Jalisco, Mexico

Dario BahenaTapia


Average Co-Inventor Count = 4.0

ph-index = 1


Company Filing History:


Years Active: 2022

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1 patent (USPTO):Explore Patents

Title: Innovations by Dario BahenaTapia in Anomaly Detection

Introduction

Dario BahenaTapia is an accomplished inventor based in Jalisco, Mexico. He has made significant contributions to the field of anomaly detection, showcasing his expertise through his patented work. His innovative solutions leverage advanced statistical methods to improve the monitoring of data behavior in various systems.

Latest Patents

Dario holds a patent titled "Systems and methods for unsupervised anomaly detection using non-parametric tolerance intervals over a sliding window of t-digests." This patent describes systems and methods for unsupervised training and evaluation of anomaly detection models. In this method, an approximation of a data distribution for a training dataset is generated, which includes varying values for a computing resource metric. The innovation employs quantile probabilities to define intervals that cover a prescribed proportion of values within a specific confidence level. Such a model can effectively monitor data inputs for anomalous behavior and trigger actions in response.

Career Highlights

Dario is currently employed at Oracle International Corporation, where his work continues to address complex challenges in data management and analysis. His career is marked by a commitment to enhancing technology and creating intelligent systems that can adapt to varying data conditions.

Collaborations

Throughout his career, Dario has had the opportunity to work with talented colleagues, including Sampanna Shahaji Salunke and Dustin R Garvey. These collaborations have broadened the scope of his projects and allowed for diverse input in the development of innovative solutions.

Conclusion

Dario BahenaTapia exemplifies the spirit of innovation within the realm of anomaly detection. Through his patented contributions and collaborative efforts, he is paving the way for more reliable and efficient data monitoring systems in the technological landscape. His work not only enhances understanding in the field but also reinforces the importance of continuous advancement in innovative methodologies.

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