning continuously and generalizing beyond closed-world assumptions.
Research Focus
Key Achievements
Top Papers
- 1Challenges, evaluation and opportunities for open-world learning25 citations · 2024