Deep Learning in Medical Biology Symposium

Deep Learning in Medical Biology Symposium

microscopy view of tissue sample
Learn about the latest methods being used to address today’s fundamental biomedical questions by using state-of-the art deep learning networks. 

DLiMB logoDeep Learning in Medical Biology (DLiMB) Symposium

Date: 29 October 2020 

Time: 8am-4pm Melbourne time (GMT+10) 

Venue: Online – Zoom 

Registration: Free – RSVP essential  



Keynote speakers 

  • Anna Kreshuk
    Group Leader at European Molecular Biology Laboratory (EMBL), Heidelberg, Germany 
  • Shantanu Singh
    Senior Group Leader, Imaging Platform, Broad Institute, Massachusetts, USA 
  • Priya Rani
    School of Engineering, RMIT University, Australia 
  • Natalie Gunn
    Healthcare Lead, IBM Research Australia





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



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



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



Diversity and Inclusion 

The symposium will be an inclusive environment where diverse voices are heard and respected. We aim to: 

  • Achieve gender parity in speakers and symposium chairs 
  • Foster a spirit of inclusiveness for all symposium attendees 
  • Encourage participation from under-represented groups, including Aboriginal and Torres Strait Islander peoples 
  • Create a space where everyone can be their authentic selves, including those from the LGBTIQA+ community 


Organising committee members 

  • Lachlan Whitehead, WEHI
  • Nina Tubau, WEHI
  • Tim Blackmore, WEHI
  • Soroor Zadeh, WEHI
  • Heejung Shim, University of Melbourne
  • Daryl Wilding-McBride, WEHI


Walter and Eliza Hall Institute logo    

University of Melbourne logo

Lattice light sheet microscope

Why optical microscopy has become one of the most powerful tools in medical research.