The Madrid Institute of Materials Sciences (CSIC-ICMM) hosted the second training workshop for the SPM 4.0 network. Both Prakhar Dutta and Jiacheng Huang, the two doctoral candidates based at the University of Gothenburg, participated to the event along with the other doctoral candidates of the network.
The second training workshop started with presentations from the doctoral candidates on their progress so far. The training event also consisted of a series of lectures on different topics such as a deep dive into atomic force microscopy and the different modes for the same, basics of deep learning, and an overview of data management plans.
ICMM also hosted some practical sessions where hands-on lectures were given on the use of atomic force microscopy machines and their applications.
Author: Prakhar Dutta
Nazli Demirpehlivan visits the Soft Matter Lab
Nazli Demirpehlivan will visit the Soft Matter Lab from 30th of March to 30th of May 2026.
Nazli is a doctoral candidate at Bruker Nano GmbH in Berlin and also a part of the MSCA-DN SPM4.0 network.
She will be carrying out her secondment as part of the SPM 4.0 network with the University of Gothenburg.
The focus of her secondment will be the development of ASAP, a deep learning based pipeline for atomic force microscopy applications alongside the doctoral candidates Prakhar Dutta and Jiacheng Huang who are also part of the network. She will also take the Deep learning course offered by the department to facilitate her PhD studies and projects.
Poster by P. Dutta at the Protein Folding in Real Time Conference, Stockholm, 11th March 2026
Prakhar Dutta, Jiacheng Huang, Nazli Demirpehlivan, Thomas Catley, Sylvia Whittle, Carlo Manzo, Rahul Nagshi, Rachel Owen, Giovanni Volpe
Date: 11th March 2026
Time: 18:00 – 20:00
Place: Aula Medica, Karolinska Institute, Solna
Conference Protein Folding in Real Time, 11-13 March 2026, Stockholm, Sweden
Abstract: Atomic force microscopy (AFM) resolves biological structure and mechanics at high resolution, but produces vast, heterogeneous datasets that are often noisy and very time-consuming to analyse. Although deep learning could automate quality control, segmentation and feature extraction, adoption is limited by scarce ground-truth training data and high technical barriers for experimentalists. Here we present ASAP, an open-source tutorial and pipeline implemented in DeepTrack to provide a reproducible foundation for AI-enabled AFM. At the protein folding conference, a dual-pathway simulation for DNA, offering both molecular dynamics and rapid, non-MD geometries to generate perfect ground truth for segmentation training was presented. By consolidating simulation and learning into a single modular ecosystem, this work enables users to build upon our pipeline to optimize AFM workflows for more efficient data acquisition and robust processing.
MSCA-DN SPM4.0 training event in Berlin, 17-21 November 2025
Charite University and Bruker Nano GmbH hosted the first training workshop for the SPM 4.0 network. Both Prakhar Dutta and Jiacheng Huang, the two doctoral candidates based at the University of Gothenburg, participated to the event along with the other doctoral candidates of the network.
The training event consisted of a series of lectures on different topics such as basics of scanning probe microscopy, medical radiation based elastography, and the basics of machine learning.
Two of the days of the training event were held at Bruker Nano GmbH in Berlin, where hands-on lectures and practicals were given on the use of atomic force microscopy machines and their applications.
Prakhar Dutta joins the Soft Matter Lab
Prakhar has a Master’s degree in Biomedical Engineering from RWTH Aachen University in Germany.
During the course of his PhD, as part of the SPM 4.0 MSCA Doctoral Network he will focus on the development of deep learning based packages for processing of Atomic Force Microscopy data and on the development of a photonic force microscope.