Resume


Education

  • Bassoon and harmony studies.

Experience

Applied Science Intern

  • Project: "Multimodal search”.
  • Summary: Adapt language and vision models to perform retrieval using image and text inputs.
  • Supervisors: Dr. Arnab Dhua, Dr. Xinliang Zhu, and Michael Huang.

Applied Science Intern

  • Project: "Robust visual similarity learning”.
  • Summary: Derive a procedure to train robust deep metric learning models on datasets with noisy correspondences. Propose a procedure to perturb the labels of benchmark that mimics real annotation errors.
  • Supervisors: Dr. Arnab Dhua, Dr. Xiaofan Lin, and Dr. Muhammet Bastan.

Applied Science Intern

  • Project: "Contextual Position Bias Estimation for Unbiased Learning to Rank”.
  • Summary: Propose a ranker-agnostic method to model the probability of an item being seen in different contexts, e.g., for different users, with a single estimator. This can be used in LTR algorithms to distinguish the absence of click due to irrelevance or lack of examination, thus better matching the true user preferences.
  • Supervisors: Dr. Matteo Ruffini and Dr. Giuseppe Di Benedetto.

Engineering Intern, CTO

  • Project: ”Speech and Audio Style Transfer” - Internship credited with Master Thesis.
  • Summary: This project introduced FastVC, a method for fast (4x faster than real-time on CPU) many-to-many non-parallel Voice Conversion (VC). The proposed approach was accepted as a technical paper to the VC Challenge 2020, where FastVC outperformed the Challenge baselines in quality results on the cross-lingual VC task.
  • Supervisors: Dr. Milos Cernak and Prof. Martin Jaggi.

Student Research Assistant

  • Project: ”Affine-Invariant Robust Training” - Semester project
  • Summary: Proposed evolution strategies as zeroth order optimization algorithms to find the worst affine transforms for each input. The proposed method effectively yields robust models and allows introducing non-parametric adversarial perturbations.
  • Supervisors: Dr. Sebastian Stich, Maksym Andriushchenko (PhD candidate at EPFL), and Prof. Martin Jaggi.

Junior at Risk Advisory IT Department

  • Bachelor's internship.
  • Hardening security measures of IT systems at Banc Sabadell.

Programming Skills

Python
JAVA
C/C++
MatLab
R
SQL
Scala
Bash
  • Tools: LaTeX, Git/GitHub, Jupyter Notebook, Linux, AWS
  • Python Packages: Numpy, SciPy, Scikit, Pandas, Matplotlib, Seaborn
  • Deep Learning Frameworks: PyTorch, TensorFlow, MXNet, Keras
  • Languages

    Catalan
    Spanish
    English
    French

    Honours

    1st prize

    • SEAT Challenge - AI For Mobility & Driving Experience

    1st prize

    • Bassoon category

    Volunteering

    Volunteer

    Attence to virtual paper presentations to ensure the correct functioning and the lack of violations of the code of conduct as well as to stimulate the discussions.

    Student Volunteer

    Coordination of several keynotes and paper presentations.