Stefano Bo

Lecturer

King’s College London

United Kingdom

Research Interests

Explore related searches

Professors in United Kingdom

Contact this professor

Get a free first email built on one of their papers, ready for you to edit and send yourself.

About

Dr. Stefano Bo is a Lecturer at King's College London, UK. His research focuses on stochastic dynamics, deep learning applications in microscopy, and transport phenomena in complex fluids. Recent articles by Dr. Bo include studies on recurrent neural networks, active viscoelastic fluids, and the mechanics of phase boundaries.

Articles (13)

Year:

2025

Year:

2025

Year:

2025

Year:

2024

Year:

2023

Year:

2023

Year:

2022

Year:

2021

Year:

2021

Year:

2021

Year:

2021

Year:

2020

Year:

2020

Collaborators (6)

Carlo Manzo

Associate Professor

University of Vic

SPAIN

View details

Lars Hubatsch

Max Planck Institute of Molecular Cell Biology and Genetics

GERMANY

View details

Piotr Surowka

University of Wrocław

POLAND

View details

Janusz Szwabiński

University of Wrocław

POLAND

View details

Charlie Duclut

Lecturer

Institut Curie

FRANCE

View details

Giorgio Volpe

Professor of Soft Matter

University College London

UNITED KINGDOM

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Stefano Bo

Research Interests

Explore related searches

Contact this professor

About

Articles (13)

Recurrent neural network analysis of single trajectories switching between anomalous diffusion states

Transport kinetics across interfaces between coexisting liquid phases

Stochastic cloaking: Concealing a region from diffusive particles

Probe particles in odd active viscoelastic fluids: How activity and dissipation determine linear stability

Lift force in odd compressible fluids

Roadmap on Deep Learning for Microscopy

Passive odd viscoelasticity

Objective comparison of methods to decode anomalous diffusion

Stochastic dynamics of single molecules across phase boundaries

Quantitative theory for the diffusive dynamics of liquid condensates

Classification, inference and segmentation of anomalous diffusion with recurrent neural networks

Enhanced force-field calibration via machine learning

Power-law population heterogeneity governs epidemic waves

Collaborators (6)

Carlo Manzo

Lars Hubatsch

Piotr Surowka

Janusz Szwabiński

Charlie Duclut

Giorgio Volpe

Make your next move.