This inventor holds 1 USPTO granted patent and 1 published patent application. Top assignee: Hewlett-Packard Development Company, L.p.. Active years: 2020.
Company Filing History:
Years Active: 2020
Title: Dominik Jackle: Innovator in Multidimensional Event Analysis
Introduction
Dominik Jackle is a notable inventor based in Palo Alto, California. He has made significant contributions to the field of event analysis through his innovative patent. His work focuses on the visualization of event similarities using multidimensional scaling, which has applications in various domains.
Latest Patents
Dominik Jackle holds a patent titled "Pixel-based temporal plot of events according to multidimensional scaling values based on event similarities and weighted dimensions." This patent describes a method for computing similarities between events that involve multiple dimensions. The similarities are determined through binary comparisons and user-specified weights for each dimension. The resulting multidimensional scaling (MDS) values are used to create a graphical visualization of a temporal plot, which includes time and MDS values on its axes. This innovative approach allows for the representation of overlapping time slices, with pixels indicating subsets of the events.
Career Highlights
Dominik Jackle is currently employed at Hewlett-Packard Development Company, L.P. His role at this esteemed organization allows him to further his research and development in the field of event analysis. His work has the potential to influence various industries by providing insights into event relationships and dynamics.
Collaborations
Some of Dominik's coworkers include Ming C. Hao and Nelson L. Chang. Their collaboration contributes to a rich environment of innovation and creativity within their team.
Conclusion
Dominik Jackle's contributions to the field of event analysis through his patent demonstrate his innovative spirit and dedication to advancing technology. His work at Hewlett-Packard Development Company, L.P. continues to pave the way for new methodologies in understanding complex event relationships.
