Dr. Florian Jug holds a PhD in Computational Neuroscience from the Institute of Theoretical Computer Science at ETH Zurich. His research aims at pushing the boundary of what AI and machine learning can do to better analyze and quantify biological data. At HT, Dr. Jug covers the full breadth of bio-image computing, from research on novel methods for computer vision and machine learning, all the way to offering bio-image analysis as a service. Florian Jug is a strong proponent of open access science, open AI and ML methods, and open source software. His team is a core contributor to Fiji (~100,000 active users) and collaboratively develops open methods such as CARE, Noise2Void, PN2V, DivNoising, etc. He organizes scientific conferences (e.g the I2K conference), workshops (e.g. the BIC workshops at top-tier computer vision conferences) and various practical courses on machine learning for bio-image analysis (e.g. DL@MBL in Woods Hole) or microscopy (e.g. Quantitative Imaging at Cold Spring Harbor).

Anna Kreshuk received the diploma degree in maths from Lomonosov Moscow State University, Moscow, Russia, and the PhD degree in computer science in Heidelberg. She is currently a group leader in EMBL Heidelberg. Her research focuses on automating analysis of microscopy images with machine learning. Anna is obviously one of the key figures in our community of bioimage analysis and we are delighted to have her join as a teacher in our course.

Virginie Uhlmann joined EMBL-EBI as a Research Group Leader in September 2018. Her research focuses on bioimage analysis, specifically continuous representations for image analysis. Virginie's group works on collaborative, interdisciplinary projects with biologists and software developers. She holds a PhD in Electrical Engineering from the Swiss Federal Institute of Technology in Lausanne (EPFL), and is an associate member in the Bio Imaging and Signal Processing Technical Committee of IEEE Signal Processing Society (2018-2020).

Carsen Stringer is a group leader at HHMI Janelia Research Campus. Her lab develops algorithms for understanding large-scale neural activity. In addition, the lab works on general segmentation algorithms for cellular data, which enable fast and accurate processing of ~50,000 neuron recordings. Carsen did her PhD work at University College London on computational neuroscience with Kenneth Harris and Matteo Carandini, and her postdoc at Janelia with Marius Pachitariu.

Dr. Gomez de Mariscal is interested in understanding cell-level biology using bioimage analysis. Her research centers on facing the challenges when applying machine-learning techniques to microscopy images and on contributing to biological discoveries with it. Previously, she developed methods to process TEM images and phase-contrast time-lapse movies to contribute to the characterization of cancer cell motility. She has also conceived new biostatistical approaches to analyse big data. She is also one of the creators of deepImageJ, an environment to bridge deep-learning to ImageJ. A crucial part of her work and dedication is to make computational tools accessible (open and user-friendly) and reusable, and train non-experts to benefit from them.

Alexander Krull is a computer scientist from Dresden, Germany. After a PhD at the TU Dresden, Alex joined the Max-Planck Institute for Molecular Cell Biology and Genetics, where he worked in the Group of Florian Jug and developed multiple state-of-the-art methods for image restoration, such as Noise2Void, Probabilistic Noise2Void, etc. Alex is now a lecturer at University of Birmingham, where he continues to work on the intersection between Deep Learning methods and bioimage analysis.

Wei OUYANG is an assistant professor in the department of applied physics at KTH Royal Institute of Technology (Stockholm, Sweden). He is currently leading a research group, the AICell Lab, which is funded by the Data-Driven Life Science fellow program. The group focuses on building AI systems for cell and molecular biology. Dr. Ouyang obtained his PhD in computational image analysis at Institut Pasteur, Paris where he mainly focuses on applying deep learning for super-resolution microscopy. During this period, he developed a deep learning method called ANNA-PALM which massively accelerates super-resolution localization microscopy by 100x. He spent 4 years at Emma Lundberg’s group as a postdoctoral researcher. To address the challenges in the dissemination of AI tools, he developed an open-source computational platform, ImJoy, which makes deep learning tools easier to build and more accessible to the user. He is actively involved in consortiums and community activities for promoting more open, scalable, accessible and reproducible scientific tools. Among them, he is leading the development of the BioImage Model Zoo for sharing AI models in bioimage analysis. Dr. Ouyang is mainly interested in AI augmented microscopy imaging and data-driven whole-cell modeling.

Dr. Funke is a group leader at HHMI’s Janelia Research Campus. He develops methods and tools to analyze vast microscopy image data sets. Specifically, Funke and his team automatize computer-vision and machine-learning techniques that are designed to work hand in hand with human annotators. Their aim is to prioritize accuracy, speed, and scalability, while overcoming challenges such as poor resolution and other ambiguities. In addition, the team wants to use statistics extracted from automatic reconstructions of biological structures to test hypotheses of accuracy and improve human proofreading.

Joran Deschamps studied physics at the Paris-Saclay University (Orsay, France) and received his PhD in 2017 from the European Molecular Biology Laboratory (EMBL, Heidelberg, Germany), jointly with the Ruprecht Karl University of Heidelberg (Germany). During his time at EMBL in the Ries lab, first as a PhD student then as a scientific officer, he developed automated microscopes for superresolution microscopy and released multiple open-source optical systems and software packages. After a postdoctoral stay at the Max Planck Institute of Molecular Cell Biology and Genetics (MPI-CBG, Dresden, Germany), he joined the Fondazione Human Technopole (Milan, Italy) in 2021 as a researcher in bioimage analysis and a research software engineer, working in the image analysis facility, where he coordinates a team developping open-source tools for the community.

Damian Dalle Nogare is the manager of the bioimage analysis facility at the Fondazione Human Technopole in Milan, Italy. Prior to joining Human Technopole, he was a staff scientist in the section of neural developmental dynamics at the National Institutes of Health in Bethesda Maryland, where he worked on collective cell migration and organ patterning. He received his PhD in Biochemistry and Cell Biology in 2008 from Rice University in Houston Texas, and his undergraduate degree in Biochemistry from the University of Otago in Dunedin, New Zealand.

Igor Zubarev is a research software engineer in the Jug Group at the Fondazione Human Technopole in Milan, Italy. He received his Masters degree in Mechanical Engineering at the Tula State University in Russia. Before joining HT he worked as a Deep Learning engineer, mostly focusing on Computer vision and natural language processing. Igor is also a Kaggle competition master.

Anirban is currently a PhD student hosted in Jug Group at Human Technopole, advised by Dr. Florian Jug. His PhD Program is affiliated with the Faculty of Computer Science at the Technische Universität Dresden where he is a PhD candidate in Computer Science. His current project involves the application of AI in bioimage analysis. More specifically, he is investigating different bioimage restoration and analysis techniques using (wavelet based) multiresolution frequency analysis, deep learning, and denoising diffusion models. Anirban graduated with his bachelor’s degree in Computer Science and Engineering, from Vel Tech University in Chennai, India (2011 – 2015). During his undergrad, Anirban spent few months at Mahindra Teqo (formerly Machine Pulse), as an Engineering Intern in renewable energy projects, where he worked in an interdisciplinary team to evaluate the migration of databases to cloud. In his undergrad, he was also selected among top students from all over India, to participate in the undergraduate summer school at the Indian Institute of Science in Bengaluru. Anirban was awarded the Aichi Monozukuri Scholarship in 2015 by the Japanese Government, where he received a full funding to pursue his Master of Engineering (M.Eng.) degree at Nagoya Institute of Technology, Japan, advised by Professor Jun Sato and co-advised by Professor Fumihiko Sakaue, where he investigated the sequential nature of information flow inside a deep neural network using LSTMs. During his Master’s course, he also did a short internship at Sun Corporation, in Aichi, Japan where he worked on the AceReal augmented reality glasses for industrial applications. After graduating with an M.Eng. degree in 2018 from Nagoya Institute of Technology, Japan, Anirban worked as a computer vision researcher at Hitachi, Ltd. (Research and Development Group) in Tokyo, Japan, from April 2018 to January 2022. His work primarily involved the application of deep learning to microscopy images.

Ashesh is a PhD student in the Jug group at the Fondazioen Human Technopole in Milan, Italy. As part of his PhD, Ashesh is trying to use Computer Vision and more generally Machine learning techniques on the Microscopy images. Given a superimposed image containing two or more overlapping structures, the aim is to get the structures in individual channels. He completed his Bachelors and Masters in Computer Science and Engineering from Indian Institute of Technology, Delhi, India in 2015. For next 3 years (2016-2018), he worked in Qplum, an early stage startup from the Fintech domain where one of the things he worked on was to develop machine learning techniques to trade ETFs on several US exchanges. After spending one year doing Coursera courses on Machine learning and participating in Kaggle competitions, he joined as a Research Assistant in the Computer science department of National Taiwan University in Prof. Hsuan-Tien‘s lab in 2020 and for one year, he worked on two problems from Computer Vision field: Gaze Estimation in the wild and predicting rainfall in the Taiwan region.

Dr. Florian Jug holds a PhD in Computational Neuroscience from the Institute of Theoretical Computer Science at ETH Zurich. His research aims at pushing the boundary of what AI and machine learning can do to better analyze and quantify biological data. At HT, Dr. Jug covers the full breadth of bio-image computing, from research on novel methods for computer vision and machine learning, all the way to offering bio-image analysis as a service. Florian Jug is a strong proponent of open access science, open AI and ML methods, and open source software. His team is a core contributor to Fiji (~100,000 active users) and collaboratively develops open methods such as CARE, Noise2Void, PN2V, DivNoising, etc. He organizes scientific conferences (e.g the I2K conference), workshops (e.g. the BIC workshops at top-tier computer vision conferences) and various practical courses on machine learning for bio-image analysis (e.g. DL@MBL in Woods Hole) or microscopy (e.g. Quantitative Imaging at Cold Spring Harbor).

Damian Dalle Nogare is the manager of the bioimage analysis facility at the Fondazione Human Technopole in Milan, Italy. Prior to joining Human Technopole, he was a staff scientist in the section of neural developmental dynamics at the National Institutes of Health in Bethesda Maryland, where he worked on collective cell migration and organ patterning. He received his PhD in Biochemistry and Cell Biology in 2008 from Rice University in Houston Texas, and his undergraduate degree in Biochemistry from the University of Otago in Dunedin, New Zealand.

Joran Deschamps studied physics at the Paris-Saclay University (Orsay, France) and received his PhD in 2017 from the European Molecular Biology Laboratory (EMBL, Heidelberg, Germany), jointly with the Ruprecht Karl University of Heidelberg (Germany). During his time at EMBL in the Ries lab, first as a PhD student then as a scientific officer, he developed automated microscopes for superresolution microscopy and released multiple open-source optical systems and software packages. After a postdoctoral stay at the Max Planck Institute of Molecular Cell Biology and Genetics (MPI-CBG, Dresden, Germany), he joined the Fondazione Human Technopole (Milan, Italy) in 2021 as a researcher in bioimage analysis and a research software engineer, working in the image analysis facility, where he coordinates a team developping open-source tools for the community.