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For the Inventor, By the Inventor

San Jose, CA, United States of America

Kailash Gopalakrishnan

LinkedIn
USPTO Granted Patents = 75 

 

Average Co-Inventor Count = 3.1

ph-index = 8

Forward Citations = 320(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:

goldMedal73 out of 164,135 
 
International Business Machines Corporation
 patents
silverMedal1 out of 5,307 
 
Leland Stanford Junior University
 patents
bronzeMedal1 out of 5,671 
 
Globalfoundries Inc.
 patents

Years Active: 2008-2025

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Areas of Expertise:
Machine Learning
Neural Networks
Systolic Arrays
Deep Learning Acceleration
Floating Point Representation
Quantization Techniques
Dataflow Architecture
Ambipolar Synaptic Devices
Matrix Multiplication
Low Precision Computing
Semiconductor Devices
High Density Memory
75 patents (USPTO):Explore Patents
1. 12443841 - Four-bit training for machine learning (2025-10-14),
2. 12399743 - Padding input data for artificial intelligence accelerators (2025-08-26),
3. 12236338 - Single function to perform combined matrix multiplication and bias add operations (2025-02-25),
4. 12217158 - Neural network circuitry having floating point format with asymmetric range (2025-02-04),
5. 12175359 - Machine learning hardware having reduced precision parameter components for efficient parameter update (2024-12-24),
6. 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),
7. 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),
8. 11941111 - Exploiting fine-grained structured weight sparsity in systolic arrays (2024-03-26),
9. 11775257 - Enhanced low precision binary floating-point formatting (2023-10-03),
10. 11669489 - Sparse systolic array design (2023-06-06),
11. 11620105 - Hybrid floating point representation for deep learning acceleration (2023-04-04),
12. 11604647 - Mixed precision capable hardware for tuning a machine learning model (2023-03-14),
13. 11551077 - Statistics-aware weight quantization (2023-01-10),
14. 11551054 - System-aware selective quantization for performance optimized distributed deep learning (2023-01-10),
15. 11455142 - Ultra-low precision floating-point fused multiply-accumulate unit (2022-09-27),

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.

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