Toronto, Canada

Maksims Volkovs

This inventor holds 31 USPTO granted patents and 122 published patent applications, plus 11 CIPO patents and 1 EPO patent, primarily in Artificial Intelligence. Top assignee: The Toronto-Dominion Bank. Active years: 2019-2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Maksims Volkovs. Retrieved from https://idiyas.com/inventor/maksims-volkovs

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

USPTO Granted Patents = 31 

% Patents Active = 74.2

 

 

Average Co-Inventor Count = 3.7

ph-index = 8

Forward Citations = 438(Granted Patents)


Company Filing History:


Years Active: 2019-2026

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Areas of Expertise:
Multi-Event Encoding
Fraud Prediction
Machine Learning
Image Retrieval
Document Embeddings
Dynamic Analysis
Collaborative Filtering
Neural Networks
AI Processes
Query Expansion
Engagement Prediction
Action Selection
31 patents (USPTO):Explore Patents

Title: Innovations and Contributions of Maksims Volkovs in the Field of Artificial Intelligence

Introduction: Maksims Volkovs, based in Toronto, Canada, is an accomplished inventor with 18 patents to his name. His innovative spirit and contributions to the field of artificial intelligence have led to significant advancements that are being utilized in various applications. Maksims is known for his work at the Toronto-Dominion Bank, where he collaborates with fellow experts to enhance technological frameworks through his inventions.

Latest Patents: Among his notable patents, two stand out for their pioneering approaches. The first is the "Prediction of future occurrences of events using adaptively trained artificial-intelligence processes and contextual data." This patent outlines a computer-implemented system that dynamically predicts future events by utilizing adaptively trained AI processes alongside contextual data. The system effectively generates input datasets based on interaction data and applies gradient-boosted, decision-tree processes to ascertain the likelihood of future occurrences, refining the predictions based on temporal intervals.

The second patent, "Automated image retrieval with image graph," introduces an advanced image retrieval system that efficiently identifies relevant images from a repository. This innovative approach utilizes an image retrieval graph to establish connections between image nodes, evaluating their similarities through edge weights. The system is adept at traversing and exploring nodes to generate query results, illustrating a significant enhancement in image-based data retrieval methodologies.

Career Highlights: Maksims Volkovs has demonstrated a strong commitment to innovation throughout his career at the Toronto-Dominion Bank. His technical expertise in artificial intelligence and machine learning has propelled his work, allowing him to develop systems that integrate seamlessly into banking operations. With a robust portfolio of patents, Maksims continues to contribute to the evolving landscape of financial technology.

Collaborations: Collaborating with esteemed colleagues such as Guangwei Yu and Tomi Johan Poutanen, Maksims has fostered a dynamic work environment that encourages creativity and technical advancement. Together, they have worked on a variety of projects that push the boundaries of what is possible with AI technology in finance and beyond.

Conclusion: In summary, Maksims Volkovs is a prominent inventor whose contributions in artificial intelligence are shaping the future of technological applications within the banking industry and other sectors. His innovative patents not only reveal his genius but also underscore the evolving nature of AI, marking him as a significant figure in modern invention. With continued collaboration and a forward-thinking mindset, Maksims is poised to make further impactful contributions in the years to come.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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