2021-04206 – PhD Position F/M : Designing passive hybrid Brain-Computer Interfaces to estimate User eXperience in virtual galleries

Telence      ·       Full time      ·        Fixed-term

Contract type : Fixed-term contract
Level of qualifications required : Graduate degree or equivalent
Fonction : PhD Position

About the research centre or Inria department

Potioc designs, develops and evaluates new approaches that exploit multimodal interaction to promote a stimulating user experience. In particular, we explore approaches based on mixed reality (AR, RV), tangible interaction, brain-computer interfaces, and physiological interfaces. The main areas of application we are targeting are education, well-being, art, and accessibility.

Context

The hired PhD student will join European project BITSCOPE (2022-2024) – a CHIST-ERA type project which stands for “Brain Integrated Tagging for Socially Curated Online Personalised Experiences”. This is a project led by Pr. Tomas Ward (from Dublin City University, Ireland), in collaboration with France (Inria Bordeaux Sud-Ouest, team Potioc), Spain (Universitat Politècnica de Valencia) and Poland (Nicolas Copernicus University). The BITSCOPE project presents a vision for brain computer interfaces (BCI) which can enhance social relationships in the context of sharing virtual experiences. We envisage a future in which attention, memorability and curiosity elicited in virtual worlds will be measured without the requirement of “likes” and other explicit forms of feedback. Instead, users of our improved BCI technology can explore online experiences leaving behind an invisible trail of neural data-derived signatures of interest. This data, passively collected without interrupting the user, and refined in quality through machine learning, can be used by standard social sharing algorithms such as recommender systems to create better experiences. Technically the work concerns the development of a passive hybrid BCI (phBCI). It is hybrid because it augments electroencephalography (EEG) with eye tracking data, galvanic skin response (GSR), heart rate (HR) and movement in order to better estimate the mental state of the user. It is passive because it operates covertly without distracting the user from their immersion in their online experience and uses this information to adapt the application. It represents a significant improvement in BCI due to the emphasis on improved denoising facilitating operation in home environments and the development of robust classifiers capable of taking inter- and intra-subject variations into account. We leverage our preliminary work in the use of deep learning and geometrical approaches to achieve this improvement in signal quality. The user state classification problem is ambitiously advanced to include recognition of attention, curiosity, and memorability which we will address through advanced machine learning, Riemannian approaches and the collection of large representative datasets in co-designed user centred experiments.

Assignment

As part of this research, the goal of this PhD thesis would be to design the passive hybrid BCI which can be used to create a metric which relates to Users’ eXperience (UX), such as attention, memorability and curiosity with a given artwork. This PhD work will involve protocol design, data collection and experiments in which explicit measures of UX, e.g., self-report will be collected to support supervised learning approaches. Then it will involve the design of machine learning algorithms to estimate such UX (e.g., attention or curiosity levels) from both EEG and physiological signals (e.g., GSR and HR). Finally, it will involve designing an online phBCI to estimate online such states when users are viewing various artworks.

Main activities

It is envisioned that the PhD work will have to solve the following tasks:

• Designing a controlled protocol to manipulate UX in a virtual exhibition
• Collecting data with such a controlled UX protocol
• Designing participant specific EEG-based UX classifiers
• Designing participant specific physiology-based UX classifiers
• Building a Multimodal participant specific UX classifier
• Building a Multimodal generic UX classifier
• Evaluation and optimization of the proposed UX-BCI classifier in ecological conditions

Skills

• EEG signal processing (temporal/spatial filtering, subspace identification, source reconstruction, etc)
• Machine Learning & Pattern Recognition for EEG classification
• Python / Matlab programming
• Skills in rigorous protocol design and running, including data collection
• Able to speak, write and work in an English speaking environment
• Experience with ElectroEncephaloGraphy (EEG) and/or BCI experiments is a strong plus
• Experience and/or skills in cognitive science (in particular psychology and/neuroscience) is a strong plus

Benefits package

• Subsidized meals
• Partial reimbursement of public transport costs
• Possibility of teleworking and flexible organization of working hours
• Professional equipment available (videoconferencing, loan of computer equipment, etc.)
• Social, cultural and sports events and activities
• Access to vocational training
• Social security coverage

Remuneration

• 1982€ / month (before taxs) during the first 2 years, 2085€ / month (before taxs) during the third year.

General Information

Theme/Domain : Interaction and visualization
Instrumentation et expérimentation (BAP C)
Town/city : Talence
Inria Center : CRI Bordeaux – Sud-Ouest
Starting date : 2022-01-01
Duration of contract : 3 years
Deadline to apply : 2021-11-26

Contacts

Inria Team : POTIOC
Recruiter : Lotte Fabien / Fabien.Lotte@inria.fr

The keys to success

There you can provide a “broad outline” of the collaborator you are looking for what you consider to be necessary and sufficient, and which may combine :

• tastes and appetencies,
• area of excellence,
• personality or character traits,
• cross-disciplinary knowledge and expertise…

This section enables the more formal list of skills to be completed and ‘lightened’ (reduced) :

• “Essential qualities in order to fulfil this assignment are feeling at ease in an environment of scientific dynamics and wanting to learn and listen.”
• ” Passionate about innovation, with expertise in Ruby on Rails development and strong influencing skills. A thesis in the field of **** is a real asset.”

About Inria

Inria is the French national research institute dedicated to digital science and technology. It employs 2,600 people. Its 200 agile project teams, generally run jointly with academic partners, include more than 3,500 scientists and engineers working to meet the challenges of digital technology, often at the interface with other disciplines. The Institute also employs numerous talents in over forty different professions. 900 research support staff contribute to the preparation and development of scientific and entrepreneurial projects that have a worldwide impact.

Instruction to apply

• CV
• Cover letter
• Master degree

Defence Security :

This position is likely to be situated in a restricted area (ZRR), as defined in Decree No. 2011-1425 relating to the protection of national scientific and technical potential (PPST).Authorisation to enter an area is granted by the director of the unit, following a favourable Ministerial decision, as defined in the decree of 3 July 2012 relating to the PPST. An unfavourable Ministerial decision in respect of a position situated in a ZRR would result in the cancellation of the appointment.

Recruitment Policy :

As part of its diversity policy, all Inria positions are accessible to people with disabilities.