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Sabu K Syed

from Austin, TX
Age ~53
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Also known as:
Sabu Ks, Syed Sabu
Phone and address:
16617 Barrhead Cv, Austin, TX 78717
(512) 341-3441
Related to:
Yusuf S Syed, 23
Connected to:
Adnan A Syed, 56Ahsen A Syed, 33Aladdin Z Syed, 79Allam A Syed, 74Amina A Syed, 46Arij H Syed, 34Arshia M Syed, 53Asghar A Syed, 64Asher N Syed, 60Ashraf S Syed, 48

Sabu Syed Phones & Addresses

  • 16617 Barrhead Cv, Austin, TX 78717 (512) 341-3441
  • 2612 Water Well Ln, Austin, TX 78728 (512) 670-9728
  • 10926 Jollyville Rd, Austin, TX 78759 (512) 241-0856
  • 4502 Emerald Forest Dr, Durham, NC 27713 (919) 544-5015
  • Ft Lewis, WA
  • 16617 Barrhead Cv, Austin, TX 78717 (512) 657-1625

Work

Company: Dell inc Dec 2000 Address: Austin, Texas Area Position: Enterprise architect

Education

Degree: Bachelor of Technology School / High School: University of Calicut 1988 to 1992 Specialities: Computer Science & Engineering

Skills

Enterprise Architecture • Enterprise Software • Soa • Cloud Computing • Solution Architecture • Integration • It Strategy • Agile Methodologies • Eai • Virtualization • Saas • Architecture • Middleware

Industries

Computer Software

Resumes

Resumes

Sabu Syed Photo 1

Enterprise Architect

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Location:
Austin, TX
Industry:
Computer Software
Work:
Dell Inc - Austin, Texas Area since Dec 2000
Enterprise Architect
IBM Tivoli Software - Raleigh-Durham, North Carolina Area Feb 1999 - Nov 2000
Software Engineer
Credit Suisse First Boston - Singapore 1997 - 1999
Sr. Software Engineer
Habib Bank AG Zurich - Dubai, United Arab Emirates 1994 - 1997
Sr. Software Engineer
Education:
University of Calicut 1988 - 1992
Bachelor of Technology, Computer Science & Engineering
Skills:
Enterprise Architecture
Enterprise Software
Soa
Cloud Computing
Solution Architecture
Integration
It Strategy
Agile Methodologies
Eai
Virtualization
Saas
Architecture
Middleware

Publications

Us Patents

Device Component Management Using Deep Learning Techniques

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US Patent:
20210241151, Aug 5, 2021
Filed:
Jan 30, 2020
Appl. No.:
16/776918
Inventors:
- Round Rock TX, US
Akanksha Goel - Faridabad, IN
Hung T. Dinh - Austin TX, US
Sabu K. Syed - Austin TX, US
James S. Watt - Austin TX, US
Kannappan Ramu - Frisco TX, US
International Classification:
G06N 7/00
G06N 3/08
G06F 3/06
G06F 11/30
Abstract:
Methods, apparatus, and processor-readable storage media for device component management using deep learning techniques are provided herein. An example computer-implemented method includes obtaining telemetry data from one or more enterprise devices; determining, for each of the one or more enterprise devices, values for multiple device attributes by processing the obtained telemetry data; generating, for each of the one or more enterprise devices, at least one prediction related to lifecycle information of at least one device component by processing the determined attribute values using one or more deep learning techniques; and performing one or more automated actions based at least in part on the at least one generated prediction.

Using Artificial Intelligence And Natural Language Processing For Data Collection In Message Oriented Middleware Frameworks

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US Patent:
20210209102, Jul 8, 2021
Filed:
Jan 7, 2020
Appl. No.:
16/735951
Inventors:
- Round Rock TX, US
Sabu K. Syed - Austin TX, US
Satish Ranjan Das - Round Rock TX, US
Manikandan Pammal Rathinavelu - Cedar Park TX, US
Panguluru Vijaya Sekhar - Bangalore, IN
Kannappan Ramu - Frisco TX, US
International Classification:
G06F 16/2452
G06F 16/248
G06F 16/25
G06N 20/00
G06N 5/04
G06F 16/242
Abstract:
A method includes receiving a natural language query requesting data from a message oriented middleware infrastructure comprising a plurality of message oriented middleware providers, and analyzing the natural language query to determine one or more types of the data being requested. In the method, one or more queries corresponding to the determined one or more types of the data are dynamically generated. The one or more queries are in native command formats corresponding to respective ones of the plurality of message oriented middleware providers. The method also includes executing the one or more queries in the native command formats to retrieve the data from the plurality of message oriented middleware providers, and providing a response to the natural language query based on the retrieved data to a user via a user interface.

Using Artificial Intelligence And Natural Language Processing For Data Collection In Message Oriented Middleware Frameworks

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US Patent:
20210209170, Jul 8, 2021
Filed:
Jan 7, 2020
Appl. No.:
16/735933
Inventors:
- Round Rock TX, US
Sabu K. Syed - Austin TX, US
Satish Ranjan Das - Round Rock TX, US
Manikandan Pammal Rathinavelu - Cedar Park TX, US
Panguluru Vijaya Sekhar - Bangalore, IN
Kannappan Ramu - Frisco TX, US
International Classification:
G06F 16/9032
G06F 40/20
G06N 20/00
G06K 9/62
H04L 12/58
G06F 17/18
Abstract:
A method includes receiving a natural language query requesting data from a message oriented middleware infrastructure comprising a plurality of message oriented middleware providers, and analyzing the natural language query to determine one or more types of the data being requested. In the method, one or more stored queries corresponding to the determined one or more types of the data are identified. The one or more stored queries are in native command formats corresponding to respective ones of the plurality of message oriented middleware providers. The method also includes executing the identified one or more stored queries in the native command formats to retrieve the data from the plurality of message oriented middleware providers, and providing a response to the natural language query based on the retrieved data to a user via a user interface.

Microservice Management Using Machine Learning

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US Patent:
20210142159, May 13, 2021
Filed:
Nov 8, 2019
Appl. No.:
16/677890
Inventors:
- Round Rock TX, US
Hung The Dinh - Austin TX, US
Sabu Syed - Austin TX, US
Ramu Kannappan - Frisco TX, US
Jatin Kamlesh Thakkar - Bangalore, IN
International Classification:
G06N 3/08
G06N 3/04
G06F 17/27
Abstract:
In some examples, a computing device may implement a method that includes receiving microservice profile information at a microservice profiler, performing lexical analysis of the microservice profile information (where the lexical analysis produces tokenized information), generating microservice modification information by performing machine learning analysis of one or more inputs (where the one or more inputs comprise the tokenized information), and outputting the microservice modification information from the microservice profiler. The microservice profile information describes one or more characteristics of a microservice. The lexical analysis is performed by a lexical analysis engine of the microservice profiler, and the machine learning analysis is performed by a machine learning system of the microservice profiler.

Code Development For Deployment On A Cloud Platform

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US Patent:
20210132935, May 6, 2021
Filed:
Oct 31, 2019
Appl. No.:
16/670460
Inventors:
- Round Rock TX, US
Rajesh Krishnan - Bangalore, IN
Pallavi Jaini - Shrewsbury MA, US
Puttaraju Chikkanna - Bangalore, IN
Nikhil Reddy Kota - Round Rock TX, US
Venkat S. Ramachandran - Round Rock TX, US
Navin Kumar - Bangalore, IN
Nithiyanandham Tamilselvan - Salem, IN
Naga Kalyan Kambapu - Austin TX, US
Desai Yarlagadda - Hyderabad, IN
Lakshmi Prasad Banala - Round Rock TX, US
Shubham Gupta - Jaipur, IN
Reddeppa Kollu - Leander TX, US
Sabu K. Syed - Austin TX, US
Anubhab Mohanty - Cuttack, IN
Vibhor Sharma - Alwar, IN
Md Shadab Ali - Nawada, IN
International Classification:
G06F 8/65
G06F 8/75
G06F 9/4401
G06F 8/36
Abstract:
A method includes receiving code for computer programming, analyzing the code and extracting a plurality of configuration properties from the code. In the method, one or more configuration files are generated from the extracted plurality of configuration properties, and microservice code is generated from the one or more configuration files. The microservice code is configured for deployment on one or more cloud computing platforms.

Cognitive Device Management Using Artificial Intelligence

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US Patent:
20210133554, May 6, 2021
Filed:
Oct 30, 2019
Appl. No.:
16/668440
Inventors:
- Hopkinton MA, US
Hung T. Dinh - Austin TX, US
Sabu K. Syed - Austin TX, US
Anay Kishore - Bihar, IN
Kannappan Ramu - Frisco TX, US
International Classification:
G06N 3/08
Abstract:
Methods, apparatus, and processor-readable storage media for cognitive device management using artificial intelligence are provided herein. An example computer-implemented method includes determining an initial telemetry data collection frequency value for a given device by applying machine learning techniques to historic data pertaining to additional devices; collecting an initial set of telemetry data associated with the given device and one or more subsequent sets of telemetry data associated with the given device in accordance with the initial telemetry data collection frequency value; performing a comparison of the one or more subsequent sets of telemetry data to the initial set of telemetry data; updating the initial telemetry data collection frequency value by applying the machine learning techniques to information resulting from the comparison; determining automated actions related to the given device by utilizing a neural network in connection with the collected telemetry data; and automatically initiating the automated actions.

Augmenting End-To-End Transaction Visibility Using Artificial Intelligence

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US Patent:
20210133594, May 6, 2021
Filed:
Oct 30, 2019
Appl. No.:
16/668947
Inventors:
- Round Rock TX, US
Kiran Kumar Pidugu - SangaReddy, IN
Sabu K. Syed - Austin TX, US
Lakshman Kumar Tiwari - Uttar Pradesh, IN
Geetha Venkatesan - Bangalore, IN
Sourav Datta - Bangalore, IN
Vijaya P. Sekhar - Bangalore, IN
Kannappan Ramu - Frisco TX, US
Jatin Kamlesh Thakkar - Bangalore, IN
International Classification:
G06N 5/02
G06Q 10/10
G06N 20/00
Abstract:
Methods, apparatus, and processor-readable storage media for augmenting end-to-end transaction visibility using artificial intelligence are provided herein. An example computer-implemented method includes obtaining data related to multiple transaction flows across multiple data sources within an enterprise system, and forecasting anomalies in connection with at least one of the transaction flows by applying one or more of a first set of artificial intelligence techniques to portions of the obtained data, wherein applying the artificial intelligence techniques is based on which of the multiple data sources correspond to the portions of the obtained data. Such a method further includes determining automated actions to be performed in connection with the forecasted anomalies by applying one or more of a second set of artificial intelligence techniques to portions of the obtained data related to the forecasted anomalies, and performing the automated actions in connection with the at least one transaction flow.

Device Manufacturing Cycle Time Reduction Using Machine Learning Techniques

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US Patent:
20210133930, May 6, 2021
Filed:
Oct 31, 2019
Appl. No.:
16/669667
Inventors:
- Round Rock TX, US
Rajesh Krishnan - Bangalore, IN
Vijaya P. Sekhar - Bangalore, IN
Sabu K. Syed - Austin TX, US
Geetha Venkatesan - Bangalore, IN
Sethukarasi Sockalingam - Bangalore, IN
Pradeepta Ranjan Choudhury - Bengaluru, IN
Abhijit Mishra - Bangalore, IN
Kannappan Ramu - Frisco TX, US
Jatin Kamlesh Thakkar - Bangalore, IN
International Classification:
G06T 5/00
G06N 3/08
G06T 7/13
G06K 9/00
Abstract:
Methods, apparatus, and processor-readable storage media for device manufacturing cycle time reduction using machine learning techniques are provided herein. An example computer-implemented method includes obtaining video input related to one or more manufacturing resources in a manufacturing environment; determining availability status information for at least one of the one or more manufacturing resources by applying one or more machine learning models to the obtained video input; and outputting the determined availability status information to at least one user device associated with the manufacturing environment.
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Sabu K Syed from Austin, TX, age ~53 Get Report