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X-WR-CALDESC:Events for Software Center
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DTSTART;VALUE=DATE:20240610
DTEND;VALUE=DATE:20240615
DTSTAMP:20260524T190927
CREATED:20240202T104108Z
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SUMMARY:Digital Product Management Week
DESCRIPTION:Teaming up with the International Software Product Management Association (ISPMA®)\, to offer a week focused on both the practice and theory of digital product management. This event is a unique platform where experts\, practitioners\, and researchers come together to share knowledge and experiences in a relaxed\, engaging atmosphere. \nThe Digital Product Management Week consists of the following events:\n\nJune 10-13: Summer school on Digital Product Management\nJune 10: PhD defense: Synergizing Data Management\, DataOps\, and Data Pipelines for AI Enhanced Embedded Systems\nJune 11-12: SPM Summit Europe\nJune 12: International Conference on Digital Product Management\nJune 12: Digital Product Passports and demonstrators for traceability\nJune 13: Startup Roundtable: The Frontier of Startups and Product Management\nJune 13: Software Center Reporting Workshop\n\nJoin us for a week of practical insights and valuable connections – more information on the conference website!
URL:https://www.software-center.se/event/digital-product-management-week/
LOCATION:Lindholmen Conference Centre\, Lindholmspiren 5\, Gothenburg\, 417 56\, Sweden
CATEGORIES:Conference
ORGANIZER;CN="Jan Bosch":MAILTO:jan.bosch@chalmers.se
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DTSTART;TZID=Europe/Stockholm:20240610T090000
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SUMMARY:Summer School on Digital Product Management
DESCRIPTION:The summer school on Digital Product Management provides an excellent opportunity for doctoral students and other participants to explore the fundamentals of digital product management and apply product management techniques to a product idea. \nThe central concept that the school is focusing on is how to create a product out of the research results. This involves creating a business model for your idea\, understanding its impact on the intangible economy and its distruptive power. Next\, we focus on identifying the core of the value proposition\, the main requirements and features for your product and how to deliver these features to the potential customers. We put special attention on the customer journey and retention and building sustainable customer relationships. Finally\, we explore the strategies for joining or creating a software ecosystem around your product idea and unlocking the potential of externalities. \nThe summer school will contain lectures\, workshops\, and hands-on activities. \nProgram in brief: \n\n\nMonday – Kick-off meeting  and selection the product idea (about technology transfer between academia and industry) \n\n\nTuesday – Product Strategy\, Product Vision\, and Product Definition – Building the Business Model and Generating the Hypotheses \n\n\nWednesday – Product planning\, Customer Insight\, and Product Requirements Engineering\, Testing the Hypotheses and discovering eliciting requirements \n\n\nThursday – Ecosystem\, Product Sourcing Strategies\, Asset Management and Sourcing  – realizing the idea and planning sustainable growth. Final presentation.
URL:https://www.software-center.se/event/summer-school-dpmw/
LOCATION:Lindholmen Conference Centre\, Lindholmspiren 5\, Gothenburg\, 417 56\, Sweden
CATEGORIES:Conference,Workshop
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BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20240610T100000
DTEND;TZID=Europe/Stockholm:20240610T130000
DTSTAMP:20260524T190927
CREATED:20240409T180442Z
LAST-MODIFIED:20240506T090935Z
UID:6538-1718013600-1718024400@www.software-center.se
SUMMARY:PhD defense: Synergizing Data Management\, DataOps\, and Data Pipelines for AI Enhanced Embedded Systems
DESCRIPTION:Candidate:\n\nAiswarya Raj Munappy\n\nOpponent:\n\nTenured associate professor Xiaofeng Wang\, University of Bolzano\, Italy\n\nCommittee: \n\nProfessor Maria Paasivaara\, LUT University Finland\nProfessor Daniel Varro\, Linköping University\nProfessor Stefan Wagner\, Technical University Munich\n\n\n\n\n\n\n\n\n  \nAbstract:\nContext: Data management is a critical aspect of any artificial intelligence (AI) initiative\, playing a pivotal role in the development\, training\, and deployment of AI models. A well-structured approach to data management ensures that AI models are trained on reliable data\, comply with ethical standards\, and contribute positively to decision-making processes in embedded systems. \nObjectives: This thesis is structured around three primary objectives. The first objective is to comprehensively understand and address the data management challenges associated with embedded systems. Building upon this understanding\, the second objective is to explore the data management practices that can help alleviate the data management challenges. Finally\, the third objective aims to develop and validate the implementation approaches for enhanced data management. \nMethod: To achieve the objectives\, we conducted research in close collaboration with industry and used a combination of different empirical research methods like interpretive case studies\, literature reviews\, and action research. \nResults: This thesis presents six main results. First\, it identifies and categorizes data management challenges\, solutions\, and limitations. Second\, it presents a stairway model delineating the stages of the evolution towards DataOps. Third\, it proposes a model for evaluating the maturity of data pipelines and identifies determinants to assess the impact of machine learning (ML) on data pipelines. Fourth\, it identifies the differences between unidirectional and bidirectional data pipelines and the significance\, benefits\, and challenges of bidirectional data pipelines. The thesis also provides a roadmap for the smooth migration from unidirectional to bidirectional data pipelines. Fifth\, it presents and validates the conceptual model of an end-to-end data pipeline for ML/DL models. It also discusses how to balance the need for robustness with the complexity of the pipeline. Finally\, it presents and validates fault-tolerant data pipelines and an AI-powered 4-stage model for automated fault recovery in data pipelines. \nConclusion: In essence\, this research contributes insights and practical guidance for addressing data management challenges in AI-enhanced embedded systems. The identified challenges\, solutions\, and proposed models pave the way for future research and industry practices\, aiming to streamline data operations\, enhance the reliability of DL models\, and promote efficient data management in evolving technological landscapes of AI-enhanced embedded systems. \n  \nHotels\nAs a participant in the defense and in the Digital Product Management Week you have a discount for the hotels in the list below: \n\nGothia Towers\, Standard room: 1590kr\, use the this link for the conference discount\nRadisson Blu Riverside Hotel:- 15% Code to be used: Corporate account id\, 57072\nComfort Hotel Göteborg: 15%: Code to be used: Chalmers Logi\nClarion Hotel Pier: 15%: Code to be used: Chalmers Logi\nRiverton:  -15%: Code to be used: DPMWEEK
URL:https://www.software-center.se/event/synergizing-data-management/
LOCATION:EDIT Jupiter 473\, Hörselgången 5\, Hörselgången 5\, Gothenburg
CATEGORIES:PhD defense
ORGANIZER;CN="Aiswarya Raj Munappy":MAILTO:aiswarya@chalmers.se
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