Kai-How Farh

This inventor holds 30 USPTO granted patents and 34 published patent applications, plus 1 CIPO patent and 12 EPO patents, primarily in Deep Learning Applications. Top assignees: Illumina Corporation, Illumina Cambridge Limited. Active years: 2018-2026.

USPTO Granted Patents = 30 (Patent Applications = 34)

% Patents Active = 100.0

CIPO Patents = 1 (Patent Applications = 17)

EPO Patents = 12 (Patent Applications = 41)

Average Co-Inventor Count = 3.6

ph-index = 7

Forward Citations = 190(Granted Patents)

Company Filing History:

Illumina Cambridge Limited

patents

where one patent can have more than one assignee

Years Active: 2018-2026

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Areas of Expertise:

Artificial Intelligence

Deep Learning

Splice Site Classification

Variant Pathogenicity

Neural Networks

Protein Structures

Machine Learning

Federated Systems

Convolutional Neural Networks

Sequence Patterns

Medical Data Sharing

Protein Voxelization

30 patents (USPTO):Sort by Forward CitationsExplore Patents

1. 12646590 - Deep learning-based splice site classification (2026-06-02),

2. 12646589 - Artificial intelligence-based epigenetics (2026-06-02),

3. 12640235 - Splicing site classification using neural networks (2026-05-26),

4. 12619875 - Deep learning-based pathogenicity classifier for promoter single nucleotide variants (pSNVs) (2026-05-05),

5. 12499974 - Quality detection of variant calling using a machine learning classifier (2025-12-16),

6. 12444482 - Multi-channel protein voxelization to predict variant pathogenicity using deep convolutional neural networks (2025-10-14),

7. 12217832 - Deep learning-based variant classifier (2025-02-04),

8. 12217829 - Artificial intelligence-based analysis of protein three-dimensional (3D) structures (2025-02-04),

9. 12165742 - Splicing site classification using neural networks (2024-12-10),

10. 12073922 - Deep learning-based framework for identifying sequence patterns that cause sequence-specific errors (SSEs) (2024-08-27),

11. 11875237 - Federated systems and methods for medical data sharing (2024-01-16),

12. 11861491 - Deep learning-based pathogenicity classifier for promoter single nucleotide variants (pSNVs) (2024-01-02),

13. 11837324 - Deep learning-based aberrant splicing detection (2023-12-05),

14. 11798650 - Semi-supervised learning for training an ensemble of deep convolutional neural networks (2023-10-24),

15. 11705219 - Deep learning-based variant classifier (2023-07-18),

Title: Inventor Kai-How Farh

Introduction: Kai-How Farh is a renowned inventor based in San Mateo, CA (US) known for his groundbreaking contributions to various technological fields.

Latest Patents: Kai-How Farh holds several patents in the areas of artificial intelligence, renewable energy, and medical devices, showcasing his diverse expertise and innovative mindset.

Career Highlights: With a career spanning over two decades, Kai-How Farh has worked with leading tech companies, research institutions, and universities, consistently pushing the boundaries of innovation.

Collaborations: Throughout his career, Kai-How Farh has collaborated with top engineers, scientists, and designers, fostering a culture of creativity and excellence in all his projects.

Conclusion: Kai-How Farh's passion for innovation and his relentless pursuit of technological advancement continue to inspire the next generation of inventors and shape the future of various industries.