Patents by Inventor Saurabh Mahapatra
Saurabh Mahapatra 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: 20240031631Abstract: Systems and methods for content customization are provided. One aspect of the systems and methods includes receiving dynamic characteristics for a plurality of users, wherein the dynamic characteristics include interactions between the plurality of users and a digital content channel; clustering the plurality of users in a plurality of segments based on the dynamic characteristics using a machine learning model; assigning a user to a segment of the plurality of segments based on static characteristics of the user; and providing customized digital content for the user based on the segment.Type: ApplicationFiled: July 20, 2022Publication date: January 25, 2024Inventors: Atanu R. Sinha, Aurghya Maiti, Atishay Ganesh, Saili Myana, Harshita Chopra, Sarthak Kapoor, Saurabh Mahapatra
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Patent number: 11836172Abstract: Methods, computer systems, computer-storage media, and graphical user interfaces are provided for facilitating data visualization generation. In one implementation, dataset intent data, visual design intent data, and insight intent data determined from a user input natural language query are obtained. A set of candidate intent recommendations is generated using various combinations of the dataset intent data, visual design intent data, and insight intent data. Each of the candidate intent recommendations is incorporated into a set of visualization templates to determine eligibility of the candidate intent recommendations. For eligible candidate intent recommendations, a score associated with a corresponding visualization template is determined. Based on the scores, a candidate intent recommendation and corresponding visualizations template is selected to use as a visual recommendation for presenting a data visualization.Type: GrantFiled: June 22, 2021Date of Patent: December 5, 2023Assignee: Adobe Inc.Inventors: Fan Du, Zening Qu, Vasanthi Swaminathan Holtcamp, Tak Yeon Lee, Sungchul Kim, Saurabh Mahapatra, Sana Malik Lee, Ryan A. Rossi, Nikhil Belsare, Eunyee Koh, Andrew Thomson, Sumit Shekhar
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Publication number: 20230342799Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for incorporating unobserved behaviors when generating user segments or predictions of future user actions. In particular, in one or more embodiments, the disclosed systems utilize a deep learning-based clustering algorithm that segments the behavioral history of users based on a future outcome. Further, the disclosed systems recognize that users may exhibit behaviors that represent two or more segments and allow for targeted marketing to users based on the user’s inclusion in multiple segments.Type: ApplicationFiled: April 25, 2022Publication date: October 26, 2023Inventors: Aurghya Maiti, Atanu R Sinha, Harshita Chopra, Sarthak Kapoor, Atishay Ganesh, Saili Myana, Saurabh Mahapatra
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Publication number: 20230306194Abstract: Systems and methods for data processing are described. Example embodiments include identifying chart data corresponding to a visual element of a user interface; selecting an insight type based on a chart category of the chart data; generating insight data for the insight type based on the chart data using a statistical measure corresponding to the insight type; generating an insight caption for the insight type by combining the insight data with a sentence template corresponding to the insight type; and communicating the insight caption to a user of the user interface.Type: ApplicationFiled: March 24, 2022Publication date: September 28, 2023Inventors: Fan Du, Cameron Elise Womack, Dylan Robert Kario, Molly Josette Bloom, Elizabeth Waters, Matthew Samuel Deutsch, Ryan Wilkes, Yeuk-Yin Chan, Eunyee Koh, Andrew Douglas Thomson, Cole Edward Connelly, Saurabh Mahapatra, Vasanthi Holtcamp
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Publication number: 20230306033Abstract: Embodiments provide systems, methods, and computer storage media for management, assessment, navigation, and/or discovery of data based on data quality, consumption, and/or utility metrics. Data may be assessed using attribute-level and/or record-level metrics that quantify data: “quality” - the condition of data (e.g., presence of incorrect or incomplete values), its “consumption” - the tracked usage of data in downstream applications (e.g., utilization of attributes in dashboard widgets or customer segmentation rules), and/or its “utility” - a quantifiable impact resulting from the consumption of data (e.g., revenue or number of visits resulting from marketing campaigns that use particular datasets, storage costs of data). This data assessment may be performed at different stages of a data intake, preparation, and/or modeling lifecycle.Type: ApplicationFiled: March 14, 2022Publication date: September 28, 2023Inventors: Arpit Ajay Narechania, Fan Du, Atanu R. Sinha, Ryan A. Rossi, Jane Elizabeth Hoffswell, Shunan Guo, Eunyee Koh, John Anderson, Sonali Surange, Saurabh Mahapatra, Vasanthi Holtcamp
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Patent number: 11769100Abstract: Systems and methods for data analytics are described. One or more embodiments of the present disclosure receive target time series data and candidate time series data, where the candidate time series data includes data corresponding to each of a plurality of candidate metrics, train a prediction network to predict the target time series data based on the candidate time series data by setting temporal attention weights corresponding to a plurality of rolling time windows and by setting candidate attention weights corresponding to the plurality of candidate metrics, identify a leading indicator metric for the target time series data from the plurality of candidate metrics based on the temporal attention weights and the candidate attention weights, and signal the leading indicator metric for the target time series data.Type: GrantFiled: May 25, 2021Date of Patent: September 26, 2023Assignee: ADOBE, INC.Inventors: Atanu Sinha, Manoj Kilaru, Iftikhar Ahamath Burhanuddin, Aneesh Shetty, Titas Chakraborty, Rachit Bansal, Tirupati Saketh Chandra, Fan Du, Aurghya Maiti, Saurabh Mahapatra
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Publication number: 20230289839Abstract: Embodiments provide systems, methods, and computer storage media for management, assessment, navigation, and/or discovery of data based on data quality, consumption, and/or utility metrics. Data may be assessed using attribute-level and/or record-level metrics that quantify data: “quality”—the condition of data (e.g., presence of incorrect or incomplete values), its “consumption”—the tracked usage of data in downstream applications (e.g., utilization of attributes in dashboard widgets or customer segmentation rules), and/or its “utility”—a quantifiable impact resulting from the consumption of data (e.g., revenue or number of visits resulting from marketing campaigns that use particular datasets, storage costs of data). This data assessment may be performed at different stages of a data intake, preparation, and/or modeling lifecycle.Type: ApplicationFiled: March 14, 2022Publication date: September 14, 2023Inventors: Arpit Ajay Narechania, Fan Du, Atanu R. Sinha, Ryan A. Rossi, Jane Elizabeth Hoffswell, Shunan Guo, Eunyee Koh, John Anderson, Sonali Surange, Saurabh Mahapatra, Vasanthi Holtcamp
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Publication number: 20230289696Abstract: Embodiments provide systems, methods, and computer storage media for management, assessment, navigation, and/or discovery of data based on data quality, consumption, and/or utility metrics. Data may be assessed using attribute-level and/or record-level metrics that quantify data: “quality”—the condition of data (e.g., presence of incorrect or incomplete values), its “consumption”—the tracked usage of data in downstream applications (e.g., utilization of attributes in dashboard widgets or customer segmentation rules), and/or its “utility”—a quantifiable impact resulting from the consumption of data (e.g., revenue or number of visits resulting from marketing campaigns that use particular datasets, storage costs of data). This data assessment may be performed at different stages of a data intake, preparation, and/or modeling lifecycle.Type: ApplicationFiled: March 14, 2022Publication date: September 14, 2023Inventors: Arpit Ajay Narechania, Fan Du, Atanu R. Sinha, Ryan A. Rossi, Jane Elizabeth Hoffswell, Shunan Guo, Eunyee Koh, John Anderson, Sonali Surange, Saurabh Mahapatra, Vasanthi Holtcamp
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Publication number: 20230136094Abstract: A method of determining efficacy of a dataset includes receiving data from a data source, wherein the data comprises a plurality of fields of unknown efficacy; mapping the data based on a plurality of data quality metrics and based on attributes of the plurality of fields wherein meta-features for the data are obtained; predicting a value for each of the plurality of data quality metrics using a ML model that takes the meta-features as input, wherein the value indicates whether a corresponding data quality metric is suitable for measuring efficacy of the fields; selecting a data quality metric based on the value, wherein the data quality metric measures an efficacy of the fields; and monitoring the efficacy of the fields in the data received from the data source based on the data quality metric.Type: ApplicationFiled: October 28, 2021Publication date: May 4, 2023Inventors: FAN DU, RYAN A. ROSSI, EUNYEE KOH, SUNGCHUL KIM, HANDONG ZHAO, KESHAV VADREVU, SAURABH MAHAPATRA, VASANTHI SWAMINATHAN HOLTCAMP
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Publication number: 20230020886Abstract: A text summarization system auto-generates text summarization models using a combination of neural architecture search and knowledge distillation. Given an input dataset for generating/training a text summarization model, neural architecture search is used to sample a search space to select a network architecture for the text summarization model. Knowledge distillation includes fine-tuning a language model for a given text summarization task using the input dataset, and using the fine-tuned language model as a teacher model to inform the selection of the network architecture and the training of the text summarization model. Once a text summarization model has been generated, the text summarization model can be used to generate summaries for given text.Type: ApplicationFiled: July 8, 2021Publication date: January 19, 2023Inventors: Saurabh Mahapatra, Niyati Chhaya, Snehal Raj, Sharmila Reddy Nangi, Sapthotharan Nair, Sagnik Mukherjee, Jay Mundra, Fan Du, Atharv Tyagi, Aparna Garimella
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Publication number: 20220405314Abstract: Methods, computer systems, computer-storage media, and graphical user interfaces are provided for facilitating data visualization generation. In one implementation, dataset intent data, visual design intent data, and insight intent data determined from a user input natural language query are obtained. A set of candidate intent recommendations is generated using various combinations of the dataset intent data, visual design intent data, and insight intent data. Each of the candidate intent recommendations is incorporated into a set of visualization templates to determine eligibility of the candidate intent recommendations. For eligible candidate intent recommendations, a score associated with a corresponding visualization template is determined. Based on the scores, a candidate intent recommendation and corresponding visualizations template is selected to use as a visual recommendation for presenting a data visualization.Type: ApplicationFiled: June 22, 2021Publication date: December 22, 2022Inventors: Fan Du, Zening Qu, Vasanthi Swaminathan Holtcamp, Tak Yeon Lee, Sungchul Kim, Saurabh Mahapatra, Sana Malik Lee, Ryan A. Rossi, Nikhil Belsare, Eunyee Koh, Andrew Thomson, Sumit Shekhar
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Publication number: 20220383224Abstract: Systems and methods for data analytics are described. One or more embodiments of the present disclosure receive target time series data and candidate time series data, where the candidate time series data includes data corresponding to each of a plurality of candidate metrics, train a prediction network to predict the target time series data based on the candidate time series data by setting temporal attention weights corresponding to a plurality of rolling time windows and by setting candidate attention weights corresponding to the plurality of candidate metrics, identify a leading indicator metric for the target time series data from the plurality of candidate metrics based on the temporal attention weights and the candidate attention weights, and signal the leading indicator metric for the target time series data.Type: ApplicationFiled: May 25, 2021Publication date: December 1, 2022Inventors: Atanu Sinha, Manoj Kilaru, Iftikhar Ahamath Burhanuddin, Aneesh Shetty, Titas Chakraborty, Rachit Bansal, Tirupati Saketh Chandra, Fan Du, Aurghya Maiti, Saurabh Mahapatra
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Patent number: 9152393Abstract: A device receives a dynamic system model for a graphical modeling environment, and associates an entity with the dynamic system model, the entity including an entity model. The device defines at least one of a parameter, a configuration, or a solver setting for the entity model, and performs a simulation of the dynamic system model. The device generates a system event during the simulation of the dynamic system model, and modifies at least one of the parameter, the configuration, or the solver setting for the entity model based on the system event.Type: GrantFiled: December 4, 2012Date of Patent: October 6, 2015Assignee: The MathWorks, Inc.Inventors: Ramamurthy Mani, Saurabh Mahapatra, Wei Li, Omar A. Orqueda