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Quantum researcher take next step towards superconductors
Superconductors can make computers significantly faster and green energy technology even more environmentally friendly. But first, we need a deeper understanding of how superconducting materials actua...
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KTH professor named Frontiers Planet Prize International Champion
Zahra Kalantari, professor in Environmental Science and Engineering at KTH Royal Institute of Technology, has been named international champion of the prestigious Frontiers Planet Prize. Kalantari and...
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Teaching bikes and autonomous cars to talk – with augmented reality
How do you communicate with a vehicle that has no driver? KTH researchers are helping cyclists navigate the traffic of the future — starting in a nuclear reactor.
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- Quantum researcher take next step towards superconductors
17 Jun 2025
- KTH professor named Frontiers Planet Prize International Champion
17 Jun 2025
- Teaching bikes and autonomous cars to talk – with augmented reality
16 Jun 2025
- Aurorae reveal Uranus’s true rotation – with unmatched precision
16 Jun 2025
- AI can help the body heal itself
16 Jun 2025
Researchers’ noticeboard
- Aurorae reveal Uranus’s true rotation – with unmatched precision
16 Jun 2025
- KTH project secures major funding to make climate-neutral cities a reality
16 Jun 2025
- Entrepreneurship scholarship for more effective skin cream
28 May 2025
- Joint lab to find functional materials of the future
27 May 2025
- Award goes toward study of wood-derived lignin for eco-friendly sunscreen
21 May 2025
Calendar
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Public defences of doctoral theses
Thursday 2025-08-21, 14:00
Location: Kollegiesalen, Brinellvägen 6 (Tillgänglighetsanpassad entré), Stockholm
Doctoral student: Akhila Rao , Programvaruteknik och datorsystem, SCS
2025-08-21T14:00:00.000+02:00 2025-08-21T14:00:00.000+02:00 Practical Machine Learning for Predictions in Mobile Networks (Public defences of doctoral theses) Kollegiesalen, Brinellvägen 6 (Tillgänglighetsanpassad entré), Stockholm (KTH, Stockholm, Sweden)Practical Machine Learning for Predictions in Mobile Networks (Public defences of doctoral theses)