Tomi Johan Poutanen

USPTO Granted Patents = 13 (Patent Applications = 19)

CIPO Patents = 2 (Patent Applications = 14)

Average Co-Inventor Count = 2.2

ph-index = 6

Forward Citations = 222(Granted Patents)

Company Filing History:

6 out of 774

The Toronto-dominion Bank

Microsoft Technology Licensing, LLC

Years Active: 1999-2025

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13 patents (USPTO):Sort by Forward Citations

Abstract keywords

1. 12387145 - Prediction of future occurrences of events using adaptively trained artificial-intelligence processes and contextual data (2025-08-12),

2. 12124925 - Dynamic analysis and monitoring of machine learning processes (2024-10-22),

3. 11030415 - Learning document embeddings with convolutional neural network architectures (2021-06-08),

4. 10932003 - Method and system for making recommendations from binary data using neighbor-score matrix and latent factors (2021-02-23),

5. 10824941 - End-to-end deep collaborative filtering (2020-11-03),

6. 10360303 - Learning document embeddings with convolutional neural network architectures (2019-07-23),

7. 9507827 - Encoding and accessing position data (2016-11-29),

8. 8509266 - Using network traffic logs for search engine index updates (2013-08-13),

9. 8203952 - Using network traffic logs for search enhancement (2012-06-19),

10. 8078642 - Concurrent traversal of multiple binary trees (2011-12-13),

11. 7996397 - Using network traffic logs for search enhancement (2011-08-09),

12. 7398271 - Using network traffic logs for search enhancement (2008-07-08),

13. 5978795 - Temporally ordered binary search method and system (1999-11-02),

Title: The Innovative Journey of Tomi Johan Poutanen

Introduction: Tomi Johan Poutanen is a prolific inventor based in Toronto, Canada, renowned for his contributions to machine learning and document analysis. With a total of 12 patents to his name, Poutanen has demonstrated a commitment to innovation that is reshaping the landscape of technology.

Latest Patents: Among his notable inventions are two recent patents that illustrate his expertise in advanced computational processes. The first, titled Dynamic analysis and monitoring of machine learning processes, involves computer-implemented methods that analyze machine learning processes dynamically. This patent describes an apparatus capable of generating analytical output that characterizes the operation of a machine learning process over multiple periods. The apparatus processes feature data from datasets and generates modified feature vectors, leading to the production of explainability data for machine learning applications.

The second patent, Learning document embeddings with convolutional neural network architectures, presents a novel document analysis system. This system trains a document embedding model to translate an ordered set of words into a latent representation that captures content, structure, and sentiment. By employing a convolutional neural network architecture, the model effectively addresses the challenges posed by variable-length documents, enabling efficient analysis and predictions of follow-up words.

Career Highlights: Poutanen has worked with leading companies in the tech industry, including Yahoo! Inc. and TD Bank. His experience with these organizations has provided him with invaluable insights into the intersection of data science and financial technology, further enhancing his innovative capabilities.

Collaborations: Throughout his career, Poutanen has collaborated with talented professionals such as Maksims Volkovs and Arkady Borkovsky. These partnerships have been vital in advancing his research and strengthening his patented innovations.

Conclusion: Tomi Johan Poutanen stands out as a prominent figure in the realm of innovation, particularly within the fields of machine learning and document processing. His contributions continue to influence the industry, showcasing the transformative power of inventive thinking in today's technology-driven world.

This text is generated by artificial intelligence and may not be accurate.