CV

General Information

Residency Barcelona
Nationality Italian
Languages Italian, English, Spanish (intermediate)

Education

  • 2019 - 2024
    PhD in Neuroscience and Machine Learning.
    Wellcome Trust PhD programme, Faculty of Engineering Mathematics, University of Bristol, UK.
    • Applications of deep reinforcement learning to understanding human motor learning, especially with policy gradient methods (60% of PhD).
    • Purely machine learning projects on improving value-based estimation methods in reinforcement learning (40% of PhD).
  • 2017 - 2019
    Contract education in Data Science and Knowledge Engineering.
    Maastricht University, Netherlands.
    • Undertook fundamental courses in mathematics and computer science at bachelor and master levels (average grade achieved 8.4/10).
  • 2016 - 2017
    Master of Research (MRes) in Cognitive Neuroscience.
    University College London (UCL), UK.
    • Awarded with Distinction; Dean's list award for top 5% of the Brain faculty.
  • 2013 - 2016
    Bachelor of Science (BSc) in Psychology.
    Bath Spa University, UK.
    • Awarded First-class; British Psychology Association award for top graduating student.

Experience

  • Current
    Senior Postdoctoral Associate in Protein Language Models & Generative Protein Design.
    Centre for Genomic Regulation (Ferruz group), Spain.
    • Led design and execution of large-scale pre-training of protein language models (ProtGPT3 project, up to 10B parameters), across multi-node, multi-GPU systems (40+ GPUs) using PyTorch Distributed, DeepSpeed, and Hugging Face Accelerate.
    • Led post-training (SFT, RLHF) of large protein and genomic (e.g., evo2) language models for target bio properties.
    • Developed large-scale evaluation pipelines for protein language model generations, integrating structure prediction (AlphaFold, ESMFold, Boltz), evolutionary consistency checks (HMM profiles, MSA-based metrics), and sequence-level scoring (ESM, ProteinMPNN) to assess structural validity and design quality at scale.
  • 2024
    Visiting Postdoctoral Research Associate in Neuroscience and Machine Learning.
    University of Oxford, UK, under Rui Ponte Costa.
    • April - December 2024.
  • 2023 - 2024
    Visiting PhD Student in Neuroscience and Machine Learning.
    University of Oxford, UK.
  • 2021 - 2022
    Teaching Assistant.
    University of Bristol, UK.
    • Engineering Mathematics 1, Computational Neuroscience.
  • 2019
    Paid Student Assistantship in Deep Reinforcement Learning and Human Vision.
    Maastricht University, Netherlands.
    • Feb - April 2019. Working on a well-known deep RL vision architecture to subsequently model human gaze (repo).
  • 2016
    Assistant Data Analyst.
    Annex Clinical, New York, USA.
    • Feb - April 2016. Analysis of a large clinical dataset to investigate the relation between anhedonia and depression in relation to clinical trial drop-out (see article).

Most Relevant Publications

  • 2026 (Submitted)
    • Garibbo, M., Boxo, G., Middendorf, L., Stocco, F., & Ferruz, N. ProtGPT3: an Open-source family of Promptable and Aligned Protein Language Models. NeurIPS.
  • 2026
    • Stocco*, F., Garibbo*, M., & Ferruz, N. Steering generative models for protein design: Aligning and conditioning strategies. Current Opinion in Structural Biology, 98, 103250.
    • Moberg, S., Garibbo*, M., Mazo*, C., Gilad, A., Schmitz, D., Costa, R. P., ... & Takahashi, N. Distinct roles of cortical layer 5 subtypes in associative learning. Nature Communications, 17(1), 2648.
  • 2024
    • Garibbo, M., Robeyns, M., & Aitchison, L. Taylor TD-learning. Advances in Neural Information Processing Systems (NeurIPS), 37.
  • *equal contribution

Contributed Talks

  • 2026
    • Garibbo, M., Boxo, G., Middendorf, L., Stocco, F., & Ferruz, N. ProtGPT3: an Open-source family of Promptable and Aligned Protein Language Models. Eric and Wendy Schmidt Symposium on Biomedical Science and AI, Broad Institute of MIT & Harvard, USA.
  • 2021
    • Garibbo, M., Ludwig, C., Lepora, N., & Aitchison, L. What can deep reinforcement learning tell us about human motor learning and vice-versa? Neuromatch Conference, December 2021, Online.
  • 2016
    • Garibbo, M. and Wierdak, E. The effect of local environmental context changes on intentional and unintentional memory retrieval. British Psychology Association South West Undergraduate Conference, March 2016, University of the West of England, Bristol.

Selected Posters

  • 2023
    • Garibbo, M., Robeyns, M., & Aitchison, L. Taylor TD-learning. NeurIPS, USA.
  • 2022
    • Zanzi, M., Garibbo, M., Tavano, A., & Saponati, M. RNN reconstruction of mouse latent neural dynamics. Neuromatch Conference, Online.
    • Garibbo, M., Ludwig, C., Lepora, N., & Aitchison, L. What deep reinforcement learning tells us about human motor learning and vice-versa. CSHL From Neuroscience to Artificially Intelligent conference, New York.

Programming and Technical Skills

  • Deep Learning frameworks: PyTorch (extensive), Hugging Face (extensive), TensorFlow.
  • Distributed Training: PyTorch Distributed, DeepSpeed, Hugging Face Accelerate (multi-node, multi-GPU training up to 40+ GPUs).
  • Programming Languages: Python (extensive), Java (basic), Matlab.
  • Infrastructure & Tools: Linux, OS, Docker, Singularity, Git, Vim, Latex, high performance computing (SLURM).

Awarded Fundings

  • 2025
    • MINECO Colaboración Público-Privada for a Deep Learning Scientist in protein design.
  • 2023
    • Wellcome Trust 8-month Transition Fund for a Postdoctoral position.
  • 2019
    • Wellcome Trust 4-year PhD Scholarship.
  • 11/2025
    • MN5 EuroHPC Development Access Call: 14,000 GPU hours.
  • 01/2026
    • MN5 Red Española de Supercomputación fast-track low priority GPU access.

Awards and Achievements

  • 2017
    • Dean's list award for top 5% graduating student of the UCL Brain faculty.
  • 2016
    • British Psychology Association award for the top psychology graduating student of Bath Spa University.

Summer Schools

  • Machine Learning x Health, University of Oxford, 1 week, August 2022, Oxford, UK.
  • Deep Learning, Neuromatch Academy, 3 weeks, July 2022, online.
  • Robotic, Perception and Learning, KTH, 1 week, June 2022, Stockholm, Sweden.
  • Computational Neuroscience, Neuromatch Academy, 3 weeks, July 2021, online.
  • 2nd International Summer School on Deep Learning, 1 week, July 2018, Genova.