Agamemnon Krasoulis

Agamemnon Krasoulis

Machine Learning Scientist

Summary

Agamemnon Krasoulis is a Machine Learning Scientist with over 10 years of experience in academic and industrial positions. His work is inspired by the potential of data and technology to improve people’s lives. He develops machine learning algorithms for biomedical and healthcare applications including in-silico drug discovery, brain-machine interfaces, upper-limb prosthetics and cochlear implants.

Download my CV.

Interests
  • Machine Learning
  • Signal Processing
  • Biomedical & Neural Engineering
  • Computational Chemistry & Biology
  • Computational Neuroscience & Neuroinformatics
Education
  • PhD in Neuroinformatics, 2018

    University of Edinburgh

  • MRes (Distinction) in Computational Neuroscience & Neuroinformatics, 2013

    University of Edinburgh

  • MEng. Electrical and Computer Engineering, 2010

    University of Patras

Experience

 
 
 
 
 
Intelligencia AI
Senior Data Scientist - Bioinformatics
Dec 2023 – Present Athens, Greece

Member of the data science and bioinformatics team.
Responsibilities include:

  • Integration of pre-clinical models into proprietary clinical outcome prediction platform
  • Lead developer of internal molecular property prediction and drug safety framework
  • Prediction of immunotherapy outcome prediction with single-cell gene expression data
 
 
 
 
 
Insilico Medicine
Machine Learning Researcher
Apr 2023 – Oct 2023 Remote

Member of the molecular property prediction team for Chemistry42 platform.
Responsibilities include:

  • ML research and experimentation (classical and deep learning)
  • Software development
  • Code reviewing
 
 
 
 
 
Deeplab
Senior Machine Learning Engineer
Jun 2020 – Nov 2022 Athens, Greece

Deep neural virtual screening (DENVIS) for early-stage drug discovery using graph neural networks.

  • R&D lead
  • Project management
  • Research intern supervision
  • Research and experimentation
  • Software development
  • Funding acquisition
  • Patent and publication writing
  • Presentations and engagement with external stakeholders
  • Set-up and organisation of deep learning reading group



EEG-based brain-computer interfacing (BCI) using deep neural networks.

  • R&D lead
  • Algo team engineering management (4 ML engineers)
  • Project management
  • Software design and architecture
  • Hiring
 
 
 
 
 
School of Engineering, University of Newcastle
Research Associate (post-doctoral)
Apr 2018 – Apr 2020 Newcastle upon Tyne, UK
Machine and motor learning for upper-limb prosthetic control.
 
 
 
 
 
School of Informatics, University of Edinburgh
Research Associate (post-doctoral)
Nov 2017 – Feb 2018 Edinburgh, UK
Deep learning for cryptography.
 
 
 
 
 
School of Informatics, University of Edinburgh
Teaching assistant
Sep 2013 – Aug 2017 Edinburgh, UK

Courses:

  • Machine Learning and Pattern Recognition
  • Probabilistic Modelling and Reasoning
  • Introductory Applied Machine Learning
  • Data Mining and Exploration
  • Neural Computation
 
 
 
 
 
School of Social and Political Science, University of Edinburgh
Software Engineer
Sep 2013 – Aug 2016 Edinburgh, UK
Experimental design and software development for fMRI experiments.
 
 
 
 
 
Institute of Sound and Vibration Research, University of Southampton
Research Assistant
Jan 2012 – Sep 2012 Southampton, UK
Development of ML algorithms for noise reduction and speech intelligibility enhancement for cochlear implants.

Skills

Python
scipy
SciPy
pandas
pandas
pytorch
PyTorch
tf
TensorFlow
sklearn
scikit-learn
jupyter
JupyterHub
docker
Docker
gcp
Google Cloud Platform