I am a postdoctoral fellow investigating questions at the intersection of graph representation learning, graph signal processing, and geometric deep learning in the groups of Guy Wolf (UdeM) and William L. Hamilton (McGill).
I completed my PhD at the University of Toronto in Anna Goldenberg’s group, where I developed latent-variable models for cancer treatment outcome prediction and drug perturbation effect modelling.
In fall 2018 I interned in Google Accelerated Science team (Mountain View, CA), where I developed machine learning models for predicting drug effects on cell phenotype from the drug molecular structure. I used SMILES variational autoencoders, convolutional nets, graph neural nets.
In 2016 I interned in Atomwise (San Francisco, CA), where I worked on 3D convolutional neural nets to predict small molecule binding to protein targets and for scoring of the 3D binding poses.
My CV can be found here.
PhD in Computer Science, 2020
University of Toronto
MSc in Computer Science, 2012
Comenius University in Bratislava
BSc in Computer Science, 2010
Comenius University in Bratislava
I was a teaching assistant for the following courses at the University of Toronto:
In 2014–2016 I was the head coach for ACM International Collegiate Programming Contest at U of Toronto.