Patents by Inventor Saikat Mukherjee
Saikat Mukherjee 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).
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Patent number: 12088476Abstract: The disclosure relates to a framework for dynamic management of analytic functions such as data processors and machine learned (“ML”) models for an Internet of Things intelligent edge that addresses management of the lifecycle of the analytic functions from creation to execution, in production. The end user will be seamlessly able to check in an analytic function, version it, deploy it, evaluate model performance and deploy refined versions into the data flows at the edge or core dynamically for existing and new end points. The framework comprises a hypergraph-based model as a foundation, and may use a microservices architecture with the ML infrastructure and models deployed as containerized microservices.Type: GrantFiled: September 21, 2022Date of Patent: September 10, 2024Assignee: Hewlett Packard Enterprise Development LPInventors: Satish Kumar Mopur, Saikat Mukherjee, Gunalan Perumal Vijayan, Sridhar Balachandriah, Ashutosh Agrawal, KrishnaPrasad Lingadahalli Shastry, Gregory S. Battas
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Publication number: 20240278799Abstract: An autonomous vehicle data searching and auditing system, is provided. The AVDSAS includes a scenario database storing therein autonomous vehicle data associated with AV(s). The AVDSAS has a scenario extraction module that is in operable communication with the scenario database. The scenario extraction module extracts scenario data from the AV data and stores the scenario data into the scenario database, wherein the scenario data includes AV parameter(s), object(s), and operational design domain element(s) associated with the AV(s). The AV data stored in the scenario database is searchable based on a query. The scenario extraction model generates scenario(s) using the scenario data from the scenario database based on the query.Type: ApplicationFiled: June 24, 2021Publication date: August 22, 2024Inventors: Saadhana B Venkataraman, Vijaya Sarathi Indla, Bony Mathew, Saikat Mukherjee, Ram Padhy, Sagar Pathrudkar, Bristi Singh
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Publication number: 20240256525Abstract: Systems and methods are disclosed for providing decentralized policy-based transactional object management for systems employing federated workflows. Various disclosed components may be added to one or more nodes of a decentralized network, wherein the disclosed components perform registration, replication, and read/write access interfacing functions. These functions result in the storage of objects on the decentralized network in a way which allows for decentralized, policy-based, and transactional management of the objects.Type: ApplicationFiled: January 27, 2023Publication date: August 1, 2024Inventors: SATHYANARAYANAN MANAMOHAN, KRISHNAPRASAD LINGADAHALLI SHASTRY, RAVI SARVESWARA, SAIKAT MUKHERJEE
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Patent number: 12019978Abstract: Systems and methods for lean parsing are disclosed. An example method is performed by one or more processors of a system and includes retrieving form data including first sentence segments and second sentence segments, determining a first predicate structure for each of the sentence segments based on a set of operators within the first set of sentence segments, identifying known tokens within the second set of sentence segments, each of the known tokens appearing on a list of predetermined tokens, identifying new tokens within the second set of sentence segments, each of the new tokens not on the list, mapping each known and new token to at least one operator, determining a second predicate structure for each sentence segment based on the mapping, and generating a predicate argument structure incorporating the first and second predicate structures, the predicate argument structure ready for mapping to at least one machine executable function.Type: GrantFiled: October 28, 2022Date of Patent: June 25, 2024Assignee: Intuit Inc.Inventors: Saikat Mukherjee, Esmé Manandise, Sudhir Agarwal, Karpaga Ganesh Patchirajan
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Patent number: 11876891Abstract: Systems and methods are provided for implementing swarm learning while using blockchain technology and election/voting mechanisms to ensure data privacy. Nodes may train local instances of a machine learning model using local data, from which parameters are derived or extracted. Those parameters may be encrypted and persisted until a merge leader is elected that can merge the parameters using a public key generated by an external key manager. A decryptor that is not the merge leader can be elected to decrypt the merged parameter using a corresponding private key, and the decrypted merged parameter can then be shared amongst the nodes, and applied to their local models. This process can be repeated until a desired level of learning has been achieved. The public and private keys are never revealed to the same node, and may be permanently discarded after use to further ensure privacy.Type: GrantFiled: November 23, 2021Date of Patent: January 16, 2024Assignee: Hewlett Packard Enterprise Development LPInventors: Sathyanarayanan Manamohan, Vishesh Garg, Krishnaprasad Lingadahalli Shastry, Saikat Mukherjee
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Publication number: 20240013592Abstract: A scenario identification system and a computer implemented method for identifying one or more critical scenarios from vehicle data associated with one or more vehicles are provided. The scenario identification system obtains at least the inertial measurement unit (IMU) data from the vehicle data, derives one or more IMU-based driving parameters from the IMU data, and analyzes the IMU-based driving parameters based on one or more predefined thresholds for identifying the critical scenario(s).Type: ApplicationFiled: August 28, 2020Publication date: January 11, 2024Inventors: Saadhana B Venkataraman, Vijaya Sarathi Indla, Bony Mathew, Saikat Mukherjee, Ram Padhy, Sagar Pathrudkar, Bristi Singh
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Publication number: 20230245023Abstract: Certain aspects of the present disclosure provide techniques for managing the lifecycle of user data. A user data lifecycle management system can collect user data from multiple sources including the user, the organization implementing the lifecycle management system, and third parties. The user data is used to create a user profile with a global user identifier. The user profile is scored based on the attributes within the user profile. The user data lifecycle management system can route the user profile to a destination source based on the score of the user profile. The destination source can be a tool of the organization for interacting with the user. The destination sources can also provide feedback to that is incorporated to the user profile and can assist the user data lifecycle management system in managing the user profile and aid in decision making.Type: ApplicationFiled: January 31, 2022Publication date: August 3, 2023Inventors: Sangeetha Uthamalingam SANTHARAM, Saikat MUKHERJEE, Narender VATTIKONDA, Sameer KUMAR, Vijay Sriharsha GUDIMELLA, Steven SETZER
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Patent number: 11687721Abstract: Systems and methods for recognizing domain specific named entities are disclosed. An example method may be performed by one or more processors of a text incorporation system and include extracting a number of terms from a text under consideration, identifying, among the number of terms, a set of unmatched terms that do not match any of a plurality of known terms, passing each respective unmatched term to a vectorization module, embedding a vectorized version of each respective unmatched term in a vector space, comparing each vectorized version to known term vectors, passing, to a machine learning model, candidate terms corresponding to known term vectors closest to the vectorized versions, identifying, using the machine learning model, a best candidate term for each respective unmatched term, mapping the best candidate terms to unmatched terms in the text under consideration, and incorporating the text under consideration into the system based on the mappings.Type: GrantFiled: July 20, 2021Date of Patent: June 27, 2023Assignee: Intuit Inc.Inventors: Conrad De Peuter, Karpaga Ganesh Patchirajan, Saikat Mukherjee
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Patent number: 11663677Abstract: A method and system to learn new forms to be incorporated into an electronic document preparation system, or to learn the behavior of existing systems, receive form data related to a new form having a plurality of data fields that expect data values based on specific functions. The method and system gather training set data including previously filled forms having completed data fields corresponding to the data fields of the new form. The method and system include multiple analysis modules that each generate candidate functions for providing data values for the data fields of the new form. The method and system evaluate the candidate functions from each analysis technique and select the candidate functions that are most accurate based on comparisons with the training set data.Type: GrantFiled: May 26, 2021Date of Patent: May 30, 2023Assignee: Intuit Inc.Inventors: Saikat Mukherjee, Cem Unsal, William T. Laaser, Mritunjay Kumar, Anu Sreepathy, Per-Kristian Halvorsen
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Patent number: 11663495Abstract: A method and system learn functions to be associated with data fields of forms to be incorporated into an electronic document preparation system. The functions are essentially sets of operations required to calculate the data field. The method and system receive form data related to a data field that expects data values resulting from performing specific operations. The method and system utilize machine learning and training set data to generate, test, and evaluate candidate functions to determine acceptable functions.Type: GrantFiled: December 6, 2021Date of Patent: May 30, 2023Assignee: Intuit Inc.Inventors: Cem Unsal, Saikat Mukherjee, Roger Charles Meike
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Publication number: 20230065070Abstract: Systems and methods for lean parsing are disclosed. An example method is performed by one or more processors of a system and includes retrieving form data including first sentence segments and second sentence segments, determining a first predicate structure for each of the sentence segments based on a set of operators within the first set of sentence segments, identifying known tokens within the second set of sentence segments, each of the known tokens appearing on a list of predetermined tokens, identifying new tokens within the second set of sentence segments, each of the new tokens not on the list, mapping each known and new token to at least one operator, determining a second predicate structure for each sentence segment based on the mapping, and generating a predicate argument structure incorporating the first and second predicate structures, the predicate argument structure ready for mapping to at least one machine executable function.Type: ApplicationFiled: October 28, 2022Publication date: March 2, 2023Applicant: Intuit Inc.Inventors: Saikat Mukherjee, Esmé Manandise, Sudhir Agarwal, Karpaga Ganesh Patchirajan
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Publication number: 20230043430Abstract: A method including generating, by a state engine from data describing behaviors of users in an environment external to the state engine, an executable process. An agent executes the executable process by determining, from the data describing the behaviors of the users, a problem of at least some of the users, and selects, based on the problem, a chosen action to alter the problem. At a first time, a first electronic communication describing the chosen action to the at least some of the users is transmitted. Ongoing data describing ongoing behaviors of the users is monitored. A reward is generated based on the ongoing data to change a parameter of the agent. The parameter of the agent is changed to generate a modified agent. The modified agent executes the executable process to select a modified action. At a second time, a second electronic communication describing the modified action is transmitted.Type: ApplicationFiled: August 9, 2021Publication date: February 9, 2023Applicant: Intuit Inc.Inventors: Daniel Ben David, Saikat Mukherjee, Nirmala Ranganathan, Yair Horesh
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Publication number: 20230033737Abstract: A computer-implemented system and method for predicting rule-based compliance scenarios to implement rule-based topic determinations. A server computing device generates a compliance scenario prediction model by training a machine learning model for a topic with historical user data and cohort labels created by analyzing the scenarios in a completeness graph to predict a set of scenario cohorts that constitute a set of most probable compliance scenarios. The server computing device executes the scenario prediction model to process a user profile including data features associated with the topic to predict a scenario cohort and a compliance scenario corresponding to the predicted cohort for the user. The server computing device automatically infers one or more personalized responses to at least one question of the respective decision node based on the predicted compliance scenario.Type: ApplicationFiled: July 30, 2021Publication date: February 2, 2023Applicant: INTUIT INC.Inventors: Carol Ann HOWE, Saikat MUKHERJEE, Anu SREEPATHY, Cem UNSAL, Shashi ROSHAN
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Publication number: 20230017701Abstract: The disclosure relates to a framework for dynamic management of analytic functions such as data processors and machine learned (“ML”) models for an Internet of Things intelligent edge that addresses management of the lifecycle of the analytic functions from creation to execution, in production. The end user will be seamlessly able to check in an analytic function, version it, deploy it, evaluate model performance and deploy refined versions into the data flows at the edge or core dynamically for existing and new end points. The framework comprises a hypergraph-based model as a foundation, and may use a microservices architecture with the ML infrastructure and models deployed as containerized microservices.Type: ApplicationFiled: September 21, 2022Publication date: January 19, 2023Inventors: Satish Kumar Mopur, Saikat Mukherjee, Gunalan Perumal Vijayan, Sridhar Balachandriah, Ashutosh Agrawal, KrishnaPrasad Lingadahalli Shastry, Gregory S. Battas
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Patent number: 11544468Abstract: This disclosure describes converting computer-executable predicate-argument structures for a specific field to field-specific predicated-argument structures to improve execution. In some implementations, a method can be performed by one or more processors of a computing device, and can include receiving one or more predicate-argument structures (PASs) associated with taxation-specific text and converting the one or more PASs into one or more tax-specific predicate-argument structures (TPASs). Converting the one or more PASs to one or more TPASs may include one or more of: defining terms in a segment based on a definition of the term from a different segment or line description (including from a different document); reordering nodes, replacing nodes, or removing nodes of a segment (such as based on one or more single segment tree traversal rules); or combining multiple PASs for multiple segments of a single line description based on one or more multiple segment tree traversal rules.Type: GrantFiled: July 24, 2020Date of Patent: January 3, 2023Assignee: Intuit Inc.Inventors: Esmé Manandise, Karpaga Ganesh Patchirajan, Saikat Mukherjee
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Patent number: 11520975Abstract: A method and system parses natural language in a unique way, determining important words pertaining to a text corpus of a particular genre, such as tax preparation. Sentences extracted from instructions or forms pertaining to tax preparation, for example are parsed to determine word groups forming various parts of speech, and then are processed to exclude words on an exclusion list and word groups that don't meet predetermined criteria. From the resulting data, synonyms are replaced with a common functional operator and the resulting sentence text is analyzed against predetermined patterns to determine one or more functions to be used in a document preparation system.Type: GrantFiled: January 23, 2020Date of Patent: December 6, 2022Assignee: Intuit Inc.Inventors: Saikat Mukherjee, Esmé Manandise, Sudhir Agarwal, Karpaga Ganesh Patchirajan
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Patent number: 11521405Abstract: A method may include acquiring, from an initial document having a document type, initial document elements and initial attributes, deriving initial features for the initial document elements using the initial attributes, detecting initial form components using the initial features, clustering the initial form components into initial line objects of an initial structured representation by applying an unsupervised machine learning model to the geometric attributes of the initial document elements, acquiring, from a next document having the document type, next document elements and next attributes describing the next document elements, deriving next features for the next document elements using the next attributes, detecting next form components using the next features, determining that the initial form components and the next form components are different, clustering the next form components into next line objects of a next structured representation, and replacing the initial structured representation with theType: GrantFiled: April 29, 2021Date of Patent: December 6, 2022Assignee: Intuit Inc.Inventors: Anu Singh, Saikat Mukherjee, Mritunjay Kumar, Karpaga Ganesh Patchirajan
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Patent number: 11481665Abstract: A system and method for accounting for the impact of concept drift in selecting machine learning training methods to address the identified impact. Pattern recognition is performed on performance metrics of a deployed production model in an Internet-of-Things (IoT) environment to determine the impact that concept drift (data drift) has had on prediction performance. This concurrent analysis is utilized to select one or more approaches for training machine learning models, thereby accounting for the temporal dynamics of concept drift (and its subsequent impact on prediction performance) in a faster and more efficient manner.Type: GrantFiled: November 9, 2018Date of Patent: October 25, 2022Assignee: Hewlett Packard Enterprise Development LPInventors: Satish Kumar Mopur, Gregory S. Battas, Gunalan Perumal Vijayan, Krishnaprasad Lingadahalli Shastry, Saikat Mukherjee, Ashutosh Agrawal, Sridhar Balachandriah
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Patent number: 11469969Abstract: The disclosure relates to a framework for dynamic management of analytic functions such as data processors and machine learned (“ML”) models for an Internet of Things intelligent edge that addresses management of the lifecycle of the analytic functions from creation to execution, in production. The end user will be seamlessly able to check in an analytic function, version it, deploy it, evaluate model performance and deploy refined versions into the data flows at the edge or core dynamically for existing and new end points. The framework comprises a hypergraph-based model as a foundation, and may use a microservices architecture with the ML infrastructure and models deployed as containerized microservices.Type: GrantFiled: October 4, 2018Date of Patent: October 11, 2022Assignee: Hewlett Packard Enterprise Development LPInventors: Satish Kumar Mopur, Saikat Mukherjee, Gunalan Perumal Vijayan, Sridhar Balachandriah, Ashutosh Agrawal, Krishnaprasad Lingadahalli Shastry, Gregory S. Battas
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Publication number: 20220253930Abstract: Systems and methods for generating a credit profile based on user behavior traits are disclosed. A system may be configured to obtain a plurality of financial based interactions of a user, generate one or more behavior trait indicators based on the plurality of financial based interactions, and generate the credit profile of the user based on the one or more behavior trait indicators. A behavior trait indicator may include a self-control indicator regarding discretionary spending, an ostrich bias indicator regarding user interactions after negative news or events, or a procrastination indicator based on voluntary late payments to user accounts.Type: ApplicationFiled: February 10, 2021Publication date: August 11, 2022Applicant: Intuit Inc.Inventors: Daniel Ben David, Saikat Mukherjee, Nirmala Ranganathan, Kymm Kause, Yair Horesh