Davide Michieletto

Davide Michieletto is a Research Fellow at the University of Edinburgh, affiliated with the Institute of Genetics and Molecular Medicine (IGMM). His work focuses on topological problems in soft matter and biology, particularly DNA topology, genome organization, and DNA-based soft materials.

• Education: BSc and MSc in Physics (University of Padova, Italy), PhD in Physics and Complexity Science (University of Warwick, UK)
• Awards: 2024 Leverhulme Prize in Physics, 2024 Louise Johnson Early Career Award, 2021 RSC Early Career Award, 2020 Royal Society University Research Fellowship, 2019 Leverhulme Early Career Fellowship, 2015 Ian Macmillan Ward Prize

The TAPLab (Topologically Active Polymers) explores how topological and mechanical control of DNA can inspire new smart materials. Recent work includes:

• Machine learning approaches to identify knots in polymers (Physics World 2024)
• DNA nanostar gels with tunable elasticity (Nature Materials 2025)
• Topological analysis of kinetoplast DNA (NAR 2025)
• DNA origami rheology studies (Soft Matter 2024)

His research bridges polymer physics, biophysics, and machine learning to address fundamental questions in genome organization and material science. Key publications span non-equilibrium dynamics, viscoelastic condensates, and DNA topology in extreme conditions.

Scientific Awards include:

• 2024: Leverhulme Prize in Physics
• 2024: Louise Johnson Early Career Award (British Biophysical Society)
• 2021: Early Career Award in Statistical Mechanics (Royal Society of Chemistry)
• 2020: Chancellor's Rising Star Award (Edinburgh)

As an adviser, Davide mentors PhD students like Giorgia Palombo (hybrid DNA hydrogels), Yair Fosado (multi-scale DNA modeling), and Djordje Mihajlovic (machine learning for knots). He supports funding opportunities including Wellcome Trust, Marie Sklodowska-Curie, and ERC Starting Grants.

The TAPLab team includes postdocs (Cleis Battaglia, Simon Weir, Yair Fosado, Saminathan Ramakrishnan), PhD students (Amandine Hong-Minh, Giorgia Palombo, Jenny Harnett, Dinesh Parthasarathy, Djordje Mihajlovic, Filippo Conforto, Emma Tomlinson), and SOFI PhD candidates (Ella Sapsford, Jenny Harnett). Recent work involves collaborations with IGMM and ESRIC for high-resolution AFM imaging.