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Roy Saurabh

AI governance · HCI · Privacy-preserving systems

Roy Saurabh

I research how AI systems can remain useful, accountable and human-centred when they move from models into real institutions.

My work spans AI assurance, privacy-preserving machine learning, human-computer interaction and the data governance of learning systems, across research, international policy and deployed software.

Incoming Postdoctoral Researcher, Umeå University, Department of Computing Science · from

Founder, AffectLog

Previously UNESCO, 2021-2025

Context

Across research, policy and implementation

  • UNICEF Innocenti

    Current

    Expert advisory group · children's data governance

  • JA Institute

    Current

    Advisor · Research Advisory Council

  • Umeå University

    from September 2026 · incoming

    Postdoctoral research · computing science

  • AffectLog

    2025-

    Founder · AI assurance research and tooling

  • UNESCO

    2021-2025

    2018-2025 · teacher development, digital learning and data governance

The through-line

Research, governance and systems are one problem

Most of my work sits in the movement between these three, rather than inside any one of them. A finding that institutions cannot act on, and a requirement no system can implement, both fail in the same way.

  1. Research

    What can we know?

  2. Governance

    What evidence and safeguards should institutions require?

  3. Systems

    How do those requirements become operational?

Current research

Four questions I am working on

Claims about an AI system should be checkable by someone who was not involved in building it.

What evidence about an AI system is adequate for a particular decision, held by a particular role, in a particular deployment?

  • AI assurance
  • Regulation
  • Reproducibility

Institutions that cannot pool sensitive data can still learn together, if the governance is built alongside the method.

What has to hold, technically and institutionally, for federated analysis across sensitive datasets to be trustworthy rather than merely decentralised?

  • Federated learning
  • Privacy
  • AI assurance

Systems that adapt to people need to be honest about how little they know about the person in front of them.

How can adaptive and affect-aware systems support learning and wellbeing without overreading sparse, intimate signals?

  • HCI
  • Learning sciences
  • Mental health

The governance of education and children's data decides what the technology is allowed to become.

How should public institutions govern data about people who cannot meaningfully consent, and what does that require of the systems built on it?

  • Data governance
  • Children's data
  • Education

Selected work

Selected work, with the evidence attached

Six items, each linked to the institution, registry or document that supports it.

Policy2025Author

Federated learning for children's data: encoding trust in education systems

Argues that governments can use sensitive education data without centralising it, and what governance that requires.

UNICEF Innocenti, Office of Strategy and Evidence

Publications2024Author

Data preprocessing and machine learning in wearable data analysis: assessing efficacy and challenges for mental health monitoring of healthcare professionals

Doctoral research on what wearable sensor data can and cannot support when the question is clinical risk.

Université Paris Cité

Reports2023Writing team

The Transformative Potential of Data for Learning

Broadband Commission working-group report on the governance of education data, written by the UNESCO team supporting the group.

Broadband Commission for Sustainable Development, ITU/UNESCO

Policy & advisory

Where the research meets institutional decisions

Advisory roles are advisory roles. None of these is employment at the institution named, and each links to the institution's own record of it.

Expert advisory groupCurrent

UNICEF Innocenti

Office of Strategy and Evidence

Expert advisory group member, Good governance of children's data

One of around twenty members advising the second phase of UNICEF Innocenti's children's data governance project, which covers data governance in education technology, a fair data economy for children, and innovations in data governance.

Publications

Scholarly publications

2019

The Alternate Education for the 21st Century

2019 IEEE 18th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)

Early work connecting cognitive science and socio-emotional learning to digital pedagogy.

PublicationsCo-author

All publications

Software

Research software

All research software

Trajectory

How the question changed

Read as a career this looks like several. Read as a line of enquiry it is one, moving steadily closer to the institutions where these systems actually land.

  1. 2005-2014

    Systems

    Large systems, and what they do to the people inside them

    Enterprise systems engineering and then consulting. The work was implementation, at a scale where a technical decision becomes an organisational fact.

  2. 2014-2018

    Systems

    Education infrastructure at national scale

    Founding and technology leadership across skills and education platforms, including national skill-development programme technology. First sustained exposure to public-sector digital delivery.

  3. 2018-2020

    Systems

    From delivering platforms to asking what learning needs

    Chief Technology Officer at UNESCO MGIEP, building learning technology with machine learning and socio-emotional learning at its centre. The question shifted from whether a system could be built to what it should be modelling.

  4. 2020-2021

    Research

    Machine learning from sensitive human data

    Lead data scientist at the Centre de Recherches Interdisciplinaires. Working directly on intimate data made the privacy constraints a research problem rather than a compliance step.

  5. 2021-2025

    Governance

    How evidence travels into policy, and what is lost on the way

    Senior Project Officer in UNESCO's Section for Teacher Development: teacher development, digital learning platforms and education data governance, including the UNESCO writing team for the Broadband Commission's data for learning reports.

  6. 2024

    Research

    Doctorate defended

    PhD in mathematics and computer science at Université Paris Cité, on machine learning from wearable data for mental-health monitoring of healthcare professionals.

  7. 2025-

    Governance

    Making assurance evidence auditable

    Founding AffectLog, and building reproducible tools for AI assurance. Advisory work with UNICEF Innocenti on children's data governance keeps the research attached to a population that bears the cost when governance fails.

  8. 2026-

    Research

    Adaptive interventions and lifelong learning

    Postdoctoral research at the Department of Computing Science, Umeå University, from September 2026.

Selected talks and public engagement

Invited lecture10 April 2025

Integrating Federated Learning with Data Governance Frameworks for Collaborative and Secure Analysis of Sensitive Data

CITIC, Universidade da Coruña · A Coruña, Spain

On handling sensitive data in health and education: where federated approaches help, and what governance has to be in place for them to mean anything.

Notes and essays

Research, collaboration and invited discussions

I am glad to hear from researchers, institutions and policy teams working on the same problems.

roy@affectlog.com

Contact details

Particularly interested in

Academic collaboration
Joint research on AI assurance, federated methods, or data governance.
Policy and standards work
Advisory groups, evidence reviews, and institutional capacity work.
Invited talks and teaching
Lectures, seminars, panels and doctoral training.
Research partnerships
Programme consortia and partnerships involving assurance or privacy-preserving analysis.