Corvallis, OR, United States of America

Raviv Raich

USPTO Granted Patents = 1 

Average Co-Inventor Count = 4.0

ph-index = 1

Forward Citations = 6(Granted Patents)


Company Filing History:


Years Active: 2010

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1 patent (USPTO):Explore Patents

Title: Raviv Raich: Innovator in Multicolor Cytometry Data Visualization

Introduction

Raviv Raich is a notable inventor based in Corvallis, OR (US). She has made significant contributions to the field of data visualization, particularly in the area of multicolor cytometry. Her innovative approach has led to the development of a unique method that enhances the understanding of complex data sets.

Latest Patents

Raviv Raich holds a patent for a "Method and apparatus for clustering and visualization of multicolor cytometry data." This computer-implemented method provides a systematic approach for clustering and visualizing n-dimensional data in a Euclidean space. The process involves collecting multiple multi-dimensional data sets, estimating probability density functions, and creating a dissimilarity matrix. The method further includes embedding this matrix into a three-dimensional Euclidean space and graphically displaying the relationships between the data sets on a computing device.

Career Highlights

Raviv Raich is affiliated with the University of Michigan, where she continues to advance her research and innovation in data visualization. Her work has garnered attention for its practical applications in various scientific fields, enhancing the ability to interpret complex data.

Collaborations

Raviv has collaborated with esteemed colleagues, including Alfred Hero and Kevin Carter. These partnerships have contributed to the depth and impact of her research, fostering an environment of innovation and discovery.

Conclusion

Raviv Raich's contributions to the field of multicolor cytometry data visualization exemplify the power of innovation in transforming complex data into understandable insights. Her work continues to influence the scientific community and pave the way for future advancements in data analysis.

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