Raghav{endra Selvan}

Raghav{endra Selvan}

Assistant Professor (TT) @ Machine Learning Section, University of Copenhagen. ELLIS Member.

Bio

Raghavendra Selvan (Raghav) is a Tenure-Track Assistant Professor at the Machine Learning (ML) Section, Department of Computer Science, University of Copenhagen. His research spans efficient ML, ML for sciences, medical image analysis, and graph neural networks. He holds a PhD from the University of Copenhagen and is affiliated with Pioneer Center for AI (Denmark) and the pan-European AI network ELLIS. Raghav was born in Bangalore, India. RS is the author of the new book “Sustainable AI”.

Book Available Now!

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RS has published Sustainable AI, a book that maps the socio-technical aspects of the interplay between sustainability and AI. Check out the webpage for the book here.

Hiring

If you are interested in joining our team check out the open positions advertised on UCPH Job Portal. Note that, we are not offering online-only opportunities or funded internships from our group. See grants offered by the likes of DDSA for funding opportunities and if it is applicable to you.

News

  • 2026-09: Bakhtiarifard et al., “Characterizing Learning in Deep Neural Networks using Tractable Algorithmic Complexity Analysis” accepted to NeurIPS.
  • 2026-09: Chen & Selvan, “A Discrepancy-Based Perspective on Dataset Condensation” accepted to TMLR with Survey certification.
  • 2026-08: RS has been awarded the HC Ørestad Research Talent Prize for 2026.
  • 2026-07: Johansen et al., “Tackling Real-World Crystal Structure Prediction from Powder X-ray Diffraction Data” accepted to Digital Discovery.
  • 2026-07: RS has been awarded Sapere Aude: DFF Research Leader grant for the new project CITADL
  • 2026-07: Inie et al., “The CO2ST of Agentic AI in Research” accepted to the Nordic Conference on Human-Computer Interaction (NordCHI).
  • 2026-06: RS has an invited comment article at The Lancet Digital Health: Selvan (2026)
  • 2026-05: Bakhtiarifard et al., “Position: Neglecting the Sustainability of AI is fuelling a Global AI Arms Race” accepted to be presented at ICML, 2026.
  • 2026-05: Wilson et al., “Position: Stop Preaching and Start Practising Data Frugality for Responsible Development of AI” accepted to be presented at ICML, 2026.
  • 2026-04: Wilson et al., “How Hyper-Datafication Impacts the Sustainability Costs in Frontier AI” accepted to be presented at ACM FAccT, 2026.
  • 2026-04: Johansen et al., “deCIFer: Crystal Structure Prediction from Powder Diffraction Data using Autoregressive Language Models” accepted to TMLR.
  • 2026-02: Saints Lab is organizing SAINTS’26 on 6 March, 2026. See program and sign up here.
  • 2026-01: Comment article published accepted at Nature Reviews Nephrology.
  • 2025-12: Wenshøj et al., “Oscillations Make Neural Networks Robust to Quantization” accepted to TMLR.
  • 2025-11: Sustainable AI now published, and available online.