Main
John Zobolas
My background is in computer science, with diverse expertise in computational modeling, software engineering, survival analysis and statistical/machine learning.
Being an engineer at heart, my strongest quality is careful, analytical thinking.
A productive workday consists of writing clean, test-driven software and producing explainable data visualizations to drive my research.
I spend my free time playing the piano, juggling or reading books.
Education
Norwegian University of Science and Technology (NTNU)
PhD in Computational Biology
Trondheim
2021 - 2017
Thesis: Software implementations allowing new approaches toward data analysis, modeling and curation of biological knowledge for Systems Medicine
[GitBook link ] [Defence video ] [Results] [Diploma]
Athens University of Economics and Business (AUEB)
MSc in Computer Science
Athens
2015 - 2013
Thesis: SkyLighting Web Application with three.js [GitHub link ]
Diploma grade: 9.4/10 [Diploma] [Transcript]
National Technical University of Athens (NTUA)
M.Eng in Electrical and Computer Engineering
Athens
2013 - 2007
Thesis: Optimal Power Allocation in the uplink of Two-Tier Wireless Femtocell
Networks [GitHub link ]
Diploma grade: 8.4/10 [Diploma] [Transcript]
Professional Experience
Postdoctoral Researcher in Clinical AI
Oslo University Hospital
Oslo
Jan 2024 - Jan 2022
- Project: PANCAIM - pancreatic cancer AI for genomics and personalized medicine [website]
- Benchmarking survival ML models using multi-omics data
Internship in Molecular AI group
AstraZeneca
Gothenburg
April 2021 - Jan 2021
- Project: Predicting bioactivity data using Matrix Factorization for target-based clustering and validation
Research stay in Molecular Interactions Team
European Bioinformatics Institute
Hinxton, England
July 2018
- Project: Extending the PSICQUIC Java-based Web service platform to include causality information of molecular interactions
Linux Systems Engineer and Database Performance Tester
Commsquare
Athens
2015 - 2013
- Linux admin/support/database performance tuning
Teaching
Intro to ML for Survival Analysis with mlr3
Oslo Bioinformatics Workshop Week [workshop link]
N/A
2023
ML course for cancer researchers
Institute for Cancer Research in Oslo
N/A
2022
- Classification trees and model ensembles [slides]
- Support Vector Machines [slides]
- Neural Networks [slides]
- Benchmarking ML models using the spam dataset [GitBook link ]
Supervision
Hedda Fjell Scheel
Veterinary research student (forskerlinjestudent)
N/A
2024 - 2023
- Project: Genetic Heterogeneity of Canine Mammary Tumors
Selected Talks
Selected Publications
Fine tuning a logical model of cancer cells to predict drug synergies: combining manual curation and automated parameterization
N/A
2023
Boolean function metrics can assist modelers to check and choose logical rules
Journal of Theoretical Biology
N/A
2022
CausalBuilder: bringing the MI2CAST causal interaction annotation standard to the curator
N/A
2021
CausalTAB: the PSI-MITAB 2.8 updated format for signalling data representation and dissemination
N/A
2019
Online Books, Blogs
Awards/Scholarships
Program Study with Scholarship, EqualSociety
Scholarship for the MSc in Computer Science (AUEB)
N/A
2013
Program Great Moment for Education, Eurobank
Award for the highest grade in the Panhellenic examinations
N/A
2007