Patents by Inventor Charles Yeomans

Charles Yeomans has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20250105858
    Abstract: A system and method for data compression with encryption, that produces a conditioned data stream by replacing data blocks within an input data stream to bring the frequency of each data block closer to an ideal value, produces an error stream comprising the differences between the original data and the encrypted data, and compresses the conditioned data.
    Type: Application
    Filed: December 11, 2024
    Publication date: March 27, 2025
    Inventors: Joshua Cooper, Aliasghar Riahi, Mojgan Haddad, Ryan Kourosh Riahi, Razmin Riahi, Charles Yeomans, Grant Fickes
  • Publication number: 20250105857
    Abstract: A system and method for multi-layer data processing with selective encryption and transformation. The system generates a multi-layer data structure comprising reference elements derived from input data separated into multiple layers. Data processors receive and process input data using this structure, correlating input elements with reference elements. The system selectively encrypts one or more layers based on predefined encryption policies and applies transformation rules to processed data elements as specified in the structure. The output is a sequence of transformed, untransformed, and selectively encrypted elements. The system includes an encryption policy subsystem for managing layer-specific policies, a key management subsystem for handling encryption keys, and an enhanced decoder capable of processing both encrypted and non-encrypted data streams.
    Type: Application
    Filed: December 9, 2024
    Publication date: March 27, 2025
    Inventors: Joshua Cooper, Charles Yeomans
  • Patent number: 12260086
    Abstract: Codebook data compaction using a universal codebook and mismatch probability estimations to improve entropy encoding methods. Training data sets are analyzed to determine the frequency of occurrence of each sourceblock in the training data sets. A mismatch probability estimate is calculated comprising an estimated frequency at which any given data sourceblock received during encoding will not have a codeword in the codebook. Entropy encoding is used to generate codebooks comprising codewords for data sourceblocks based on the frequency of occurrence of each sourceblock. A “mismatch codeword” is inserted into the codebook based on the mismatch probability estimate to represent those cases when a block of data to be encoded does not have a codeword in the codebook.
    Type: Grant
    Filed: November 1, 2023
    Date of Patent: March 25, 2025
    Assignee: ATOMBEAM TECHNOLOGIES INC
    Inventors: Joshua Cooper, Aliasghar Riahi, Charles Yeomans
  • Patent number: 12261632
    Abstract: A system and method for efficient data storage, transfer, synchronization, and security using automated model monitoring and training. The system analyzes test datasets to detect data drift, retraining encoding and decoding algorithms as needed. New data sourceblocks are created and assigned codewords, compiling an updated codebook for distribution to connected devices. A novel dyadic distribution subsystem simultaneously compresses and encrypts data by transforming input streams into a dyadic distribution. This process generates a compressed main data stream and a secondary stream of transformation information, which are combined into a secure output. The system includes a network device manager for optimizing codebook distribution based on device resource usage. Operating in both lossless and lossy modes, the system offers flexible, efficient, and secure data handling across various network configurations.
    Type: Grant
    Filed: November 7, 2024
    Date of Patent: March 25, 2025
    Assignee: ATOMBEAM TECHNOLOGIES INC
    Inventors: Joshua Cooper, Grant Fickes, Charles Yeomans
  • Publication number: 20250096815
    Abstract: A system and methods for multi-type data compression or decompression with a virtual management layer in a distributed computing environment, comprising. It incorporates a virtual management layer to organize incoming data types and allocate compression or decompression tasks across multiple computing devices, selecting techniques best suited for particular data types. Associated data sets may be flagged prior to processing, ensuring preservation of relationships even when compressed or decompressed on different devices. This distributed approach allows efficient parallel processing of multiple data types, improving scalability and performance. A load balancing module optimizes task distribution based on available resources and processing requirements. The system enables each data type to be processed using the most efficient technique while maintaining associations between related data sets, effectively handling larger volumes of diverse data.
    Type: Application
    Filed: December 6, 2024
    Publication date: March 20, 2025
    Inventors: Joshua Cooper, Charles Yeomans, Zhu Li, Brian Galvin
  • Patent number: 12237848
    Abstract: A system and method for encrypted data compression, which uses frequency analysis on data blocks within an input data stream to produce a prefix table, representing a first layer of transformation, and which applies a Burrow's-Wheeler transform (BWT) to the data inside the prefix table, representing a second layer of transformation, and which compresses the transformed data. In some implementations, the system and method may further include applying the BWT to a conditioned stream of genomic data, wherein the conditioned stream of data is accompanied by an error stream comprising the differences between the original data and the encrypted data.
    Type: Grant
    Filed: November 6, 2023
    Date of Patent: February 25, 2025
    Assignee: ATOMBEAM TECHNOLOGIES INC
    Inventors: Joshua Cooper, Aliasghar Riahi, Mojgan Haddad, Ryan Kourosh Riahi, Razmin Riahi, Charles Yeomans
  • Publication number: 20250062777
    Abstract: A system and method for efficient data storage, transfer, synchronization, and security using automated model monitoring and training. The system analyzes test datasets to detect data drift, retraining encoding and decoding algorithms as needed. New data sourceblocks are created and assigned codewords, compiling an updated codebook for distribution to connected devices. A novel dyadic distribution subsystem simultaneously compresses and encrypts data by transforming input streams into a dyadic distribution. This process generates a compressed main data stream and a secondary stream of transformation information, which are combined into a secure output. The system includes a network device manager for optimizing codebook distribution based on device resource usage. Operating in both lossless and lossy modes, the system offers flexible, efficient, and secure data handling across various network configurations.
    Type: Application
    Filed: November 7, 2024
    Publication date: February 20, 2025
    Inventors: Joshua Cooper, Grant Fickes, Charles Yeomans
  • Publication number: 20250055475
    Abstract: A system and methods for multi-type data compression or decompression with a virtual management layer, comprising. It incorporates a virtual management layer to organize incoming data types and select a compression or decompression system that utilizes a technique best suited for a particular data type. Associated data sets may be flagged prior to compression or decompression so that associated types may be preserved together after the compression or decompression process is complete. This approach allows each data type to be compressed or decompressed using a technique that is the most efficient for a particular data type. Additionally, the approach allows all information associated with a particular data set to be compressed or decompressed in some way.
    Type: Application
    Filed: August 20, 2024
    Publication date: February 13, 2025
    Inventors: Joshua Cooper, Charles Yeomans, Zhu Li, Brian Galvin
  • Publication number: 20250055477
    Abstract: A system and method for lossy precompression for data compaction using automated model monitoring and training, wherein statistical analyses of test datasets are used to determine if the probability distribution of two datasets are within a pre-determined range, and responsive to that determination new encoding and decoding algorithms may be retrained in order to produce new data sourceblocks, and pre-compression of data prior to processing and statistical analysis allows for the compaction of already compressed data into highly dense formats. The new data sourceblocks may then be processed and assigned new codewords which are compiled into an updated codebook which may be distributed back to encoding and decoding systems and devices.
    Type: Application
    Filed: October 29, 2024
    Publication date: February 13, 2025
    Inventors: Joshua Cooper, Charles Yeomans
  • Patent number: 12224776
    Abstract: A system and method for lossy precompression for data compaction using automated model monitoring and training, wherein statistical analyses of test datasets are used to determine if the probability distribution of two datasets are within a pre-determined range, and responsive to that determination new encoding and decoding algorithms may be retrained in order to produce new data sourceblocks, and pre-compression of data prior to processing and statistical analysis allows for the compaction of already compressed data into highly dense formats. The new data sourceblocks may then be processed and assigned new codewords which are compiled into an updated codebook which may be distributed back to encoding and decoding systems and devices.
    Type: Grant
    Filed: September 6, 2023
    Date of Patent: February 11, 2025
    Assignee: ATOMBEAM TECHNOLOGIES INC
    Inventors: Joshua Cooper, Charles Yeomans
  • Patent number: 12224775
    Abstract: A system and method for highly efficient encoding of data that includes extended functionality for asymmetric encoding/decoding and network policy enforcement. In the case of asymmetric encoding/decoding the original data is encoded by an encoder according to a codebook and sent to a decoder, but the output of the decoder depends on data manipulation rules applied at the decoding stage to transform the decoded data into a different data set from the original data. In the case of network policy enforcement, a behavior appendix into the codebook, such that the encoder and/or decoder at each node of the network comply with network behavioral rules, limits, and policies during encoding and decoding.
    Type: Grant
    Filed: February 22, 2023
    Date of Patent: February 11, 2025
    Assignee: ATOMBEAM TECHNOLOGIES INC
    Inventors: Joshua Cooper, Aliasghar Riahi, Mojgan Haddad, Ryan Kourosh Riahi, Razmin Riahi, Charles Yeomans
  • Publication number: 20250047294
    Abstract: A system and method for enhancing lossy compressed data. The system receives a compressed data stream, decompresses it, and enhances the decompressed data using adaptive neural network models. Key features include data characteristic analysis, dynamic model selection from multiple specialized neural networks, and quality estimation with feedback-driven optimization. The system adapts to various data types and compression levels, recovering lost information without detailed knowledge of the compression process. It implements online learning for continuous improvement and includes security measures to ensure data integrity. The method is applicable to diverse data types, including financial time-series, images, and audio.
    Type: Application
    Filed: September 25, 2024
    Publication date: February 6, 2025
    Inventors: Joshua COOPER, Grant FICKES, Charles YEOMANS, Brian GALVIN
  • Publication number: 20250047300
    Abstract: A system and method for highly efficient encoding of data that includes extended functionality for asymmetric encoding/decoding and network policy enforcement. In the case of asymmetric encoding/decoding the original data is encoded by an encoder according to a codebook and sent to a decoder, but the output of the decoder depends on data manipulation rules applied at the decoding stage to transform the decoded data into a different data set from the original data. In the case of network policy enforcement, a behavior appendix into the codebook, such that the encoder and/or decoder at each node of the network comply with network behavioral rules, limits, and policies during encoding and decoding.
    Type: Application
    Filed: October 25, 2024
    Publication date: February 6, 2025
    Inventors: Joshua Cooper, Aliasghar Riahi, Mojgan Haddad, Ryan Kourosh Riahi, Razmin Riahi, Charles Yeomans
  • Publication number: 20250047297
    Abstract: Data storage, transfer, synchronization, and security using automated system efficacy monitoring and model training is disclosed. Statistical analyses of test datasets are used to determine if the probability distribution of two datasets are within a pre-determined range, and responsive to that determination new encoding and decoding algorithms may be retrained in order to produce new data sourceblocks. The new data sourceblocks may then be processed and assigned new codewords which are compiled into an updated codebook which may be distributed back to encoding and decoding systems and devices.
    Type: Application
    Filed: October 18, 2024
    Publication date: February 6, 2025
    Inventors: Joshua Cooper, Aliasghar Riahi, Mojgan Haddad, Ryan Kourosh Riahi, Razmin Riahi, Charles Yeomans
  • Publication number: 20250044939
    Abstract: Compression of medical imaging data using codebooks and entropy encoding. Medical imaging data such as tomosynthesis imagery data may be compressed using codewords based on frequency analysis. In an implementation sequential registration technique may be applied to the medical imaging data to create a plurality transformation matrices. The plurality of transformation matrices may be compressed using a matrix codebook. The compressed medical imaging data may be represented as an image codebook and the matrix codebook, providing secure storage and lossless compression of sensitive medical information.
    Type: Application
    Filed: August 12, 2024
    Publication date: February 6, 2025
    Inventors: Joshua Cooper, Charles Yeomans
  • Publication number: 20250047298
    Abstract: A system and method for intrusion detection with prediction and validation subsystems powered by machine learning. The system analyzes real-time codeword streams and historical data to predict potential intrusions before they fully manifest. It employs various machine learning models to extract features, identify patterns, and validate detected anomalies. The system continuously learns from validated events and false positives, improving its accuracy over time. An integrated encryption module secures sensitive data using a dyadic distribution-based algorithm, combining compression and encryption. This approach significantly reduces false positives, enhances threat detection capabilities, and provides robust data protection for cybersecurity applications.
    Type: Application
    Filed: October 18, 2024
    Publication date: February 6, 2025
    Inventors: Joshua Cooper, Grant Fickes, Charles Yeomans
  • Publication number: 20250045251
    Abstract: A system and method for optimizing intrachip communication using machine learning-based codebook refinement is presented. The system employs an on-chip machine learning model to continuously analyze data patterns and update a codebook used for data compression in intrachip communication. Key aspects may comprise real-time data collection, feature extraction, performance monitoring, and gradual codebook updates. The system adapts to evolving data patterns, improving compression efficiency over time. A fallback mechanism ensures system stability by reverting to a conservative codebook if performance degrades. Security measures, including cryptographic signatures for updates and anomaly detection, are integrated. The system optimizes power consumption by adjusting operations based on the chip's power state. This adaptive approach significantly enhances intrachip communication efficiency, potentially improving overall chip performance and energy efficiency.
    Type: Application
    Filed: October 18, 2024
    Publication date: February 6, 2025
    Inventors: Joshua Cooper, Charles Yeomans, Gregory Caltabiano
  • Patent number: 12218697
    Abstract: A system and method for event-driven data communication using codebooks with protocol prediction and translation. This invention presents an advanced adaptive communication system that dynamically optimizes network protocols using machine learning-driven prediction and translation modules. The system analyzes real-time traffic patterns and historical data to anticipate communication needs, proactively switching to optimal protocols when beneficial. A sophisticated translation module, powered by large language models, enables seamless communication between systems using different protocols, including legacy systems. This approach enhances network efficiency, ensures backward compatibility, and future-proofs communication infrastructures, making it particularly valuable in complex, heterogeneous network environments.
    Type: Grant
    Filed: September 7, 2024
    Date of Patent: February 4, 2025
    Assignee: ATOMBEAM TECHNOLOGIES INC
    Inventors: Joshua Cooper, Charles Yeomans
  • Patent number: 12218695
    Abstract: A system and method for data storage, transfer, synchronization, and security using automated system efficacy monitoring and model training, wherein statistical analyses of test datasets are used to determine if the probability distribution of two datasets are within a pre-determined range, and responsive to that determination new encoding and decoding algorithms may be retrained in order to produce new data chunklets. The new data chunklets may then be processed and assigned new codewords which are compiled into an updated codebook which may be distributed back to encoding and decoding systems and devices.
    Type: Grant
    Filed: January 29, 2023
    Date of Patent: February 4, 2025
    Assignee: ATOMBEAM TECHNOLOGIES INC.
    Inventors: Joshua Cooper, Aliasghar Riahi, Mojgan Haddad, Ryan Kourosh Riahi, Razmin Riahi, Charles Yeomans
  • Patent number: 12216623
    Abstract: A system and method for random-access manipulation of compacted data files, utilizing a reference codebook, a random-access engine, a data deconstruction engine, and a data deconstruction engine. The system may receive a data query pertaining to a data read or data write request, wherein the data file to be read from or written to is a compacted data file. A random-access engine may facilitate data manipulation processes by transforming the codebook into a hierarchical representation and then traversing the representation scanning for specific codewords associated with a data query request. In an embodiment, an estimator module is present and configured to utilize cardinality estimation to determine a starting codeword to begin searching the compacted data file for the data associated with the data query. The random-access engine may encode the data to be written, insert the encoded data into a compacted data file, and update the codebook as needed.
    Type: Grant
    Filed: September 1, 2024
    Date of Patent: February 4, 2025
    Assignee: ATOMBEAM TECHNOLOGIES INC
    Inventors: Joshua Cooper, Charles Yeomans, Brian Galvin