Leman Akoglu

Title: Leman Akoglu: Innovator in Anomaly Detection and Data Clustering

Introduction

Leman Akoglu is a prominent inventor based in Pittsburgh, PA (US). He has made significant contributions to the field of data analysis, particularly in the areas of anomaly detection, association, and clustering techniques. With a total of 5 patents to his name, Akoglu's work has had a substantial impact on how data is interpreted and utilized in various applications.

Latest Patents

One of Leman Akoglu's latest patents focuses on techniques for anomaly, association, and clustering detection. This innovative approach involves building at least one code table for each attribute in a dataset. The process includes selecting a first code table corresponding to a first attribute and a second code table for a second attribute. These code tables are then merged into a combined code table, which is evaluated for acceptance or rejection. An anomaly is identified when the total compression cost for a data point exceeds a threshold compression cost derived from one or more code tables. Additionally, associations within a data table are detected by merging attribute groups, splitting data groups, and assigning data points accordingly. Clusters are inferred from a matrix of data and code words associated with the code tables.

Career Highlights

Leman Akoglu is currently employed at International Business Machines Corporation, commonly known as IBM. His role at IBM allows him to leverage his expertise in data analysis and contribute to cutting-edge technological advancements. His work has been instrumental in enhancing the capabilities of data processing and interpretation.

Collaborations

Throughout his career, Leman Akoglu has collaborated with notable colleagues, including Hanghang Tong and Rohit Madhukar Khandekar. These collaborations have fostered a rich exchange of ideas and have led to significant advancements in their respective fields.

Conclusion

Leman Akoglu is a distinguished inventor whose work in anomaly detection and data clustering has paved the way for innovative solutions in data analysis. His contributions continue to influence the industry and inspire future advancements in technology.