The Vertically Integrated Projects (VIP) program unites undergraduate education and faculty research in a team-based context. As a VIP student you earn academic credits, while working in a VIP-team connected to a research project.

About Vertically Integrated Projects (VIP)

VIP provide a multi-year, multidisciplinary approach to learning that is project-based, innovative, and research-active.  It is an opportunity for you to practice professional skills while making real-world contributions in a research context. You will be working with researchers and students from all levels of study. 

Vertically Integrated Projects (VIP) are:

  • Ambitious: Embedded in faculty scholarship and exploration
  • Collaborative: Enabled by vertical integration of teams
  • Large-scale: Teams can have dozens of students
  • Long-term: They span semesters, even years
  • Multidisciplinary: Students from many different programs participate

Courses

VIP: Research integrated development project, basic course

VIP: Research integrated development project, continuing course

Our current VIP teams

VIP teams starting in the autumn semester 2019:

Hybrid Games

Goals

This team will explore and assess hybrid games by designing, implementing and testing them on full scale games.

Hybrid games are created by mixing real-life and online elements and mechanics. Online access allows us to design, among other things, information dissemination across large spaces as well as intelligent and interactive game elements. Real-life elements let users establish traditional and powerful modes of engagement as well as introduce non-designed aspects in a game.

We are agnostic as regards to the kinds of games we design; we will design, implement and test at least one new game per year.

Research, design or technical issues involved or addressed

The team will research different aspects of game design and implementation.

Design: Based on existing research, and through an analysis of our own and others’ hybrid games, we seek to create a hierarchical dictionary of basic components.

Implement and evaluate: Develop games and integrated assessment methods in parallel, so as to assess the game’s impact (in terms of, for instance, engagement with the game, learning outcomes).

Methods, technology and approaches

Methods: outcome assessments (interviews, questionnaires, observation), data visualisation

Technologies: Database Design (relational, non-relational), responsive web app design and development (HTML, CSS, Javascript), Game Design, Artificial Intelligence/Machine Learning, Physical Objects Design and Production, Media Production, AR

Approach: event design and implementation

Student’s knowledge and areas of interest

  • computational science and engineering
  • human-computer interaction
  • game design, passion for games, story-telling
  • graphic and web design
  • event design and implementation
  • physical objects design and production
  • media production (music, photography, film, virtual and augmented reality)

Partners:
Data Society (MAU), Computational Media Lab (Media Technology, MAU)

Instructors:

Erik Pineiro and Johannes Karlsson

Contact:

Erik Pineiro 

Machine Intelligence

Goals 

To develop innovative solutions for real-world application domains, building upon the state-of-the-art available technologies in machine learning and artificial intelligence, coupled with our novel research ideas and hypothesis, towards addressing important societal challenges.

Research, design or technical issues involved or addressed

The team will tackle problems where the research and development of smart autonomous systems can play a key role with respect to today’s societal challenges and overall human well-being. The scope of research topics includes AI sub-areas such as (but not limited to):

  • image and video processing
  • visual scene analysis and interpretation      
  • audio/speech/natural language processing
  • activity recognition
  • recommender systems
  • deep reinforcement learning and planning      
  • deep neural networks
  • multi-agent (systems) learning
  • block-chain technologies

Methods, technology and approaches

The work carried out within the Machine Intelligence team has a strong focus on data science methods and practices, as well as hands-on experience with tools for data analysis and visualisation.

Projects are mainly focussed on software development based on existing open source frameworks (cloud computing platforms, such as AWS; big data frameworks, such as Spark, Google Colab), as well as potentially deploying solutions for embedded systems when needed (for example, using RaspberryPi). Existing AXIS camera setups in MAH (IOTAP lab and Library) will be made available to students, as well as other hardware components that may be required.

Resulting work will be properly documented and persisted for further development and demonstration purposes as part of the course report. Students having completed a project with the Machine Intelligence team under the VIP course, are encouraged to continue development of those projects as their final thesis project.

Student’s knowledge and areas of interest

  • experience with or willingness to learn machine learning, artificial intelligence and data analytics concepts and methods
  • experience with or willingness to get familiar with key programming tools and frameworks for ML/AI development

Partners

Preliminary: AXIS, Apptus, Sigma Technology (potentially)

Academic projects: DISS-project, ECOS-project

Instructor 

Radu Mihailescu

Contact

Radu Mihailescu

 

Smart Campus

Goals

  • support people getting to places by potentially influencing equipment, such as the elevators
  • support finding colleagues/lecturers/staff and most suitable study/work place for current task
  • understand usage, for example, for replanning/rebuilding
  • optimise usage, facility maintenance and cleaning
  • monitor number of people per floor for safety/evacuation purposes
  • virtually bring the campus together (many buildings at different locations)
  • smart meeting rooms, such as, equipment configuration and control
  • let personal/group preferences influence actuation of devices, for example, lights, window blinds, temperature, and ventilation

Research, design or technical issues involved or addressed

Smart Campus team members will propose projects in:

  • smart education
  • smart building
  • IoT flipped classroom
  • smart parking 
  • Smart transport - to and from and within Campus
  • IoT orangery
  • building control, for example, shades and ventilation

Projects include hardware and software development, app development, prototyping, proof of concept, problem solving, and service development by applying approaches and methods in:

  • machine learning
  • agent-based learning
  • optimisation and simulation system
  • sensors, sensor networks
  • interaction technology
  • communications

Methods, technology and approaches

The methods, technologies, and approaches will be discussed between the students and instructors of each project at the early stages.

The hardware components required for a project on Smart Campus will be provided to the students, this includes, development boards such as ESP boards or Arduino, various sensors, wireless communication technologies such as ZigBee, Bluetooth/BLE, nrf modules.

It is also required that all data captured during different phases of project, programming codes, algorithms be stored in a network drive to keep all the files available for future uses, demonstration, and development.

The team of students completed a project on the Smart Campus under the VIP course are encouraged to continue development of those projects as their final thesis project.

Student’s knowledge and Areas of Interest

A team of students working on a particular project in the Smart Campus needs to have knowledge, understanding and experience in smaller project/s with a focus on one or more of the following research areas and show creativity in solving problems:

  • IoT
  • machine learning
  • agent-based learning
  • optimisation and simulation system
  • sensors and sensor networks
  • interaction technology
  • mobile app development
  • communications

Partners

Preliminary industry partners: Sigma connectivity and Axis and academically IoTaP-subproject DISS.

Instructors

Reza Malekian, Jan Persson, Radu-Casian Mihailescu, Simon Siggelsten

Contact

Reza Malekian

How can I be part of a VIP-team?

  1. Apply to the VIP course that suits your level of study experience, dependent on the credits you have. For the spring semester 2020, all new students apply to the course VIP: Research Integrated Development Project. Students who continue from the autumn semester 2019, apply to the continuing course VIP: Research Integrated Development Project, continuing course
  2. Choose a VIP-team that you would like to be part of. Email the team instructor and Maria Engberg with the following information: 
    • What do you study now?
    • In a few sentences, tell us why you have chosen this team and what you think you can contribute.
  3. Come to the introduction meeting about VIP. You will receive more information about the meeting when you are accepted to the VIP course.
  4. Participate in VIP courses/VIP teams for several semesters in a row.

For more information about the VIP-programme, please contact Maria Engberg.