Patents by Inventor Raghu Kiran Ganti

Raghu Kiran Ganti 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).

  • Patent number: 12141697
    Abstract: Aspects of the present disclosure relate to annotating or tagging customer data. In some embodiments, the annotating can include summarizing touchpoints into k-hot encoding feature vectors, mapping the feature vectors onto an embedding layer, predicting a hierarchical data sequence using the embedding layer and the feature vectors, extracting the feature vectors that are most influential in predicting the embedding layer, and outputting the touchpoints associated with the most influential feature vectors.
    Type: Grant
    Filed: April 18, 2023
    Date of Patent: November 12, 2024
    Assignee: International Business Machines Corporation
    Inventors: Linsong Chu, Pranita Sharad Dewan, Raghu Kiran Ganti, Joshua M. Rosenkranz, Mudhakar Srivatsa
  • Patent number: 11954085
    Abstract: A computer implemented method performs data skipping in a hierarchically organized computing system. A group of processor units determines leaf node data sketches for data in leaf nodes in the hierarchically organized computing system. The leaf node data sketches summarize attributes of data in the leaf nodes. The group of processor units aggregates the leaf node data sketches at intermediate nodes in the hierarchically organized computing system to form aggregated data sketches at the intermediate nodes and retains data sketches received at the intermediate nodes from a group of child nodes to form retained data sketches. The retained data sketches are one of leaf node data sketches and the aggregated data sketches. The group of processor units searches the data using the retained data sketches and the data skipping within the hierarchically organized computing system in response to queries made to the intermediate nodes in the hierarchically organized computing system.
    Type: Grant
    Filed: September 22, 2022
    Date of Patent: April 9, 2024
    Assignee: International Business Machines Corporation
    Inventors: Mudhakar Srivatsa, Raghu Kiran Ganti, Joshua M. Rosenkranz, Linsong Chu, Tuan Minh Hoang Trong, Utpal Mangla, Satishkumar Sadagopan, Mathews Thomas
  • Publication number: 20240104075
    Abstract: A computer implemented method performs data skipping in a hierarchically organized computing system. A group of processor units determines leaf node data sketches for data in leaf nodes in the hierarchically organized computing system. The leaf node data sketches summarize attributes of data in the leaf nodes. The group of processor units aggregates the leaf node data sketches at intermediate nodes in the hierarchically organized computing system to form aggregated data sketches at the intermediate nodes and retains data sketches received at the intermediate nodes from a group of child nodes to form retained data sketches. The retained data sketches are one of leaf node data sketches and the aggregated data sketches. The group of processor units searches the data using the retained data sketches and the data skipping within the hierarchically organized computing system in response to queries made to the intermediate nodes in the hierarchically organized computing system.
    Type: Application
    Filed: September 22, 2022
    Publication date: March 28, 2024
    Inventors: MUDHAKAR SRIVATSA, RAGHU KIRAN GANTI, Joshua M. Rosenkranz, Linsong Chu, Tuan Minh HOANG TRONG, Utpal Mangla, SATISHKUMAR SADAGOPAN, Mathews Thomas
  • Patent number: 11941038
    Abstract: Systems, methods and/or computer program products for controlling and visualizing topic modeling results using a topic modeling interface. The interface allows user directed exploration, understanding and control of topic modeling algorithms, while offering both semantic summaries and/or structure attribute explanations about results. Explanations and differentiations between results are presented using metrics such as cohesiveness and visual displays depicting hierarchical organization. Through user-manipulation of features of the interface, iterative changes are implemented through user-feedback, adjusting parameters, broadening or narrowing topic results, and/or reorganizing topics by splitting or merging topics. As users trigger visual changes to results being displayed, users can compare and contrast output from the topic modeling algorithm.
    Type: Grant
    Filed: May 19, 2022
    Date of Patent: March 26, 2024
    Assignee: International Business Machines Corporation
    Inventors: Raghu Kiran Ganti, Mudhakar Srivatsa, Shreeranjani Srirangamsridharan, Jae-Wook Ahn, Michele Merler, Dean Steuer
  • Patent number: 11907766
    Abstract: A cloud-enterprise resource management system enables sharing of computing resources belonging to different datacenters by one or more clients of a resource pooling and sharing service. Each datacenter of includes a first partition of computing resources and a second partition of computing resources. The first partition is designated as reserved for use by an enterprise operating the datacenter. The second partition is designated as available for use by one or more clients of the resource pooling and sharing service. A workload manager in each datacenter predicts workload and transfers (i) a first computing resource from the first partition to the second partition wherein when the predicted workload is below a first threshold and (ii) a second computing resource from the second partition to the first partition when the predicted workload is above a second threshold.
    Type: Grant
    Filed: November 4, 2020
    Date of Patent: February 20, 2024
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Dinesh C. Verma, Raghu Kiran Ganti, Bijan Davari
  • Patent number: 11830371
    Abstract: Aspects of the invention include receiving, by a processor, airspace data associated with a predefined airspace, obtaining roadway data associated with the predefined airspace, determining a set of air travel channels within the predefined airspace based on the roadway data, defining a set of travel lanes within the set of air travel channels, wherein each travel lane in the set of travel lanes comprises an altitude range, receiving unmanned aircraft (UA) data associated with a set of UAs within the predefined airspace, wherein the UA data comprises one or more flight paths for each UA in the set of UAs, and assigning each UA in the set of UAs to a travel lane in the set of travel lanes based on the one or more flight paths.
    Type: Grant
    Filed: September 17, 2020
    Date of Patent: November 28, 2023
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Naveen Mathew Nathan Sathiyanathan, Linsong Chu, Raghu Kiran Ganti, Mudhakar Srivatsa
  • Publication number: 20230376518
    Abstract: Systems, methods and/or computer program products for controlling and visualizing topic modeling results using a topic modeling interface. The interface allows user directed exploration, understanding and control of topic modeling algorithms, while offering both semantic summaries and/or structure attribute explanations about results. Explanations and differentiations between results are presented using metrics such as cohesiveness and visual displays depicting hierarchical organization. Through user-manipulation of features of the interface, iterative changes are implemented through user-feedback, adjusting parameters, broadening or narrowing topic results, and/or reorganizing topics by splitting or merging topics. As users trigger visual changes to results being displayed, users can compare and contrast output from the topic modeling algorithm.
    Type: Application
    Filed: May 19, 2022
    Publication date: November 23, 2023
    Inventors: RAGHU KIRAN GANTI, MUDHAKAR SRIVATSA, Shreeranjani Srirangamsridharan, Jae-Wook Ahn, Michele Merler, Dean Steuer
  • Patent number: 11797842
    Abstract: Aspects of the present disclosure relate to identifying friction points in customer data. In some embodiments, identifying friction points can include receiving a set of input sequence data and predicted class labels for the set of input sequence data; selecting input sequences, from the set of input sequence data, that have class labels matching a ground truth class label; reducing the selected sequences to anchor points; and grouping the reduced selected sequences into critical data set signatures using discriminatory subsequence mining.
    Type: Grant
    Filed: August 2, 2019
    Date of Patent: October 24, 2023
    Assignee: International Business Machines Corporation
    Inventors: Linsong Chu, Pranita Sharad Dewan, Raghu Kiran Ganti, Joshua M. Rosenkranz, Mudhakar Srivatsa
  • Patent number: 11727266
    Abstract: Aspects of the present disclosure relate to annotating or tagging customer data. In some embodiments, the annotating can include summarizing touchpoints into k-hot encoding feature vectors, mapping the feature vectors onto an embedding layer, predicting a hierarchical data sequence using the embedding layer and the feature vectors, extracting the feature vectors that are most influential in predicting the embedding layer, and outputting the touchpoints associated with the most influential feature vectors.
    Type: Grant
    Filed: August 2, 2019
    Date of Patent: August 15, 2023
    Assignee: International Business Machines Corporation
    Inventors: Linsong Chu, Pranita Sharad Dewan, Raghu Kiran Ganti, Joshua M. Rosenkranz, Mudhakar Srivatsa
  • Publication number: 20230252297
    Abstract: Aspects of the present disclosure relate to annotating or tagging customer data. In some embodiments, the annotating can include summarizing touchpoints into k-hot encoding feature vectors, mapping the feature vectors onto an embedding layer, predicting a hierarchical data sequence using the embedding layer and the feature vectors, extracting the feature vectors that are most influential in predicting the embedding layer, and outputting the touchpoints associated with the most influential feature vectors.
    Type: Application
    Filed: April 18, 2023
    Publication date: August 10, 2023
    Inventors: Linsong Chu, Pranita Sharad Dewan, Raghu Kiran Ganti, Joshua M. Rosenkranz, Mudhakar Srivatsa
  • Publication number: 20230252902
    Abstract: Provided are a computer-implemented method, a computer program product, and a computer system for drone deployment for distributed asset maintenance and repair. Embodiments identify a fix for a problem at an asset and identify a drone to perform the fix. Embodiments generate an initial flight plan that describes a drone flight path for the drone, and embodiments generate an updated flight plan for the drone by updating the drone flight path using real-time air traffic data, real-time road traffic data, and real-time drone flight path conditions obtained from one or more edge devices. Embodiments generate an overall flight plan for the drone and one or more other drones using a predicted cost and a predicted period of time for the updated drone flight path. Embodiments send a drone flight path from the overall flight plan to the drone with instructions to fix the problem.
    Type: Application
    Filed: February 8, 2022
    Publication date: August 10, 2023
    Inventors: Thiago BIANCHI, Tiago BERTONI SCARTON, Raghu Kiran GANTI, Mudhakar SRIVATSA
  • Patent number: 11687709
    Abstract: Provided are a method, system, and computer program product for representing text, in which a text is received and analyzed by utilizing a pre-trained embedding model and a feature vector model, wherein selected words in the text have corresponding weights. Operations whose parameters include weights of a feature vector and an embedding are performed to generate a weighted embedding data structure. A summation is performed of all corresponding columns of a plurality of rows of the weighted embedding data structure to generate a data structure that represents the text. The data structure that represents the text is utilized to generate at least one of a classification metadata for the text and a summarization of the text.
    Type: Grant
    Filed: October 22, 2020
    Date of Patent: June 27, 2023
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Dylan Zucker, Adham Suliman, Foad Khoshouei, ChunHui Y. Higgins, Raghu Kiran Ganti, Shirley M. Han, Isaiah Santala
  • Publication number: 20230169354
    Abstract: A system, computer program product, and method are provided for distributed data workflow semantics. A pipeline, such as a machine learning (ML) pipeline, is represented in a data flow graph (DFG). The represented pipeline is subject to annotations, with the annotations including pipeline nodes and object references. The pre-processed pipeline is subject to execution or processing with the annotated object references capturing object lineage. Output from the executed pipeline is constructed and a corresponding control signal is formatted to dynamically and selectively control an operatively coupled physical hardware device or software.
    Type: Application
    Filed: November 30, 2021
    Publication date: June 1, 2023
    Applicant: International Business Machines Corporation
    Inventors: Mudhakar SRIVATSA, Raghu Kiran GANTI, Carlos Henrique ANDRADE COSTA, Linsong CHU, Joshua M. ROSENKRANZ
  • Publication number: 20230169408
    Abstract: A system, computer program product, and method are provided for distributed data workflow semantics. A pipeline, such as a machine learning (ML) pipeline, is implemented over a data flow graph (DFG) with nodes configured to support rich semantics. The rich semantics include two or more operational semantics, and at least one lineage semantic to selectively combine features that trace lineage to a common input object. The lineage semantic is leveraged to associate training and testing data set pairs in cross validation of the trained ML models produced from parallelizing the selection of ML pipelines.
    Type: Application
    Filed: November 30, 2021
    Publication date: June 1, 2023
    Applicant: International Business Machines Corporation
    Inventors: Carlos Henrique Andrade Costa, RAGHU KIRAN GANTI, MUDHAKAR SRIVATSA, Linsong Chu, Joshua M. Rosenkranz, Tuan Minh HOANG TRONG
  • Publication number: 20230168923
    Abstract: A system, computer program product, and method are provided for distributed data workflow semantics. A pipeline, such as a machine learning pipeline, is represented in a data flow graph (DFG) with nodes and edges. The represented nodes are configured to be annotated with an operational semantic. On order of execution of the pipeline is discovered through the node annotation(s) represented in the annotated DFG, and execution of the pipeline is based on the discovered order. A control signal formatted based on the executed pipeline is configured to dynamically and selectively control an operatively coupled physical hardware device.
    Type: Application
    Filed: November 30, 2021
    Publication date: June 1, 2023
    Applicant: International Business Machines Corporation
    Inventors: Raghu Kiran GANTI, Mudhakar SRIVATSA, Carlos Henrique Andrade Costa
  • Patent number: 11594022
    Abstract: Aspects of the invention include generating a combined raster image from point cloud data and reference data describing an original location of a power line. Selecting a set of candidate pixels from the combined raster image describing an updated location of a power line, wherein the selection is based at least in part on a location of pixels in the combined raster image that describe the original location. Detecting pixels from the set of candidate pixels that describe an updated location of a power line. Modifying the combined raster image to reflect the updated location of the power line.
    Type: Grant
    Filed: November 16, 2020
    Date of Patent: February 28, 2023
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Linsong Chu, Mudhakar Srivatsa, Raghu Kiran Ganti
  • Patent number: 11551143
    Abstract: A computer-implemented method for generating and deploying a reinforced learning model to train a chatbot. The method includes selecting a plurality of conversations, wherein each conversation includes an agent and a user. The method includes identifying, in each of the conversations, a set of turns and on or more topics. The method further includes associating one or more topics to each turn of the set of turns. The method includes, generating a conversation flow for each conversation, wherein the conversation flow identifies a sequence of the topics. The method includes applying an outcome score to each conversation. The method includes creating a reinforced learning (RL) model, wherein the RL model includes a Markov is based on the conversation flow of each conversation and the outcome score of each conversation. The method includes deploying the RL model, wherein the deploying includes sending the RL model to a chatbot.
    Type: Grant
    Filed: November 21, 2019
    Date of Patent: January 10, 2023
    Assignee: International Business Machines Corporation
    Inventors: Raghu Kiran Ganti, Mudhakar Srivatsa, Shreeranjani Srirangamsridharan, Yeon-sup Lim, Linsong Chu
  • Patent number: 11487822
    Abstract: Techniques for inserting and extracting geolocation data using spatial indexing in a key value database are provided. In an embodiment, a system is provided for generating one or more geohashes for a geometry object, wherein the one or more geohashes comprises encoded bits that are stored as keys in a key value database. In one example, the system comprises a geometry indexing component that generates a spatial index, wherein the spatial index is based on a total number of the encoded bits generated for the one or more geohashes. In one example, the system comprises a geometry storing component that stores the geometry object and the one or more geohashes in the key value database using the spatial index to allow for faster retrieval of the geometry object. The advantage is that properly inserted and indexed spatial data can be quickly retrieved.
    Type: Grant
    Filed: June 13, 2018
    Date of Patent: November 1, 2022
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Raghu Kiran Ganti, Mudhakar Srivatsa, Dakshi Agrawal, Kisung Lee
  • Patent number: 11410558
    Abstract: An action recommendation system uses reinforcement learning that provides a next action recommendation to a traffic controller to give to a vehicle pilot such as an aircraft pilot. The action recommendation system uses data of past human actions to create a reinforcement learning model and then uses the reinforcement learning model with current ABS-B data to provide the next action recommendation to the traffic controller. The action recommendation system may use an anisotropic reward function and may also include an expanding state space module that uses a non-uniform granularity of the state space.
    Type: Grant
    Filed: May 21, 2019
    Date of Patent: August 9, 2022
    Assignee: International Business Machines Corporation
    Inventors: Raghu Kiran Ganti, Mudhakar Srivatsa, Venkatesh Ashok Rao Rao, Linsong Chu
  • Patent number: 11372821
    Abstract: A spatial-temporal storage method, system, and non-transitory computer readable medium, include, in a first layer, a geometric translation circuit configured to split spatial-temporal information into row keys and translate a geometry query into a range scan, and a multi-scan optimization circuit configured to compute an optimal read strategy to optimize the range scan translated by the geometric translation circuit into a series of block starting offsets and block sizes, and, in a second layer, a block grouping circuit configured to allow grouping of blocks in the second layer while preserving spatial data locality when splits of spatial-temporal information occur in the first layer.
    Type: Grant
    Filed: August 7, 2018
    Date of Patent: June 28, 2022
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Raghu Kiran Ganti, Shen Li, Mudhakar Srivatsa