Andrew Pannone

Pennsylvania State University

Papers

1

Total Citations

3

H-Index

1

About

Andrew Pannone is a rising leader in the emerging field of bio-inspired neuromorphic electronics, with a focus on developing intelligent sensors that mimic biological vision systems. His most-cited work introduces an insect-inspired, spike-based collision detector that operates effectively in low-light and nighttime conditions—a critical challenge for autonomous vehicles and drones. By leveraging atomically thin, light-sensitive memtransistors, Pannone created an in-sensor computing platform that processes visual information directly at the sensor level, bypassing the need for bulky, power-hungry conventional cameras and processors. This approach not only reduces latency and energy consumption but also enables robust performance in complex terrestrial and extraterrestrial environments. With his 2022 paper already garnering significant attention, Pannone’s contributions are shaping the future of edge computing and autonomous navigation. His work exemplifies how interdisciplinary research—combining materials science, neuroscience, and engineering—can yield practical, nature-inspired solutions for real-world sensing challenges.

Research Focus

Key Achievements

1
H-Index
1
Papers
3
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
An insect-inspired, spike-based, in-sensor, and night-time collision detector based on atomically thin and light-sensitive memtransistors
3 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Pennsylvania State University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago