Session	Start Time	Talk Title	Speaker(s)
Opening Remarks	8:30AM	Welcome to CVMI 2023 & Logistics for Hybrid Format	Mei Chen (Microsoft)
Invited Talk	8:40AM	Machine learning challenges in spatial single cell omics analysis	Fabian Theis (Technische Universität München)
Invited Talk	9:20AM	AI for breast cancer diagnostics 2.0	Jeroen van der Laak (Radboud University Medical Center)
Accepted Paper	10:00AM	Giga-SSL: Self-Supervised Learning for Gigapixel Images	Tristan Lazard (Mines-Paristech)*; Marvin Lerousseau (Mines-Paristech); Etienne Decenciere (Mines-Paristech); Thomas Walter (Institut Curie / Mines ParisTech)
Accepted Paper	10:10AM	Fast local thickness	Vedrana A Dahl (Technical University of Denmark)*; Anders Bjorholm Dahl (Technical University of Denmark)
Work-in-Progress	10:20AM	Automatic analysis of cryo-electron tomography using computer vision and machine learning	Min Xu (Mohamed bin Zayed University of Artificial Intelligence)
Work-in-Progress	10:25AM	Performance Review of Retraining and Transfer Learning of DeLTA 2.0 for Image Segmentation for Pseudomonas fluorescens SBW25	Beate C Gericke (Max Planck Institute for Evolutionary Biology)*; Finn Degner (Technische Hochschule Lübeck); Tom Hüttmann (Technische Hochschule Lübeck); Sören Werth (Technische Hochschule Lübeck); Carsten Fortmann-Grote (Max Planck Institute for Evolutionary Biology
10:30AM	Coffee Break
Accepted Paper	10:40AM	A Super-Resolution Training Paradigm Based on Low-Resolution Data Only to Surpass the Technical Limits of STEM and STM Microscopy	Björn Möller (TU Braunschweig)*; Jan Pirklbauer (Institut für Nachrichtentechnik, TU Braunschweig); Marvin Klingner (Technische Universität Braunschweig ); Peer Kasten (TU Braunschweig); Markus Etzkorn (TU Braunschweig); Tim J Seifert (Technische Universität Braunschweig); Uta Schlickum (Institute of Applied Physics and Laboratory for Emerging Nanometrology, Technische Universität Braunschweig, Braunschweig, Germany); Tim Fingscheidt ( Technische Universität Braunschweig)
Accepted Paper	10:50AM	New Bayesian Focal Loss Targeting Aleatoric Uncertainty Estimate: Pollen Image Recognition	Natalia E Khanzhina (ITMO University)*; Maxim Kashirin (ITMO University); Andrey Filchenkov (ITMO University)
Work-in-Progress	11:00AM	Virtual Staining for Pixel-Wise and Quantitative Analysis of Single Cell Image Analysis	Abdurrahim Yilmaz (Bundeswehr University Munich); Rahmetullah Varol (Universitat der Bundeswehr Munchen)*; Tülay Aydın (Universitat der Bundeswehr Munchen)
Work-in-Progress	11:05AM	Self-supervised clustering and annotation of single-cell trajectories	Kristina Ulicna (The Alan Turing Institute)*; Manasi Kelkar (University College London (UCL)); Christopher J Soelistyo (The Alan Turing Institute); Guillaume Charras (University College London (UCL)); Alan R Lowe (University College London)
Work-in-Progress	11:10AM	Spatio-temporal graph attention networks predict single cell response to cancer treatment in live 3D tumour spheroids	Matt De Vries (Institute of Cancer Research), Lucas Dent (Institute of Cancer Research), Hugh Sparks (Imperial College London), Christopher Dunsby (Imperial College London), Chris Bakal (Institute of Cancer Research)
Invited Talk	11:15AM	How Can Humans Learn from AI	Po-Hsuan Cameron Chen (Need)
Lunch Break	11:55AM	Lunch Break
Invited Talk	13:00	Decoding hidden signal from neurodegenerative drug discovery high-content screens	Michael J Keiser (UC San Francisco)
Invited Talk	13:40	Multimodal Computational Pathology	Faisal Mahmood (Harvard Medical School)
Accepted Paper	14:20	Learning to Correct Sloppy Annotations in Electron Microscopy Volumes	Minghao Chen (MIT); Mukesh Banglore Renuka (Harvard University); Lu Mi (MIT); Jeff Lichtman (Harvard University); Nir Shavit (Massachusetts Institute of Technology); Yaron Meirovitch (Harvard; MIT)*
Accepted Paper	14:30	Theia: Bleed-Through Estimation with Convolutional Neural Networks	Najib Ishaq (NIH); Nathan Hotaling (NIH); Nicholas Schaub (National Center for the Advancement of Translational Science, National Institutes of Health)*
Accepted Paper	14:40	RxRx1: A Dataset for Evaluating Experimental Batch Correction Methods	Maciej Sypetkowski (Recursion); Morteza Rezanejad (Recursion)*; Saber Saberian (Recursion); Oren Kraus (Recursion); John Urbanik (Recursion); James Taylor (Enveda Biosciences); Ben Mabey (Recursion); Mason Victors (Recursion); Jason Yosinski (ML Collective); Alborz Rezazadeh Sereshkeh (Recursion); Imran Haque (Recursion); Berton Earnshaw (Recursion)
Accepted Paper	14:50	An Ensemble Method with Edge Awareness for Abnormally Shaped Nuclei Segmentation	Yue Han (Purdue University)*; Yang Lei (HP); Viktor Shkolnikov (HP); Daisy Xin (HP); Alicia Auduong (HP); Steven Barcelo (HP); Jan Allebach (Purdue University); Edward Delp (Purdue University)
15:00PM	Coffee Break
Invited Talk	15:30	PLIP: Leveraging medical Twitter to build a visual–language foundation model for pathology AI	James Zou (Stanford University)
Invited Talk	16:00	Point-and-click: using microscopy images to guide spatial next generation sequencing measurements	Jocelyn Kishi (Stealth TechBio Startup)
Accepted Paper	16:40	Out of Distribution Generalization via Interventional Style Transfer in Single-Cell Microscopy	Wolfgang M Pernice (Columbia University)*; Michael Doron (The Broad Institute); Alex Quach (Massachusetts Institute of Technology); Aditya Pratapa (Virginia Polytechnic Institute and State University); Sultan Kenjeyev (University College London, University of London); Nicholas De Veaux (New York University); Michio Hirano (Columbia University); Juan Caicedo (Broad Institute)
Accepted Paper	16:50	One-shot and Partially-Supervised Cell Image Segmentation Using Small Visual Prompt	Sota Kato (Meijo university)*; Kazuhiro Hotta (Meijo University)
Invited Talk	17:00	Enhancing SAM's Biomedical Image Analysis through Prompt-based Learning	Dong Xu (University of Missouri Columbia)
Challenge	17:30	The Cell Tracking and Mitosis Challenge	Samreen Anjum (University of Colorado Boulder)
Closing Remarks	17:45	Announcements & Look Forward to CVMI 2024	Mei Chen (Microsoft)