Subhendu Das, 63207 Autumn Dr, Chapel Hill, NC 27516

2011013, Jun 2, 2011

Nov 22, 2010

12/952014

Xiao Jun Dai - Beijing, CN
Subhendu Das - Durham NC, US
Zhi Gan - Beijing, CN
Zhang Yue - Beijing, CN

INTERNATIONAL BUSINESS MACHINES CORPORATION - Armonk NY

G06F 12/08

711129, 711141, 711E12022, 711E12026

Managing access to a cache memory includes dividing said cache memory into multiple of cache areas, each cache area having multiple entries; and providing at least one separate lock attribute for each cache area such that only a processor thread having possession of the lock attribute corresponding to a particular cache area can update that cache area.

2012019, Jul 26, 2012

Mar 20, 2012

13/425197

Xiao Jun Dai - Beijing, CN
Subhendu Das - Durham NC, US
Zhi Gan - Beijing, CN
Zhang Yue - Beijing, CN

INTERNATIONAL BUSINESS MACHINES CORPORATION - Armonk NY

G06F 12/08
G06F 12/12
G06F 12/14

711129, 711145, 711133, 711E12094, 711E12069, 711E1204

Managing access to a cache memory includes dividing said cache memory into multiple of cache areas, each cache area having multiple entries; and providing at least one separate lock attribute for each cache area such that only a processor thread having possession of the lock attribute corresponding to a particular cache area can update that cache area.

2022040, Dec 22, 2022

Jun 16, 2021

17/349882

- Armonk NY, US
Subhendu Das - Chapel Hill NC, US
Mukesh Kumar - Bangalore, IN

G06Q 10/06
G06N 20/00
G06Q 40/08
G06Q 20/40

Embodiments relate to a system, program product, and method for automatically executing an impact analysis of a data analytics pipeline to determine impacts to the pipeline subject to changes to input data and the pipeline. The method includes determining, automatically, components of the pipeline that are impacted by the implemented changes. The method also includes identifying datasets to rescore through the pipeline. Each of the datasets to rescore have been scored through the pipeline prior to the changes such that previous scores of each of the respective datasets have been determined by the pipeline prior to the changes. The method further includes rerunning, through only the determined impacted components, the datasets, thereby generating rescores of the datasets. The method also includes retrieving each of the previous scores of the datasets, comparing the rescores with the respective previous scores, and transmitting, subject to the comparing, alerts to an output device.

2022030, Sep 29, 2022

Mar 24, 2021

17/210954

- Armonk NY, US
Mukesh Kumar - BANGALORE, IN
Subhendu Das - Chapel Hill NC, US

G06F 11/34

A processor may receive target data regarding initial targets. The initial targets may relate to specific values for a first set of factors regarding performance of tasks for a first time period. The processor may receive task data regarding the performance of the tasks. The task data may be associated with values for a second set of factors over a second time period. The processor may analyze attributes of the tasks. The processor may generate feature data regarding features of the task. The features may relate to the attributes of the tasks that can be varied to perform the tasks over the second time period. The processor may generate a simulation of the performance of the tasks using the task data and the feature data.

2022030, Sep 29, 2022

Mar 23, 2021

17/209568

- Armonk NY, US
Mukesh Kumar - BANGALORE, IN
Subhendu Das - Chapel Hill NC, US

G06N 20/00
G06N 5/04

In some embodiments, a processor may receive a claim, where the claim relates to an event. The processor may identify characteristics of the claim. The processor may determine, using an AI model, an alert reason based on a similarity of the characteristics of the claim to characteristics of one or more other claims. The processor may generate an alert notification, and the processor may output the alert notification to a user.

2022026, Aug 18, 2022

Feb 18, 2021

17/178967

- Armonk NY, US
Subhendu Das - Chapel Hill NC, US
Mukesh Kumar - Bangalore, IN
Shweta Shandilya - Bangalore, IN

G06F 9/30
G06F 9/38
G06F 9/50

A computer-implemented system, method and computer program product for preparing alert reports that includes: receiving an override request to override an insight used to prepare the alert reports; determining, determining one or more execution pipelines used to prepare the alert reports that used the insight that is the subject of the override request; determining one or more impacted pipeline runs that were executed to prepare the alert reports that used the insight that is the subject of the override request; updating the one or more execution pipelines used to prepare the alert reports; and generating new alert reports, wherein generating the new alert reports comprises re-running the one or more impacted pipeline runs using the one or more updated execution pipelines wherein the insight that is the subject of the override request is overridden.

2022017, Jun 9, 2022

Dec 7, 2020

17/114419

- Armonk NY, US
Ratul Sarkar - Bangalore, IN
Ankit Kumar Singh - Ranchi, IN
Subhendu Das - Chapel Hill NC, US

G06F 16/93
G06N 20/00

A computer categorizes a news article by an activity and an associated activity phase, includes receiving, by a computer, at least one news article from an article source. The computer assigns for each news article, an activity of focus selected from a list of target activities, using a first machine learning model. The computer identifies, for each news article, at least one activity phase candidate selected from a list of activity phases associated with the activity of focus, using a second machine learning model. The computer determines, for each of new article, an activity phase of focus from among the activity phase candidates. The determination is based, at least in part on a confirmation attribute associated with the article. The computer categorizes each of the articles by said activity of focus and said activity phase of focus.

2023001, Jan 19, 2023

Jul 13, 2021

17/374485

- Armonk NY, US
Subhendu Das - Chapel Hill NC, US
Mukesh Kumar - BANGALORE, IN

G06Q 20/40
G06F 11/32
G06F 11/30

A computer-implemented system, platform, computer program product, tool, and/or method for re-running alert reports that includes: identifying an alert report to be rerun; collecting information on the alert report; gathering information on the configuration of a data analytics pipeline that generated the alert report; gathering data used to generate the alert report; recreating a regenerated data analytics pipeline based upon the information gathered on the configuration of the data analytics pipeline that generated the alert report; running the regenerated data analytics pipeline using the gathered data to create a rerun alert report; and optionally comparing the rerun to the original run including optionally generating a visual display of the results including in an aspect creating a side-by-side comparison of the tasks.