Masayuki Karasuyama
Papers
1
Total Citations
10
H-Index
1
About
Masayuki Karasuyama is a leading researcher in machine learning and data science, with a core focus on developing efficient algorithms for complex, real-world data analysis. His work bridges computational methods and biological applications, particularly through the analysis of high-dimensional and sequential data. Karasuyama’s major contributions include a novel learning algorithm for sparse subsequence pattern-based classification, which he applied to comparative animal trajectory data analysis—a field transformed by advances in robotics and measurement technologies. This work, published in 2019, has garnered 10 citations and exemplifies his ability to translate machine learning innovations into practical biological insights. By converting time series of animal movements into sequences of finite symbols, his method enables robust classification and pattern discovery from noisy, high-dimensional trajectory data. Karasuyama’s research is notable for its interdisciplinary impact, offering tools that empower biologists to extract meaningful behavioral patterns from complex movement datasets. His work continues to influence the development of efficient, interpretable machine learning techniques for sequential data analysis.
Research Focus
Key Achievements
Top Papers
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