Patents by Inventor Rakesh Rameshrao Pimplikar
Rakesh Rameshrao Pimplikar 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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Publication number: 20240070350Abstract: An example operation may include one or more of identifying an external system that passes an input attribute to a process based on a workflow representation of the process, building a simulator of the external system based on attributes of the external system identified from the workflow representation, simulating future values of the input attribute to be passed to the process by the external system based on the simulator of the external system and a previous simulation run of the process performed via a workflow software application, and executing a new simulation of the process via the workflow software application based on the simulated future values of the input attribute.Type: ApplicationFiled: August 23, 2022Publication date: February 29, 2024Inventors: Rakesh Rameshrao Pimplikar, Ritwik Chaudhuri, Pranay Kumar Lohia, Ramasuri Narayanam, Sameep Mehta, Gyana Ranjan Parija
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Publication number: 20240070519Abstract: A method, computer program, and computer system are provided for online fairness monitoring. A dataset having one or more entries with one or more protected attributes and data corresponding to a trained machine learning model is received. An entry having a maximum reward is selected based on a reward probability associated with the entry. A determination is made as to whether bias has developed in the trained machine learning model toward one or more of the one or more protected attributes based on a change to the reward probability or a distribution of reward probabilities exceeding a threshold value.Type: ApplicationFiled: August 26, 2022Publication date: February 29, 2024Inventors: Manish Kesarwani, Pranay Kumar Lohia, Ramasuri Narayanam, Rakesh Rameshrao Pimplikar, Sameep Mehta
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Patent number: 11836793Abstract: One embodiment provides a computer implemented method, including: receiving information corresponding to a customer of a seller, wherein the information is related to credit information of the customer; generating a credit attribute for the customer with respect to the seller, wherein the generating includes utilizing a plurality of artificial intelligence agents that each analyze at least a subset of the information to each generate an agent version of the credit attribute; and recommending a deferral of at least a portion of a pending invoice of the seller for the customer, wherein a value of the deferral is based upon the credit attribute.Type: GrantFiled: December 11, 2020Date of Patent: December 5, 2023Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Shrihari Vasudevan, Sudhanshu Shekhar Singh, Rakesh Rameshrao Pimplikar, Gyana Ranjan Parija, Jasmina Mohorn, Didier Denove, Magesh A Narayanan, Khalid Siddiqui
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Publication number: 20230186197Abstract: In an approach for effective performance assessment, a processor classifies relevancy of a goal submitted by an employee. A processor classifies the goal into one of pre-defined dimensions. A processor receives feedback about the goal from a manager. A processor classifies whether the feedback is actionable with respect to the corresponding goal. A processor classifies consistency of the feedback with the corresponding dimension of the goal. A processor classifies consistency of the feedback with the corresponding position level of the employee. A processor converts the feedback along the corresponding dimension into a rating for the dimension on a pre-defined scale.Type: ApplicationFiled: December 14, 2021Publication date: June 15, 2023Inventors: Rakesh Rameshrao Pimplikar, Sameep Mehta, Nazia Hasan, Varun Gupta, Kingshuk Banerjee
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Publication number: 20230177383Abstract: Methods, systems, and computer program products for adjusting machine learning models based on simulated fairness impact are provided herein. A computer-implemented method includes obtaining, by a central simulation system, policies to be used for performing a simulation involving machine learning models, implemented on different systems, interacting with a target population; providing information for configuring simulators on the different systems, each simulator representing at least the machine learning model of a given one of the different systems; performing iterations of the simulation for the policies, wherein, for each iteration, the central simulation system: predicts a state of the target population, provides the state to the simulators, and collects metrics based on results of the simulators; and selecting and sending one of the policies to at least one of the different systems based on the collected metrics.Type: ApplicationFiled: December 7, 2021Publication date: June 8, 2023Inventors: Pranay Kumar Lohia, Kushal Mukherjee, Rakesh Rameshrao Pimplikar, Monika Gupta, Sameep Mehta, Stacy F. Hobson
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Publication number: 20230177355Abstract: Methods, systems, and computer program products for automated fairness-driven graph node label classification are provided herein. A computer-implemented method includes obtaining at least one input graph; predicting one or more node labels associated with the at least one input graph by processing at least a portion of the at least one input graph using a graph node label prediction model, wherein the graph node label prediction model includes at least one loss function; generating an updated version of the graph node label prediction model based at least in part on the one or more predicted node labels and one or more group fairness-based constraints relevant to the at least one input graph; and performing one or more automated actions using the updated version of the graph node label prediction model.Type: ApplicationFiled: December 6, 2021Publication date: June 8, 2023Inventors: Ramasuri Narayanam, Sameep Mehta, Rakesh Rameshrao Pimplikar, Pranay Kumar Lohia
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Publication number: 20230113171Abstract: A system, method, and computer program product for implementing automated digital agent communication and control is provided. The method includes retrieving from a digital agent, a query associated with knowledge based control process. Digital knowledge elements, associated digital skills, and a sequence of control operations are received to obtain a response to the query. A first possible set of knowledge of a set of digital knowledge elements, skills, and an associated sequence of operation are selected and the first possible set of knowledge, skills, and associated sequence of operation are transmitted to the digital agent. A sequence of skills are executed with respect to digital knowledge elements and components and a hardware interface device is enabled to interact with and control various devices for enabling operational functionality associated with devices. Knowledge based fabric code associated with future instances of enabling the hardware interface device is updated.Type: ApplicationFiled: October 8, 2021Publication date: April 13, 2023Inventors: Kushal Mukherjee, Rakesh Rameshrao Pimplikar, Ramasuri Narayanam, Gyana Ranjan Parija, Nidhish M. Pathak, Nidhi Sagar, Anish Jain
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Publication number: 20220188920Abstract: One embodiment provides a computer implemented method, including: receiving information corresponding to a customer of a seller, wherein the information is related to credit information of the customer; generating a credit attribute for the customer with respect to the seller, wherein the generating includes utilizing a plurality of artificial intelligence agents that each analyze at least a subset of the information to each generate an agent version of the credit attribute; and recommending a deferral of at least a portion of a pending invoice of the seller for the customer, wherein a value of the deferral is based upon the credit attribute.Type: ApplicationFiled: December 11, 2020Publication date: June 16, 2022Inventors: Shrihari Vasudevan, Sudhanshu Shekhar Singh, Rakesh Rameshrao Pimplikar, Gyana Ranjan Parija, Jasmina Mohorn, Didier Denove, Magesh A. Narayanan, Khalid Siddiqui
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Patent number: 11288720Abstract: One embodiment provides a computer implemented method, including: receiving billing information related to a billing contract of a customer of a seller, wherein the billing contract identifies amounts of invoices and an invoice frequency; identifying, utilizing one or more artificial intelligence agents, one or more risk factors associated with generation of a pending invoice based upon the billing information; and recommending, utilizing the one or more artificial intelligence agents, a generation date for the pending invoice based upon the one or more risk factors, wherein the recommending includes selecting a generation date to facilitate timely payment of the pending invoice by the customer.Type: GrantFiled: December 11, 2020Date of Patent: March 29, 2022Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Shrihari Vasudevan, Sudhanshu Shekhar Singh, Rakesh Rameshrao Pimplikar, Shweta Garg, Gyana Ranjan Parija, Jasmina Mohorn, Magesh A Narayanan, Didier Denove, Khalid Siddiqui
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Patent number: 10909844Abstract: A computer-implemented dynamic road stretch dividing method, the method comprising: determining a current lane distribution of partitions of a road stretch; calculating a new lane distribution of the road stretch to ameliorate traffic based on a pragmatic factor; changing an alignment of the partitions of the current lane distribution to obtain the new lane distribution; and updating the pragmatic factor based on at least one of an external policy and a constraint input by a user.Type: GrantFiled: August 22, 2019Date of Patent: February 2, 2021Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Kuntal Dey, Rakesh Rameshrao Pimplikar, Sudhanshu Shekhar Singh, Biplav Srivastava
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Patent number: 10607481Abstract: A dynamic road stretch dividing method, system, and computer program product, include determining a current lane distribution of partitions of a road stretch, calculating a new lane distribution of the road stretch to ameliorate traffic based on a pragmatic factor, and changing an alignment of the partitions of the current lane distribution to obtain the new lane distribution.Type: GrantFiled: February 27, 2017Date of Patent: March 31, 2020Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Kuntal Dey, Rakesh Rameshrao Pimplikar, Sudhanshu Shekhar Singh, Biplav Srivastava
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Publication number: 20190378408Abstract: A computer-implemented dynamic road stretch dividing method, the method comprising: determining a current lane distribution of partitions of a road stretch; calculating a new lane distribution of the road stretch to ameliorate traffic based on a pragmatic factor; changing an alignment of the partitions of the current lane distribution to obtain the new lane distribution; and updating the pragmatic factor based on at least one of an external policy and a constraint input by a user.Type: ApplicationFiled: August 22, 2019Publication date: December 12, 2019Inventors: Kuntal Dey, Rakesh Rameshrao Pimplikar, Sudhanshu Shekhar Singh, Biplav Srivastava
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Publication number: 20180247528Abstract: A dynamic road stretch dividing method, system, and computer program product, include determining a current lane distribution of partitions of a road stretch, calculating a new lane distribution of the road stretch to ameliorate traffic based on a pragmatic factor, and changing an alignment of the partitions of the current lane distribution to obtain the new lane distribution.Type: ApplicationFiled: February 27, 2017Publication date: August 30, 2018Inventors: Kuntal Dey, Rakesh Rameshrao Pimplikar, Sudhanshu Shekhar Singh, Biplav Srivastava