Soft Matter Lab

Fredrik Skärberg defended his PhD thesis on January 29th, 2026. Congrats!

Cover of the PhD thesis. *(Image by F. Skärberg)*

Fredrik Skärberg defended his PhD thesis on January 29th, 2026. Congrats!
The defense took place in FB, Institutionen för fysik, Origovägen 6b, Göteborg, at 09:00.

Title: From Light to Data Using Deep Learning for Quantitative Microscopy

Abstract: Quantitative microscopy aims to measure physical properties of microscopic particles from optical images, but weak and complex signals often make this difficult. This thesis explores how computational methods, especially deep learning guided by physical understanding, can improve particle detection and characterization in microscopy.
The work introduces new approaches for locating and tracking particles, extends these ideas to three-dimensional and label-free imaging, and reviews practical analysis workflows. It further shows how combining complementary imaging techniques can enhance nanoparticle measurements and how deep learning can recover three-dimensional structural information from microscopy images.
Overall, this thesis strengthens the connection between optical measurements and quantitative particle information, expanding the potential of label-free microscopy for biological and nanoscale studies.

Thesis: https://gupea.ub.gu.se/handle/2077/90201

Supervisor: Daniel Midtvedt
Examiner: Raimund Feifel
Opponent: Arrate Munoz Barrutia
Committee: Per Augustsson, Jens Petersen, Rebecka Jörnsten
Alternate board member: Vitali Zhaunerchyk

Roadmap on Deep Learning for Microscopy published in Journal of Physics: Photonics

Spatio-temporal spectrum diagram of microscopy techniques and their applications. *(Image by the Authors of the manuscript.)*

Roadmap on Deep Learning for Microscopy
Giovanni Volpe, Carolina Wählby, Lei Tian, Michael Hecht, Artur Yakimovich, Kristina Monakhova, Laura Waller, Ivo F. Sbalzarini, Christopher A. Metzler, Mingyang Xie, Kevin Zhang, Isaac C.D. Lenton, Halina Rubinsztein-Dunlop, Daniel Brunner, Bijie Bai, Aydogan Ozcan, Daniel Midtvedt, Hao Wang, Nataša Sladoje, Joakim Lindblad, Jason T. Smith, Marien Ochoa, Margarida Barroso, Xavier Intes, Tong Qiu, Li-Yu Yu, Sixian You, Yongtao Liu, Maxim A. Ziatdinov, Sergei V. Kalinin, Arlo Sheridan, Uri Manor, Elias Nehme, Ofri Goldenberg, Yoav Shechtman, Henrik K. Moberg, Christoph Langhammer, Barbora Špačková, Saga Helgadottir, Benjamin Midtvedt, Aykut Argun, Tobias Thalheim, Frank Cichos, Stefano Bo, Lars Hubatsch, Jesus Pineda, Carlo Manzo, Harshith Bachimanchi, Erik Selander, Antoni Homs-Corbera, Martin Fränzl, Kevin de Haan, Yair Rivenson, Zofia Korczak, Caroline Beck Adiels, Mite Mijalkov, Dániel Veréb, Yu-Wei Chang, Joana B. Pereira, Damian Matuszewski, Gustaf Kylberg, Ida-Maria Sintorn, Juan C. Caicedo, Beth A Cimini, Muyinatu A. Lediju Bell, Bruno M. Saraiva, Guillaume Jacquemet, Ricardo Henriques, Wei Ouyang, Trang Le, Estibaliz Gómez-de-Mariscal, Daniel Sage, Arrate Muñoz-Barrutia, Ebba Josefson Lindqvist, Johanna Bergman
Journal of Physics: Photonics 8, 012501 (2026)
arXiv: 2303.03793
doi: 10.1088/2515-7647/ae0fd1

Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasing resolution and throughput. Artificial intelligence, deep neural networks, and machine learning (ML) are all niche terms describing computational methods that have gained a pivotal role in microscopy-based research over the past decade. This Roadmap encompasses key aspects of how ML is applied to microscopy image data, with the aim of gaining scientific knowledge by improved image quality, automated detection, segmentation, classification and tracking of objects, and efficient merging of information from multiple imaging modalities. We aim to give the reader an overview of the key developments and an understanding of possibilities and limitations of ML for microscopy. It will be of interest to a wide cross-disciplinary audience in the physical sciences and life sciences.

Berenice García will defend her PhD thesis on January 28th, 2026. Congrats!

Cover of the PhD thesis. *(Image by B. García)*

Berenice García defended her PhD thesis on January 28th, 2026. Congrats!
The defense took place in PJ, Institutionen för fysik, Origovägen 6b, Göteborg, at 09:00.

Title: Quantitative Optical Microscopy of Microscale Soft Matter Systems

Abstract: Many biological and soft-matter particles operate at sizes below the diffraction limit and scatter light only weakly, making them hard to study with conventional microscopy. This thesis introduces two complementary, label-free interferometric methods that enable single-particle characterization across the meso–microscale. By combining optical scattering, off-axis holography, and particle tracking, these approaches quantify size, refractive index, internal structure, and mobility of individual rigid nanoparticles and soft biomolecular condensates. Together, this work provides new tools for probing the physical principles of nanoscale soft matter and phase-separated biological assemblies.

Thesis: https://hdl.handle.net/2077/90110

Supervisor: Daniel Midtvedt
Examiner: Bernhard Mehlig
Opponent: Balpreet Singh Ahluwalia
Committee: Per Augustsson, Arrate Muñoz Barrutia, Alexandra Stubelius
Alternate board member: Kristian Gustafsson

Yu-Wei Chang defended his PhD thesis on January 23rd, 2026. Congrats!

Cover of the PhD thesis. *(Image by Hula King, https://www.behance.net/hulaking)*

Yu-Wei Chang defended his PhD thesis on January 23rd, 2026. Congrats!
The defense will take place in SB-H7 lecture hall, SB-Building, Institutionen för fysik, Johanneberg Campus, Göteborg, at 13:00.

Title: A Unified Software-Generating Framework for Biological Data Analysis

Abstract: Biological data analysis relies heavily on software, but as projects grow it becomes hard to keep code, interfaces, and tests aligned, and to reuse methods without rewriting them. This thesis presents Genesis, which generates runnable modules, GUIs, and unit tests from a single human-readable .gen.m description of each analysis component. By maintaining a central library of these descriptions, analyses can be recombined for new questions while staying consistent. Four studies across neuroimaging, light-sheet microscopy, and plant Raman spectroscopy show the framework is reusable and extensible across domains.

Thesis: http://hdl.handle.net/2077/90289

Supervisor: Giovanni Volpe (Main), Caroline Beck Adiels
Examiner: Raimund Feifel
Opponent: Arvind Kumar
Committee: Wojciech Chachólski, Rita Almeida, Paolo Vinai
Alternate board member: Mohsen Mirkhalaf

Hang Zhao presented his half-time seminar on 22 January 2026

Hang Zhao, supervised by Giovanni Volpe and Joana Pereira, will present his halftime seminar under the topic “Brain connectome revealed neuro-degenerative disease” on 9-10 am, 22nd Jan. 2026 in Nexus and through Zoom (https://gu-se.zoom.us/j/7726618257). The seminar starts from his presentation about the past and planned project, followed by a discussion and questions by his opponent, Professor Mattias Göksor.

Presentation by S. K. Manikandan at The Arctic Meeting for Adaptive Mechanisms in Biological Systems, Abisko, Sweden, January 21, 2026

Recent advances in nonequilibrium physics allow extracting thermodynamic quantities, such as entropy production, directly from dynamical information in microscopic movies. *(Figure by S. Manikandan, adapted from Manikandan et al., Phys. Rev. Research 6, 023310 (2024).)*

Localizing entropy production in cellular processes
Sreekanth Manikandan
Date: 21 Jan 2026
Time: 10:00 CEST
Place: STF Abisko, Sweden
The Arctic Meeting for Adaptive Mechanisms in Biological Systems

Quantifying the spatiotemporal forces, affinities, and dissipative costs of cellular-scale non-equilibrium processes from experimental data and localizing it in space and time remain a significant open challenge. Here, I explore how principles from stochastic thermodynamics, combined with machine learning techniques, offer a promising approach to addressing this issue. I will present preliminary results from experiments on fluctuating cell membranes and simulations of non-equilibrium systems in stationary and time-dependently driven states. These studies reveal potential strategies for localizing entropy production in experimental biophysical contexts while also highlighting key challenges and limitations that must be addressed.

Eduard Andrei Duta Costache joins the Soft Matter Lab

Eduard Andrei Duta Costache started his PhD at the Physics Department of the University of Gothenburg on the 19th of January 2026.

Eduard has a double Master’s degree in Artificial Intelligence from the University of Alicante (Spain) and in Machine Learning & Data Mining from Jean Monnet University (France).

During the course of his PhD, as part of the GREENS MSCA Doctoral Network, he will focus on developing AI frameworks to model and optimize the lifecycle of micro-robotic platforms.

Steven Smith visits the Soft Matter Lab

Steven Smith will visit the Soft Matter Lab from 17 to 28 January 2026.

Steven brings years of expertise from the laboratory of Professor Carlos Bustamante, where they pioneered the use and development of optical tweezers. As the main developer of the widely used ‘minitweezers’ instrument, which today is used by dozens of research groups, he has helped shape the field of single-molecule biophysics on a global scale. We look forward to his visit, during which he will work on refining cutting-edge single-molecule measurement techniques.

Yu-Wei Chang nailed his PhD thesis on January 7th, 2026. Congrats!

Thesis nailing by Yu-Wei Chang. *(Photo by C. Khanolkar.)*

Yu-Wei Chang nailed his PhD thesis, A Unified Software-Generating Framework for Biological Data Analysis, on January 7th, 2026. Congrats!

The nailing took place in Universitetsbyggnaden i Vasaparken, Universitetsplatsen 1, Göteborg, at 13:30.

In Swedish academia, “nailing” (spikning) is the formal public announcement and publication of a doctoral thesis. It happens weeks before the defence so that the public has time to read the thesis in advance and prepare questions for the defence. In addition to the physical nailing, the thesis is also published electronically (e-spikning) via GUPEA.

Yu-Wei will defend his thesis on 23 January at 13:00 in SB-H7 lecture hall, SB-Building, Institutionen för fysik, Johanneberg Campus, Göteborg.

Thesis (GUPEA handle): http://hdl.handle.net/2077/90289

Thesis Nailing by B. García Rodríguez, 7 January 2026. Congrats!

Thesis nailing by Berenice García Rodríguez. *(Photo by C. Khanolkar.)*

On 7 January at 13:00, Berenice García Rodríguez nailed her PhD thesis, Quantitative Optical Microscopy of Microscale Soft Matter Systems, at the University of Gothenburg in Vasaparken.
Family and friends were present to mark this milestone.

Berenice will defend her thesis on 28 January at 09:00 in PJ-salen, Institutionen för fysik, Origovägen 6, Göteborg.