Hisashi Shidara

Hokkaido University, Hokkaido University of Science

Papers

2

Total Citations

19

H-Index

2

About

Hisashi Shidara is a researcher at the intersection of robotics, ethology, and machine learning. His work focuses on developing novel technologies to observe and analyze animal behavior, particularly for wandering species. Shidara’s key contributions include the creation of a markerless visual servo control system for a servosphere—a robotic observation platform that creates an endless field for tracking animal movement. This innovation, detailed in his 2019 paper (9 citations), eliminates the need for physical markers, enabling more naturalistic studies. He also pioneered an efficient learning algorithm for sparse subsequence pattern-based classification, applied to comparative animal trajectory data analysis (2019, 10 citations). This method converts complex time-series movement data into symbolic sequences, allowing researchers to uncover behavioral patterns that were previously hidden. Shidara’s work is instrumental in bridging engineering and biology, providing tools that allow biologists to gain deeper insights into animal navigation, foraging, and social interactions. His research stands out for its practical impact, offering scalable solutions for automated, high-throughput behavioral analysis in comparative biology.

Research Focus

Key Achievements

2
H-Index
2
Papers
19
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
Efficient learning algorithm for sparse subsequence pattern-based classification and applications to comparative animal trajectory data analysis
10 citations · 2019
📈 Most Prolific Year: 2019 (2 Papers)
🤝 Key Collaborators: 20
🏛 Institutions: Hokkaido University, Hokkaido University of Science

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago