Joanna Zemla
joanna.zemla@ifj.edu.pl


Bio
Lorep ipsum….

Gabriel Gomila
ggomila@ibecbarcelona.eu

Gabriel Gomila has got a PhD in Physics from the University of Barcelona (1997) with a thesis based on the theoretical modelling of electron transport at semiconductor interfaces. Later on, he was post-doctoral researcher at three different universities in Italy, France and Spain where he specialized in the theoretical modelling of nanoescale electronic devices. In 2001 he moved to the Department of Electronics at the University of Barcelona thanks to a Ramon y Cajal fellowship, where he expanded his research interests towards the merge of electronics and biological fields, thus focusing on microsystems for biological applications on-a-chip and on Atomic Force Microscopy for the electrical study of biological samples. In 2005 he became Associate Professor at the University of Barcelona and in 2008 Group Leader at IBEC, and in 2014 he was awarded with the ICREA Academia prize, which recognizes and promotes the research excellence of the university staff of Catalonia. Since 2017 he is Full Professor at the Department of Electronics of the University of Barcelona.

Jesús Pineda
jesus@iflai.com

Jesús Pineda earned his PhD in physics at the University of Gothenburg, where his research focused on the intersection of deep learning and computer vision. He is currently AI Research & Development Lead at IFLAI AB and a visiting researcher at the University of Gothenburg. His work centers on applying deep learning to extract insights from microscopy data, and he has co-authored several articles in high-impact journals. He is also a co-author of the book Deep Learning Crash Course and a core developer of the deep learning software packages DeepTrack and Deeplay.

Henrik Klein
henrik@iflai.com

Henrik Klein earned his PhD in Physics & AI from Chalmers University of Technology in Sweden, specifically focused on developing data-efficient AI for microscopy, spectroscopy and spectrometry analysis. Afterwards, he co-founded IFLAI AB and is active operationally as CTO. Additionally, he is co-author of Deep Learning Crash Course, a hands-on programming textbook focused on programming complex AI from scratch and have spoken and organized numerous conferences within AI for scientific data analysis. 

Carlo Manzo
carlo.manzo@uvic.cat

Carlo Manzo is an Associate Professor of Biophysics at the Universitat de Vic – Universitat Central de Catalunya (UVic-UCC), where he leads the Quantitative BioImaging Lab (QuBI). His research integrates biophysics, advanced optical microscopy, and artificial intelligence, with a strong emphasis on single-molecule imaging and the quantitative analysis of biological systems. He is a former Ramón y Cajal fellow and recipient of the Pérez Payà Prize from the Sociedad de Biofísica de España. He has authored more than 50 publications in leading international journals and has led multiple competitively funded research projects. He is actively involved in international community initiatives, including the organization and leadership of the Anomalous Diffusion (AnDi) Challenges, which promote reproducible and quantitative benchmarking of data-driven methods. Carlo Manzo is also co-author of the book Deep Learning Crash Course (No Starch Press).

David Rayner
david.rayner@gu.se

Dr. David Rayner is training coordinator and a research data advisor at the Swedish National Data Service (SND). SND is a national research infrastructure that helps researchers make all types of digital research data accessible and is dedicated to advancing FAIR (Findable, Accessible, Interoperable, Reusable) principles across scientific domains. Dr. Rayner supports researchers and institutions in designing workflows that enhance transparency, reproducibility, and impact. He leads hands-on data-management training for academic and professional audiences and contributes practical information on research data management for the national web portal Researchdata.se.