Session	Start Time	Talk Title	Speaker(s)
Opening Remarks	8:30AM	Welcome to CVMI 2024 & Logistics for Hybrid Format	Mei Chen (Microsoft)
Invited Talk	8:40AM	Microscopy, foundation models, and the scaling hypothesis: a phenomenal step forward for image-based profiling	Berton Earnshaw, Ph.D., Machine Learning Fellow, Recursion
Invited Talk	9:20AM	Protein Data Bank: From Two Epidemics to the Global Pandemic to mRNA Vaccines and Paxlovid	Stephen K. Burley, University Professor & Henry Rutgers Chair, Rutgers University
Accepted Paper	10:00AM	Discovering interpretable models of scientific image data with deep learning	Christopher J Soelistyo (The Alan Turing Institute)*; Alan R Lowe (University College London)
Accepted Paper	10:10AM	Vim4Path: Self-Supervised State Space Modeling for Histopathology Images	Ali Nasiri-Sarvi (Concordia University); Vincent Quoc-Huy Trinh (Institute for Research in Immunology and Cancer); Hassan Rivaz (PERFORM Centre & Department of Electrical and Computer Engineering, Concordia University); Mahdi S Hosseini (Concordia University)*
Accepted Paper	10:20AM	Low-Resolution-Only Microscopy Super-Resolution Models Generalizing to Non-Periodicities at Atomic Scale	Björn Möller (TU Braunschweig)*; Zhengyang Li (Technische Universität Carolo-Wilhelmina Braunschweig); Markus Etzkorn (TU Braunschweig); Tim Fingscheidt ( Technische Universität Braunschweig)
Break	10:30AM	Coffee Break
Invited Talk	11:00AM	Learning and using self-supervised phenotypic features in small molecule discovery	Paula A. Marin Zapata, Data Scientist, Bayer Berlin
Accepted Paper	11:40AM	Refining Biologically Inconsistent Segmentation Masks with Masked Autoencoders	Alexander Sauer (University of Oxford)*; Yuan Tian (Yale University); Joerg Bewersdorf (Yale); Jens Rittscher (Oxford)
Accepted Paper	11:50AM	Histopathological Image Classification with Cell Morphology Aware Deep Neural Networks	Andrey Ignatov (ETH Zurich)*; Josephine Yates (ETH Zürich); Valentina Boeva (ETH Zurich)
Break	12:00PM	Lunch Break
Invited Talk	13:00	Building Large-Scale Foundation Models for Digital Pathology with Millions of Whole Slides and Multi-Modal Generative AI: from Virchow to PRISM	Siqi Liu, Ph.D., Director of AI Science, Paige AI
Accepted Paper	13:40	Unsupervised Microscopy Video Denoising	Mary D Aiyetigbo (Clemson University)*; Alexander K Korte (Clemson University); Ethan M Anderson (Clemson University); Reda M Chalhoub (Medical University of South Carolina); Peter Kalivas (Medical University of South Carolina); Feng Luo (Clemson University); Nianyi Li (Clemson University)
Accepted Paper	13:50	NOISe: Nuclei-Aware Osteoclast Instance Segmentation for Mouse-to-Human Domain Transfer	Sai Kumar Reddy Manne (Northeastern University); Brendan F Martin (Northeastern University); Tyler Roy (MaineHealth Institute for Research); Ryan Neilson (MaineHealth Institute for Research); Rebecca Peters (MaineHealth Institute for Research); Meghana Chillara (Northeastern University); Christine W Lary (Northeastern University); Katherine J Motyl (MaineHealth); Michael Wan (Northeastern University)*
Accepted Paper	14:00	Uncertainty Estimation for Tumor Prediction with Unlabeled Data	Juyoung Yun (Stony Brook University)*; Shahira Abousamra (Stony brook university); CHEN LI (Stony Brook University); Rajarsi Gupta (Stony Brook University); Tahsin Kurc (Stony Brook University); Dimitris Samaras (Stony Brook University); Alison L Van Dyke (National Cancer Institute); Joel Saltz (Stony Brook University); Chao Chen (Stony Brook University)
Accepted Paper	14:10	Triage of 3D pathology data via 2.5D multiple-instance learning to guide pathologist assessments	Gan Gao (Univeristy of Washington); Andrew Song (HMS); Fiona Wang (University of Washington); David R Brenes (University of Washington); Rui Wang (University of Washington); Sarah Chow (University of Washington); Kevin W Bishop (University of Washington); Lawrence D True (University of Washington); Faisal Mahmood (Pathology, Brigham and Women's Hospital, Harvard Medical School); Jonathan T.C. Liu (University of Washington)*
Invited Talk	14:20	Predicting Patient Treatment Outcomes using (Diffusion) Generative Models	Charlotte Bunne, Assistant Professor, EPFL
Poster Session	15:00PM	Coffee Break & Poster Session
Accepted Paper	15:45	GRAPE: GANs as Robust Adversarial Perturbation Encoders	Mahtab Bigverdi (University of Washington); Burkhard Hoeckendorf (Genentech)*; Heming Yao (Genentech); Philipp B Hanslovsky (Genentech); Romain Lopez (UC Berkeley); David Richmond (Genentech)
Accepted Paper	15:55	Super-resolution of biomedical volumes with 2D supervision	Cheng Jiang (University of Michigan)*; Alexander Gedeon (University of Michigan); Yiwei Lyu (University of Michigan); Eric Landgraf (University of Michigan); Yufeng Zhang (University of Michigan); Xinhai Hou (University of Michigan); Akhil Kondepudi (University of Michigan); Asadur Z Chowdury (University of Michigan); Honglak Lee (LG AI Research / University of Michigan); Todd C Hollon (1985)
Accepted Paper	16:05	Weakly Supervised Set-Consistency Learning Improves Morphological Profiling of Single-Cell Images	Heming Yao (Genentech)*; Philipp B Hanslovsky (Genentech); Jan-Christian Huetter (Genentech); Burkhard Hoeckendorf (Genentech); David Richmond (Genentech)
Accepted Paper	16:15	Grad-CAMO: Learning Interpretable Single-Cell Morphological Profiles from 3D Cell Painting Images	Vivek Gopalakrishnan (MIT)*; Jingzhe Ma (Xellar Biosystems); Zhiyong Xie (Xellar Biosystem)
Invited Talk	16:25	High-throughput mapping of 3D reconstructed neurons at whole-brain scale using petavoxel-computing	Hanchuang Peng, Ph.D, Allen Institute for Brain Science.
Work-in-Progress	17:05	Automating Removal of Contaminating Brainstem Tissue from Volumetric Mouse Spinal Cord Serial Two-Photon Tomography Images	Ariana Nawaby, Matthew Kenwood, Denise Ramirez
Challenge	17:15	Report Out: The Cell Tracking and Mitosis Challenge	Atharva Peshkar (University of Colorado Boulder)
Closing Remarks	17:30	Closing Remarks & Look Forward to CVMI 2025	Mei Chen (Microsoft)