Heidelberg, Germany

Mandana Samii

This inventor holds 2 USPTO granted patents. Top assignees: Sap Ag, Sap Se. Active years: 2008-2018.


% Patents Active = 100.0

Average Co-Inventor Count = 4.5

ph-index = 1

Forward Citations = 56(Granted Patents)


Location History:

  • Rauenberg, DE (2008)
  • Heidelberg, DE (2018)

Company Filing History:


Years Active: 2008-2018

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2 patents (USPTO):Explore Patents

Title: Mandana Samii: Innovator in Data Visualization

Introduction

Mandana Samii is a notable inventor based in Heidelberg, Germany. He has made significant contributions to the field of data visualization, particularly in the context of managing large data volumes. With a total of 2 patents, his work has focused on creating intuitive interfaces that enhance user interaction with complex datasets.

Latest Patents

One of Mandana Samii's latest patents is the "Tag cloud visualization and/or filter for large data volumes." This innovative interactive tag cloud provides an intuitive interface to large data volumes, allowing users to quickly assess high-level contours of the data. The tag cloud can filter big data efficiently, enabling non-developer users to focus on specific tasks. It indicates data priority based on frequency of incidence or other criteria, affording visibility to aggregated big data content before users drill down for details.

Career Highlights

Throughout his career, Mandana has worked with prominent companies such as SAP SE and SAP AG. His experience in these organizations has contributed to his expertise in data management and visualization technologies.

Collaborations

Mandana has collaborated with various professionals in his field, including Peer Hilgers and Esther M. Blankenship. Their combined efforts have further advanced the development of innovative solutions in data visualization.

Conclusion

Mandana Samii's contributions to data visualization through his patents and career experiences highlight his role as an influential inventor in the tech industry. His work continues to impact how users interact with large datasets, making complex information more accessible and manageable.

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