Time

Speaker

Topic

8:00 – 8:10am

Welcome and introduction

8:10 – 9am

Anna Kreshuk, European Molecular Biology Laboratory (EMBL)  

3D image segmentation at scale 

(Invited talk) 

9:00 – 9:50am 

Shantanu Singh, Broad Institute

Accelerating Drug Discovery through the Power of Microscopy Imaging and Deep Learning 

(Invited talk)

9:50 – 10:00am

Break

10:00 – 10:20am

Genevieve Buckley, Monash University 

Adaptive image acquisition: combining deep learning sample segmentation with automated microscope control

10:20 – 10:40am 

Rashindrie Perera, University of Melbourne  

Deep feature based classification of Breast Cancer Whole Slide Images using Tumor Infiltrating Lymphocyte Grade 

10:40 – 11:00am

Ben Croker, University of California San Diego 

Analysis of cell death signaling using StarDist 

11:00 – 11:20am

Hui Li, University of Melbourne  

Bi-Objective Optimisation in Single Cell Variational Inference 

11:20 – 11:40am

Sonika Tyagi, Monash University 

Linc2function: An Artificial Neural Network (ANN) model to annotate lncRNA transcripts

11:40 – 12:40pm 

Lunch Break 

12:40 – 1:20pm 

Liam Fearnley (40 mins), WEHI

Implementing machine and deep learning methods

1:20 – 1:40pm

Tamasha Malepathirana, University of Melbourne

A Convolutional Neural Network architecture for complex Multi-Electrode Array signal pattern analysis 

1:40 – 2:10pm 

Natalie Gunn, IBM Research 

Through the looking glass: how AI can make your eye the window to your health 

(Invited talk) 

2:10 – 2:30pm

Break

2.30 – 2:50pm 

Chris Woodruff, WEHI

Microbiome characterisation using deep learning to merge multiple regions of the ribosomal RNA operon 

2:50 – 3:30pm

Priya Rani, RMIT University  

Attention Augmented U-Net (AA-UNet) for semantic segmentation of lung infections in COVID-19 patients 

(Invited talk) 

3:30 – 3:50pm 

Tobias Rasse, Max Planck Institute for Heart and Lung Research 

OpSeF: Open source Python framework for collaborative instance segmentation of bioimages 

3:50 – 4:00pm

Close