Elisa G. de Lope

Elisa G. de Lope

PhD student in Biomedical Data Science

University of Luxembourg

Hi, I’m Elisa

Welcome to my corner of the internet! 👋

I’m interested in applying machine learning methods to solve challenges in the biomedical realm.

My background includes a blend of machine (and deep) learning modelling & bioinformatics. I currently work at the University of Luxembourg, where I extend my PhD work on graph representation learning for omics data. Additionally, I’m a Google summer of code ‘24 contributor on the deepchem library, where I integrate protein language models for predicting binding sites.

I recently graduated from my doctoral studies (yay!), in which I focused on statistical and ML methods to identify blood-based molecular markers for Parkinson’s disease diagnosis and prognosis. One of the highlights of my PhD was being awarded Fondation de Luxembourg’s fellowship to do a research visit in Cambridge, where I focused on exciting graph representation learning models (aka graph ML or geometric DL) with Pietro Liò (Cambridge Univeristy) and Petar Veličković (Google DeepMind).

Beyond research, I’m a fellow of the 2023 MIT Catalyst fellowhip program, where I explore the space of un-met needs in health(-tech) and I proudly serve as a global shaper recognized by the World Economic Forum of Geneva.

At work and in life, I thrive in collaborative, engaging atmospheres and enjoy sports, from padel tennis to running, with a special fondness for outdoor activities. While at Cambridge, I raced with the triathlon club the Varsity duathlon against Oxford - quite an experience! In my downtime, I enjoy indulging in a good book and the occasional slice of carrot cake with a glass of white wine.

Now that you know me a bit better, please don’t hesitate to get in touch if you’d like to chat about any of the above (or anything in techbio) or if you’re interested in collaborating on a project. I’m always open to new opportunities and connections 🤗

Disclaimer: this site is currently under (active) construction!

Download my resumé.

Interests
  • Machine learning
  • Graphs
  • Omics data
  • Drug discovery
Education
  • PhD in Biomedical Data Science, 2024

    University of Luxembourg

  • MSc in Bioinformatics, 2018

    Universitat Autonoma de Barcelona

  • BSc in Biotechnology (computational), 2017

    Universidad Politécnica de Madrid

Skills

Python
R
sql
bash
git
Machine Learning

Experience

 
 
 
 
 
Deepchem
Google summer of code contributor
May 2024 – Present Luxembourg (LU)

Integrated Hugging Face pLM ESM-2 in DeepChem open source library for predicting protein binding sites.

Production-level coding and tutorials, proposal was accepted within 13.4% acceptance rate. See more about my project here.

 
 
 
 
 
University of Luxembourg, Dept. of Engineering
Postdoctoral Researcher
University of Luxembourg, Dept. of Engineering
Mar 2024 – Present Luxembourg (LU)

Graph representation learning for modelling omics data (extension of PhD project).

Boosting Prot2text, a deep learning model to predict protein function from sequence and structure data.

 
 
 
 
 
Luxembourg Center for Systems Biomedicine
Doctoral Researcher
Luxembourg Center for Systems Biomedicine
Sep 2020 – Dec 2023 Luxembourg (LU)

I’m part of the Biomedical Data Science group. Integrative machine learning methods for the joint analysis of different types of omics, clinical and imaging data.

Responsibilities include:

  • State of the Art research and definition of experiments and project strategy
  • Scripting and modelling
  • Validation of results
 
 
 
 
 
Accenture Applied Intelligence
Data scientist
Accenture Applied Intelligence
Apr 2019 – Jun 2020 Barcelona (SP)

Applied statistics and ML models in a wide range of industries and projects. Forecasting sales, computer vision OCR, statistics for fraud detection, visualization.

Responsibilities include:

  • Extraction, preprocessing and analysing data from different formats
  • Modelling
  • Preparing scripts and models for deployment
 
 
 
 
 
Capgemini
Data analyst
Capgemini
Sep 2018 – Mar 2019 Barcelona (SP)

Use of SAS to access, manage, analyze and present data. Daily tasks related to SAS developer role, consultant and a migration of data from different database versions (data warehouse).

Responsibilities include:

  • Data extraction on SAS
  • Database migration
  • Scripting on SAS/SAS-SQL
 
 
 
 
 
Pharmacelera
Bioinformatician - intern
Pharmacelera
Feb 2018 – Jul 2018 Barcelona (SP)

Heuristics for computing hydrophobic properties based on quantum mechanics calculations applied to virtual screening and the alignment of molecules in drug discovery. Built a pipeline x30 times faster without compromising accuracy.

Responsibilities include:

  • Research in virtual screening techniques
  • Parametrization of hydrophobic descriptors
  • Build and validate the parametrized pipeline on external data

Accomplish­ments

deeplearning.ai
Deep Learning Specialization
See certificate
Coursera
Sequence models
See certificate
Coursera
Convolutional Neural Networks
See certificate
Coursera
Structuring Machine Learning Projects
See certificate
Coursera
Improving Deep Neural Networks- Hyperparameter Tuning, Regularization and Optimization
See certificate
Coursera
Neural Networks and Deep Learning
See certificate
CambridgeEnglish
CAE (Certificate of Advanced English)
AllianceFrançaise
DELF B2 (Diplôme d’Études en Langue Française)
DataCamp
Object-Oriented Programming in R
See certificate

Side Projects

*
SleepGuard

SleepGuard

Objective sleep data to guide treatment of sleep disturbance in PTSD. Project from MIT-Catalyst program.

Farmelody

Farmelody

Data-driven ‘farm-tech’, our secret weapon is the analysis of microbiome data. Prototype under construction!

Publications

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