Search
Full Menu and site Navigation
Los Angeles

The INCOSE-LA Chapter is one of the largest in the world with approximately 400 members from over 40 organizations. The largest company contingents are represented by most major aerospace and telecommunications companies, CMMi consultants, civil agencies, universities and transportation industry. 

Keep up with INCOSE-LA on:
Facebook
LinkedIn
INCOSE LA Meetup Group
Now on YouTube

Quick Links:
CSER 2020
INCOSE Connect LA Chapter Folder
INCOSE Careers Links
SE Junior Handbook
LA Chapter Trello Management Site

Artificial Intelligence for Systems Engineering - AI4SE 2020

Artificial Intelligence for Systems Engineering - AI4SE 2020
Madrid, Spain
13-14 October 2020


The Knowledge Reuse Group, INCOSE and AEIS invite submissions to AI4SE workshop, which will take place at Carlos III University of Madrid within the “Artificial Intelligence in Systems Engineering Week”.

Artificial Intelligence (AI), sometimes called machine intelligence, is intelligence “demonstrated” by machines, in contrast to the natural intelligence displayed by humans and animals. Computer science defines AI research as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chances of successfully achieving its goals. Colloquially, the term "artificial intelligence" is used to describe machines that mimic certain "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving".

Systems Engineering (SE) is an interdisciplinary field of engineering development and engineering management that focuses on how to design and manage complex systems throughout their life cycle. Activities such as requirements engineering, reliability management, logistics, coordination of different teams, testing and evaluation, maintainability and many other disciplines necessary for the successful development, design, implementation, and ultimate decommission of systems, become more difficult when dealing with large or complex projects.

Topics of interest: 
Many of the challenges described in the previous definitions are human intensive, and could demand highly developed skills in learning, reasoning, decision making and problem solving. Therefore, Artificial Intelligence and all of its interleaved variants (machine learning, knowledge engineering, artificial reasoning, ontologies, optimization methods, etc.) are more and more relevant to systems engineering.

On the other hand, emergent Intelligent Systems like autonomous vehicles in all their facets (cars, trains, submarines, aircrafts, ships, etc.) are revolutionizing our perception of services. These systems are offering divergent ways of operations, where machines learn from their own operation and, theoretically, they improve its quality of service. Not deterministic systems propose giant challenges like how the certification should take place considering they will operate differently along its service life. How to V&V them, or even how to configure them in the case of potential accidents, ethical aspects etc. 

For more information, for the workshop visit the website and see the AI4SE 2020 Call for Papers.

Artificial Intelligence for Systems Engineering - AI4SE 2020

Artificial Intelligence for Systems Engineering - AI4SE 2020
Madrid, Spain
13-14 October 2020


The Knowledge Reuse Group, INCOSE and AEIS invite submissions to AI4SE workshop, which will take place at Carlos III University of Madrid within the “Artificial Intelligence in Systems Engineering Week”.

Artificial Intelligence (AI), sometimes called machine intelligence, is intelligence “demonstrated” by machines, in contrast to the natural intelligence displayed by humans and animals. Computer science defines AI research as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chances of successfully achieving its goals. Colloquially, the term "artificial intelligence" is used to describe machines that mimic certain "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving".

Systems Engineering (SE) is an interdisciplinary field of engineering development and engineering management that focuses on how to design and manage complex systems throughout their life cycle. Activities such as requirements engineering, reliability management, logistics, coordination of different teams, testing and evaluation, maintainability and many other disciplines necessary for the successful development, design, implementation, and ultimate decommission of systems, become more difficult when dealing with large or complex projects.

Topics of interest: 
Many of the challenges described in the previous definitions are human intensive, and could demand highly developed skills in learning, reasoning, decision making and problem solving. Therefore, Artificial Intelligence and all of its interleaved variants (machine learning, knowledge engineering, artificial reasoning, ontologies, optimization methods, etc.) are more and more relevant to systems engineering.

On the other hand, emergent Intelligent Systems like autonomous vehicles in all their facets (cars, trains, submarines, aircrafts, ships, etc.) are revolutionizing our perception of services. These systems are offering divergent ways of operations, where machines learn from their own operation and, theoretically, they improve its quality of service. Not deterministic systems propose giant challenges like how the certification should take place considering they will operate differently along its service life. How to V&V them, or even how to configure them in the case of potential accidents, ethical aspects etc. 

For more information, for the workshop visit the website and see the AI4SE 2020 Call for Papers.

News

  • INCOSE-LA September 2020 New Members

    Date | Oct 02, 2020

    Name

    Organization

    Su Jun Zhang

    SAIC

    Michael Perz

    LinQuest Corporation

    Sal Castellino

    Linquest Corporation

    Michelle Glaser-Weiner

    LinQuest Corp

    Joseph Bell

    G2 Ops, Inc.

    Althaf Syed

    Linquest Corporation

    Kibeom Sung

     

    Lilliam Brown

    SAIC

    Ulric Pattillo

    The Linquest Corporation

    Shawkang Wu

    LinQuest

    tan nguyen

    linquest corporation

    Julia White

    The Aerospace Corporation

    Elizabeth Wimberly

     

    Clinton Brdlik

    US Department of Defense

    Bret Botzong

    Linquest Corporation

    Brian Harms

    LinQuest

    Lawrence Yu

    saic

    Eric Berg

    Moog Aircraft Group

    Gary Wilson

    Raytheon Technologies

    Carlos Guardado

    BAE Systems

    Adriana Fukuzato

    SAIC

    Annie Trenkle

     

    Fay Plummer

     

    michael cameron

    Boeing

    Marlon Bright

    John Deere

    Hetav Patel

    The Aerospace Corporation

    Morgan Tubb

    Lockheed Martin Corporation

    Stephen Noel

    SAIC


Artificial Intelligence for Systems Engineering - AI4SE 2020

Artificial Intelligence for Systems Engineering - AI4SE 2020
Madrid, Spain
13-14 October 2020


The Knowledge Reuse Group, INCOSE and AEIS invite submissions to AI4SE workshop, which will take place at Carlos III University of Madrid within the “Artificial Intelligence in Systems Engineering Week”.

Artificial Intelligence (AI), sometimes called machine intelligence, is intelligence “demonstrated” by machines, in contrast to the natural intelligence displayed by humans and animals. Computer science defines AI research as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chances of successfully achieving its goals. Colloquially, the term "artificial intelligence" is used to describe machines that mimic certain "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving".

Systems Engineering (SE) is an interdisciplinary field of engineering development and engineering management that focuses on how to design and manage complex systems throughout their life cycle. Activities such as requirements engineering, reliability management, logistics, coordination of different teams, testing and evaluation, maintainability and many other disciplines necessary for the successful development, design, implementation, and ultimate decommission of systems, become more difficult when dealing with large or complex projects.

Topics of interest: 
Many of the challenges described in the previous definitions are human intensive, and could demand highly developed skills in learning, reasoning, decision making and problem solving. Therefore, Artificial Intelligence and all of its interleaved variants (machine learning, knowledge engineering, artificial reasoning, ontologies, optimization methods, etc.) are more and more relevant to systems engineering.

On the other hand, emergent Intelligent Systems like autonomous vehicles in all their facets (cars, trains, submarines, aircrafts, ships, etc.) are revolutionizing our perception of services. These systems are offering divergent ways of operations, where machines learn from their own operation and, theoretically, they improve its quality of service. Not deterministic systems propose giant challenges like how the certification should take place considering they will operate differently along its service life. How to V&V them, or even how to configure them in the case of potential accidents, ethical aspects etc. 

For more information, for the workshop visit the website and see the AI4SE 2020 Call for Papers.