Angeliki Pantazi

IBM Research - Zurich

Papers

2

Total Citations

42

H-Index

2

About

Angeliki Pantazi is a pioneering researcher at the intersection of neuromorphic computing, in-memory computing, and edge artificial intelligence. Her work addresses one of the most pressing challenges in modern AI: enabling intelligent systems to operate efficiently in resource-constrained, real-world environments without relying on power-hungry cloud infrastructure. Pantazi's research on phase-change memory-based in-memory computing represents a significant leap forward, demonstrating how hardware-software co-design can enable rapid, autonomous learning — a capability critical for AI systems that must adapt on-the-fly at deployment sites. Her acclaimed 2025 study on learning-to-learn with phase-change memory has already garnered 22 citations, reflecting its immediate impact on the field. Equally impressive is her contribution to neuromorphic optical flow processing using event cameras, which has attracted 20 citations since 2023 and offers transformative potential for robotics and computer vision at the edge, dramatically reducing latency and energy consumption. Together, these works establish Pantazi as a leading voice shaping the future of efficient, biologically-inspired computing systems — research that holds profound implications for autonomous robots, IoT devices, and the next generation of adaptive AI hardware.

Research Focus

Key Achievements

2
H-Index
2
Papers
42
Total Citations
21
Avg Citations/Paper
🏆 Most Cited Paper
Rapid learning with phase-change memory-based in-memory computing through learning-to-learn
22 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 16
🏛 Institutions: IBM Research - Zurich

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 16 days ago