ai4st.github.io/tracks.html at main · ai4st/ai4st.github.io · GitHub

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    <title>Tracks | AI4ST Bicocca</title>
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      <h1 class="title">Specialization Tracks</h1>
      <h2 class="subtitle">which track to choose?</h2>
      <a href="/" class="button back-button">&lt; back</a>
      [2022/11/17]:
      <a
        target="_blank"
        href="https://elearning.unimib.it/course/view.php?id=47428"
      >
        Videorecording and documentation of the meeting on the study plan.
      </a>
      <h3 class="track-title button">
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        Track 1: Industrial and Environmental Applications
      </h3>
      <div class="track-content hide">
        <p>
          Focus on <strong>monitoring, control and automation</strong> of
          manufacturing processes, for ensuring product quality levels, and for
          environmental monitoring and support to the management of that same
          environment.
        </p>
        <p>
          Students will be able to use artificial intelligence specifically for:
        </p>
        <ul>
          <li>Analysis of industrial and environmental data.</li>
          <li>
            <strong>Extraction of information</strong> and knowledge regarding
            the <strong>quality and characteristics of products</strong>.
          </li>
          <li>
            <strong>Analysis of signals and images</strong> in a manufacturing
            and environmental context.
          </li>
          <li>
            Management of industrial or environmental
            <strong>production processes</strong>.
          </li>
          <li>
            Management of <strong>smart and adaptive environments</strong> (e.g.
            smart buildings, smart cities, smart infrastructures).
          </li>
          <li>
            Management of manufacturing processes and smart environments in
            support of sustainability.
          </li>
        </ul>
      </div>
      <h3 class="track-title button">
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        Track 2: Embedded Systems
      </h3>
      <div class="track-content hide">
        <p>
          Focus on smart embedded systems for various areas of application,
          including
          <strong>
            consumer electronics, medical devices and systems, prosthetics,
            motor vehicles and transport</strong
          >. Students will gain a specialised understanding in the use of
          artificial intelligence to develop intelligent adaptive behaviours,
          and cultivating
          <strong>organic interactions between humans and machines</strong>.
        </p>
        <p>
          Students will be able to use artificial intelligence specifically for:
        </p>
        <ul>
          <li>
            Analysis of data coming from
            <strong>sensors and human-system interfaces</strong>.
          </li>
          <li>
            Extraction of information and knowledge regarding the
            <strong>
              behaviour of the embedded system and the environment in which it
              operates</strong
            >.
          </li>
          <li>
            Extraction of information and knowledge from user interactions.
          </li>
          <li>
            <strong>Analysis of signals and images</strong> in smart embedded
            systems.
          </li>
          <li>
            Decision-making support in the corresponding areas of application.
          </li>
        </ul>
      </div>
      <h3 class="track-title button">
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        Track 3: Signal/Image Processing for Healthcare and Environment
      </h3>
      <div class="track-content hide">
        <p>
          Focus on collecting and analysing <strong>multi-sensor data</strong>,
          both in the field of
          <strong>
            environmental monitoring through observations of the Earth
          </strong>
          and sensor networks, as well as in the healthcare arena, providing
          <strong>
            decision-making support through the analysis of biomedical images
            and signals</strong
          >.
        </p>
        <p>
          Students will be able to use artificial intelligence specifically for:
        </p>
        <ul>
          <li><strong>Multi-sensor</strong> management.</li>
          <li>
            Collecting and processing of signals and images, with specific
            <strong>care about the physical phenomena</strong> and the physical
            meaning of the data.
          </li>
          <li>
            <strong>Extraction of information</strong> and knowledge about the
            <strong> state of the environment and its evolution</strong>.
          </li>
          <li>
            Extraction of information and knowledge about the
            <strong>health of patients</strong>.
          </li>
          <li><strong>Medical diagnostic devices</strong>.</li>
          <li>Tools for <strong>environmental observation</strong>.</li>
          <li>
            Decision-making support in the corresponding application areas.
          </li>
        </ul>
      </div>
      <h3 class="track-title button">
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        Track 4: Complex Systems and Quantum Technologies
      </h3>
      <div class="track-content hide">
        <p>
          Focus on
          <strong>
            identification, modelling, and analysis of complex physical systems
          </strong>
          (including quantum systems) as well as for the
          <strong>processing of information using quantum techniques</strong>.
        </p>
        <p>
          Students will be able to use artificial intelligence specifically for:
        </p>
        <ul>
          <li>
            <strong>Analysis of data and knowledge</strong> for modelling
            complex systems.
          </li>
          <li>
            <strong>Extraction of characteristic behaviours</strong> of complex
            systems.
          </li>
          <li>
            <strong>Simulation of the behaviour</strong> of complex systems.
          </li>
          <li>
            Design and
            <strong>
              development of quantum algorithms to support artificial
              intelligence</strong
            >.
          </li>
        </ul>
      </div>
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