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Fundamental Sciences Presentation of the Knovel AI and Engineering Village AI tools

Presentation of the Knovel AI and Engineering Village AI tools

2025-10-22 15:00
Microsoft Teams

On October 22 (Wednesday) at 3:00 p.m., we invite you to a presentation of the Knovel AI and Engineering Village AI tools on trial, intended for students, researchers, lecturers, and practitioners.
 
Elsevier representative Marta Bracha will demonstrate how, by using specialized search platforms powered by reliable engineering content and AI-driven search capabilities, you can learn to conduct an effective literature review, find citable references, retrieve the data you need, map out material properties, and make use of essential equations and graphs.
 
Microsoft Teams
Join the meeting now
Meeting ID: 242 907 268 290 5
Passcode: Qo6Sw6x4
 
Engineering and technology platform Knovel and Knovel AI (until 2025 11 20)
 
Knovel is an engineering and technology platform that provides access to a wide range of technical data, books, articles, handbooks, data tables and other valuable information.
The platform is useful for anyone working in engineering design, manufacturing, research or other technology fields, as well as those looking for solutions to specific engineering problems.
 
In addition to comprehensive content, Knovel also offers interactive analysis tools for solving technical problems: interactive calculators, equations, graphs, data processing programs, tables, diagrams, technical references and databases. These tools help engineers find, analyze and apply the necessary information in practical activities faster.
 
Knovel AI is a new artificial intelligence feature that further enhances literature search and helps you find information faster. It provides reliable, citation-worthy insights derived only from carefully selected and vetted Knovel engineering content.
 
Unlike traditional keyword searches, Knovel, powered by artificial intelligence, understands the context of a question, finding and summarizing the most important results from full-text technical sources, including design guides, conference proceedings, and databases. 
 
Compendex on Engineering Village and Engineering Village AI (until 2025 11 20)
 
Engineering Village (EV) is a specialized engineering information search and analysis platform, designed specifically for the engineering community - students, researchers, teachers and practitioners.
 
EV provides access to a wide range of international sources covering various engineering fields: mechanical, chemical, civil, electrical, environmental, materials, computer engineering, etc.
 
The platform provides:
  • scientific articles;
  • conference proceedings;
  • dissertations;
  • technical documents, standards;
  • patents.
EV offers powerful filters and search operators that allow you to accurately find the necessary information by author, publication type, topic, words in the abstract or even engineering terms. This allows scientists and students to save a lot of time when searching for relevant sources for a specific problem or project.
 
EV provides tools for analyzing search results - you can monitor the dynamics of publications, main topics, authors, institutions or geographical trends. This is useful for research planning or literature reviews.
 
The platform helps both students writing term papers or final theses, and researchers preparing publications or projects, by allowing them to quickly find reliable, high-quality and scientifically valuable sources.
 
Engineering Village AI is a generative artificial intelligence tool built on Compendex, one of the largest and most comprehensive engineering bibliographic databases in the world. With the help of this tool, engineering researchers can effectively discover and synthesize interdisciplinary knowledge and insights.
 
Access is available from VILNIUS TECH computer network or via VPN. As a security measure, two-factor authentication is additionally required (i.e. verification from mobile device app or by call).
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    • Emilija Blaškevič
    • Ernestas Čepulionis
    • Karolina Kardokaitė
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Faculty of Fundamental Sciences
Faculty of Fundamental Sciences
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