IDiyas

For the Inventor, By the Inventor

Ottawa, Canada

Seyednaser Nourashrafeddin

USPTO Granted Patents = 12 

 

Average Co-Inventor Count = 5.5

ph-index = 1

Forward Citations = 10(Granted Patents)


Company Filing History:

goldMedal12 out of 71 
 
Kinaxis Inc.
 patents

Years Active: 2020-2025

where 'Filed Patents' based on already Granted Patents

12 patents (USPTO):
1. 12488053 - Machine learning segmentation methods and systems (2025-12-02),
2. 12412137 - Analysis and correction of supply chain design through machine learning (2025-09-09),
3. 12393907 - Analysis and correction of supply chain design through machine learning (2025-08-19),
4. 12242954 - Interactive machine learning (2025-03-04),
5. 12154013 - Interactive machine learning (2024-11-26),
6. 11887044 - Analysis and correction of supply chain design through machine learning (2024-01-30),
7. 11886514 - Machine learning segmentation methods and systems (2024-01-30),
8. 11748678 - Analysis and correction of supply chain design through machine learning (2023-09-05),
9. 11361276 - Analysis and correction of supply chain design through machine learning (2022-06-14),
10. 11188856 - Analysis and correction of supply chain design through machine learning (2021-11-30),
11. 10846651 - Analysis and correction of supply chain design through machine learning (2020-11-24),
12. 10832196 - Analysis and correction of supply chain design through machine learning (2020-11-10),

Title: Seyednaser Nourashrafeddin: Innovator in Supply Chain Design

Introduction

Seyednaser Nourashrafeddin is a prominent inventor based in Ottawa, Canada. He has made significant contributions to the field of supply chain design through his innovative use of machine learning technologies. With a total of 11 patents to his name, Seyednaser has established himself as a key figure in advancing supply chain management practices.

Latest Patents

One of Seyednaser's latest patents is focused on the analysis and correction of supply chain design through machine learning. This patent describes a method and system for conducting a machine learning cluster analysis of historical lead time data, which is enhanced by various features. The data can be categorized into groups based on the time-density of the data, with clustering performed on each group. Additionally, the historical lead time data is divided into multiple tolerance zones according to specific criteria. The clusters are then separated based on the tolerance zone of each group and further distinguished according to one or more lead time identifiers, resulting in several distinct clusters. Another notable patent involves a dynamic supply chain planning system that utilizes machine learning algorithms to forecast future lead times based on historical lead time data, weather data, and financial data related to specific locations and dates within the supply chain.

Career Highlights

Seyednaser Nourashrafeddin currently works at Kinaxis Inc., a company renowned for its innovative supply chain management solutions. His work at Kinaxis has allowed him to apply his expertise in machine learning to real-world supply chain challenges, enhancing the efficiency and effectiveness of supply chain operations.

Collaborations

Seyednaser has collaborated with talented individuals such as Zhen Lin and Chantal Bisson-Krol, contributing to the development of advanced supply chain solutions.

Conclusion

Seyednaser Nourashrafeddin is a distinguished inventor whose work in supply chain design through machine learning has made a significant impact in the industry. His innovative patents and contributions to Kinaxis Inc. highlight his commitment to advancing supply chain management practices.

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