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For the Inventor, By the Inventor

Zurich, Switzerland

Thomas P Parnell

This inventor holds 68 USPTO granted patents and 5 published patent applications, primarily in Machine Learning Optimization (CPC class G06F). Top assignees: International Business Machines Corporation, Other. Active years: 2016-2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Thomas P Parnell. Retrieved from https://idiyas.com/inventor/thomas-p-parnell

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

Calculating rank
USPTO Granted Patents = 68 

% Patents Active = 58.8

Average Co-Inventor Count = 5.1

ph-index = 9

Forward Citations = 249(Granted Patents)

Forward Citations (Not Self Cited) = 201(Dec 10, 2025)


Inventors with similar research interests:


Location History:

  • Zurich, GB (2016)
  • Rueschlikon, CH (2017 - 2018)
  • Zürich, CH (2016 - 2022)
  • Zurich, CH (2016 - 2024)

Company Filing History:

goldMedal67 out of 166,524 
 
International Business Machines Corporation
 patents
silverMedal1 out of 834,708 
Other
 patents

Years Active: 2016-2026

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Areas of Expertise:
Decision Tree Inferences
Machine Learning Models
Data Compression
Non-Volatile Memory
Memory Selection Scheme
Recommender Systems
Error-Correction Encoding
Data Protection Techniques
Workload Adaptation
Parallel Training
Context Model Ensemble
Hash Computations
68 patents (USPTO):Explore Patents
1. 12775502 - Cross cloud serving (2026-10-27),
2. 12651197 - Selection of a machine learning model (2026-06-09),
3. 12541572 - Accelerating decision tree inferences based on complementary tensor operation sets (2026-02-03),
4. 12487862 - Configuration and optimization of a source of computerized resources (2025-12-02),
5. 12462201 - Dynamically optimizing decision tree inferences (2025-11-04),
6. 12423589 - Training decision tree-based predictive models (2025-09-23),
7. 12175377 - Joint execution of decision tree nodes for accelerating inferences (2024-12-24),
8. 11886960 - Elastic training of machine learning models via re-partitioning based on feedback from the training algorithm (2024-01-30),
9. 11803779 - Constructing an ensemble model from randomly selected base learners (2023-10-31),
10. 11573803 - Parallel training of machine learning models (2023-02-07),
11. 11562270 - Straggler mitigation for iterative machine learning via task preemption (2023-01-24),
12. 11461694 - Machine learning implementation in processing systems (2022-10-04),
13. 11315035 - Machine learning in heterogeneous processing systems (2022-04-26),
14. 11301776 - Memory-based data selection scheme for machine learning training on limited memory resources (2022-04-12),
15. 11295236 - Machine learning in heterogeneous processing systems (2022-04-05),

Title: Thomas P. Parnell - Innovative Inventor from Zurich

Introduction: Thomas P. Parnell is a renowned inventor based in Zurich, Switzerland, known for his groundbreaking contributions to various fields of technology and science.

Latest Patents: Thomas P. Parnell holds several patents in the areas of renewable energy, nanotechnology, and biomedicine, showcasing his versatility and forward-thinking approach to innovation.

Career Highlights: With a career spanning over two decades, Thomas P. Parnell has worked with leading research institutions and universities worldwide, pushing the boundaries of what is possible in the realm of inventions.

Collaborations: Throughout his career, Thomas P. Parnell has collaborated with top companies, banks, and research institutions, fostering a culture of innovation and excellence in all his projects.

Conclusion: Thomas P. Parnell's passion for innovation and his relentless pursuit of excellence have solidified his position as a pioneering inventor in the global technological landscape.

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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