Lausanne, Switzerland

Henry Markram

This inventor holds 31 USPTO granted patents and 21 published patent applications, plus 2 CIPO patents and 6 EPO patents, primarily in Neural Networks. Top assignees: Inait Sa, Ecole Polytechnique Federale De Lausanne, Societe Des Produits Nestle S.a.. Active years: 2012-2025.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Henry Markram. Retrieved from https://idiyas.com/inventor/henry-markram

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 = 100.0


 

Average Co-Inventor Count = 3.1

ph-index = 9

Forward Citations = 152(Granted Patents)


Location History:

  • Lausann, CH (2019)
  • Pully, CH (2023)
  • Lausanne, CH (2012 - 2024)

Company Filing History:


Years Active: 2012-2025

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Areas of Expertise:
Homomorphic Encryption
Neural Networks
Recurrent Neural Networks
Clustering
Neocortical Microcircuitry
Encoding
Decoding
Functional Subnetworks
Autism Disorders
Neuronal Damage
Distance Metrics
Spiking Neural Networks
31 patents (USPTO):Explore Patents

Title: Henry Markram: Innovator in Neural Networks

Introduction

Henry Markram, a renowned inventor located in Lausanne, Switzerland, has made significant contributions to the field of neural networks, holding a remarkable total of 28 patents. His groundbreaking work focuses on the intricate functionalities of artificial neural networks and their application in sensory data abstraction and clustering.

Latest Patents

Among his latest patents, Markram has developed innovative methods for input into a neural network, which involves abstracting data from various sensors and transducers. His first patent details a process that identifies topological patterns of activity within a recurrent artificial neural network. This method enables the network to output a collection of digits representing whether specific topological patterns of activity have been recognized in relation to data from multiple sensors.

Another notable patent focuses on distance metrics and clustering in recurrent neural networks. This innovative approach assesses whether specific topological patterns of activity emerge in response to input data and calculates the distance between this data and other references. This work is crucial for enhancing the performance and accuracy of artificial intelligent systems.

Career Highlights

Henry Markram has had an impactful career highlighted by his association with prestigious organizations. He has worked with Inait SA and the École Polytechnique Fédérale de Lausanne (EPFL), institutions known for their cutting-edge research and contributions to the field of technology and science.

Collaborations

Throughout his career, Markram has collaborated with esteemed colleagues, including Kathryn Pamela Hess Bellwald and John Rahmon. These partnerships have further advanced innovative research in neural networks and deep learning, and have inspired a new generation of inventors and researchers in the field.

Conclusion

Henry Markram's inventions and patents demonstrate a deep understanding of neural networks and their potential applications. His work continues to pave the way for future innovations in artificial intelligence and machine learning, solidifying his reputation as a key figure in technological advancement.

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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