Kailash Gopalakrishnan

This inventor holds 77 USPTO granted patents and 4 published patent applications and 3 EPO patents, primarily in Deep Learning Hardware (CPC class H01L). Top assignees: International Business Machines Corporation, Globalfoundries Inc., Leland Stanford Junior University. Active years: 2008-2026.

USPTO Granted Patents = 77 (Patent Applications = 4)

% Patents Active = 62.3

EPO Patents = 3 (Patent Applications = 4)

Average Co-Inventor Count = 3.2

ph-index = 8

Forward Citations = 334(Granted Patents)

Forward Citations (Not Self Cited) = 283(Dec 10, 2025)

Inventors with similar research interests:

Location History:

Mountain View, CA (US) (2008 - 2013)
New York, NY (US) (2016 - 2023)
San Jose, CA (US) (2008 - 2024)
Yorktown Heights, NY (US) (2024)

Company Filing History:

75 out of 166,159

International Business Machines Corporation

Leland Stanford Junior University

patents

Years Active: 2008-2026

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Areas of Expertise:

Machine Learning

Neural Network Circuitry

Matrix Multiplication

Deep Learning

Low Precision Formats

Systolic Arrays

Weight Quantization

Dataflow Architecture

Floating Point Representation

SIMD Execution Units

Parameter Update

Compression Techniques

77 patents (USPTO):Sort by Forward CitationsExplore Patents

1. 12689537 - Single-producer-multiple consumers synchronization and multicast data transfer (2026-07-21),

2. 12639396 - Reformatting of tensors to provide sub-tensors (2026-05-26),

3. 12443841 - Four-bit training for machine learning (2025-10-14),

4. 12399743 - Padding input data for artificial intelligence accelerators (2025-08-26),

5. 12236338 - Single function to perform combined matrix multiplication and bias add operations (2025-02-25),

6. 12217158 - Neural network circuitry having floating point format with asymmetric range (2025-02-04),

7. 12175359 - Machine learning hardware having reduced precision parameter components for efficient parameter update (2024-12-24),

8. 12141513 - Method to map convolutional layers of deep neural network on a plurality of processing elements with SIMD execution units, private memories, and connected as a 2D systolic processor array (2024-11-12),

9. 11977974 - Compression of fully connected / recurrent layers of deep network(s) through enforcing spatial locality to weight matrices and effecting frequency compression (2024-05-07),

10. 11941111 - Exploiting fine-grained structured weight sparsity in systolic arrays (2024-03-26),

11. 11775257 - Enhanced low precision binary floating-point formatting (2023-10-03),

12. 11669489 - Sparse systolic array design (2023-06-06),

13. 11620105 - Hybrid floating point representation for deep learning acceleration (2023-04-04),

14. 11604647 - Mixed precision capable hardware for tuning a machine learning model (2023-03-14),

15. 11551077 - Statistics-aware weight quantization (2023-01-10),

Title: The Innovator Extraordinaire: Kailash Gopalakrishnan

Introduction:

Kailash Gopalakrishnan, a prolific inventor based in San Jose, CA, has made significant strides in the tech world with his groundbreaking innovations. With an impressive portfolio of 67 patents, he continues to push the boundaries of technology and computation.

Latest Patents:

Among his recent patents is the groundbreaking "Enhanced low precision binary floating-point formatting" technique. This innovation revolutionizes the way binary floating-point numbers are operated on and calculated, offering enhanced precision and efficiency in computing-intensive applications.

Another notable patent is the "Sparse systolic array design," which optimizes resource efficiency in systolic arrays by skipping distributed operands with zero-values. This design improvement showcases Kailash's commitment to enhancing computational efficiency.

Career Highlights:

Kailash Gopalakrishnan has lent his expertise to renowned institutions and companies, including IBM (International Business Machines Corporation) and Leland Stanford Junior University. His contributions have been instrumental in shaping cutting-edge technologies and advancing computational capabilities.

Collaborations:

Throughout his career, Kailash has collaborated with esteemed colleagues such as Jungwook Choi and Bahman Hekmatshoartabari. Together, they have synergized their expertise to drive innovation and tackle complex technological challenges.

Conclusion:

In conclusion, Kailash Gopalakrishnan stands as a trailblazing inventor whose ingenuity and dedication have left an indelible mark on the tech industry. His pioneering patents and collaborations underscore his commitment to driving technological advancement and revolutionizing computational capabilities.