Career

A picture of Daniele Grattarola giving a talk at the 2026 CoFold Summit in Barcelona.

2026 - Now
Proxima
Head of Machine Learning
Leading a team of 10+ AI scientists developing a frontier generative AI platform spanning biomolecular structure prediction, proximity modulator design, and structural proteomics, deployed across multiple internal and external drug discovery programs.

2025 - 2026
Mistral AI
AI Scientist
Worked on large-scale synthetic data generation and post-training for multimodal LLMs.

2023 - 2025
Isomorphic Labs
Staff Research Scientist
Led the Generative Models team, pioneering generative AI methods across multiple drug design modalities that delivered strong results in several internal and external drug discovery programs.
Previously: Research Scientist, Senior Research Scientist.

2022 - 2023
École Polytechnique Fédérale De Lausanne (EPFL)
Postdoctoral Researcher
Conducted research at the intersection of AI and structural biology, with a primary focus on neural fields and generative models for protein design. Member of the LTS2 and LPDI labs.

2019 - 2022
Juvenescence, Menten AI, VantAI
External consultant
Advised early-stage biotech startups on building graph ML models to accelerate their drug discovery pipelines.

2019 - 2020
Krembil Research Institute
Visiting Researcher
Conducted research on geometric deep learning for the localisation of epileptic seizures from human intracranial EEG recordings.

Academia

Teaching

I have contributed to teaching, organizing, and supervising these university courses:

Faculty roles

I have been Ph.D. representative for USI's Faculty of Computer Science in 2018/2019.
During that time, I was the official point of contact between the Faculty and its doctoral students, participating in Faculty meetings and contributing to the strategic decisions of the University.

Awards

  • Awarded a Mobility grant of 18.000 CHF by the Swiss National Science Foundation in 2019.

Community & Open Source

This is a list of my past and current roles as a member of the AI community:

Spektral

I am the main developer of Spektral, an open-source Python library for creating graph neural networks in TensorFlow and Keras. The project has thousands of active users and was one of the first libraries ever created for graph deep learning.

Supervising & Mentoring

Mentoring for International Opportunity
L. Silvello  |  Mentorship (Talented Italians in the UK, 2025-2026)

Mentoring for International Opportunity
V. Barletta  |  Mentorship (Talented Italians in the UK, 2024-2025)

SmoothPool: a Hierarchical Pooling Operator for GNNs
Y. Chen  |  Master's thesis (USI, 2022)

Exploring Implicit Neural Representations from a Signal Processing Perspective
J. Deschenaux  |  Semester project (EPFL, 2022)

Adaptive Neural Cellular Automata
A. Charneca  |  Semester project (EPFL, 2022)

Coarsening Disassortative Graphs
A. Bar, G. Gonzalez, A. Jamadandi, V. Polianskii, M. Thiessen, Z. Zhong  |  Student project (LOGML summer school, 2021)

Molecule Generation with Graph-based Generative Adversarial Networks
M. Nobile  |  Master's thesis (USI, 2021)

Prediction of Epileptic Seizures with Graph-based Deep Learning
A. Ruggeri  |  Master's thesis (USI, 2020)

Talks

Invited talk and panel discussion
2026 CoFold Summit, Barcelona (May 6, 2026)

Generalised Implicit Neural Representations
Neural Information Processing Systems (2022)  |  Slides  

Introduction to Graph Neural Networks and Graph Pooling
Graph Deep Learning course, USI (Feb 28, 2022)  |  Slides  

Learning Graph Cellular Automata
Learning on Graphs and Geometry Reading Group (Jan 11, 2022)  |  Slides   Video  
Italian Workshop on Machine Learning and Data Mining, AIXIA (2021)  |  Slides  
Neural Information Processing Systems (Dec 7, 2021)  |  Slides  

Graph Neural Networks: Operators and Architectures
Dissertation defense, USI (Dec 10, 2021)  |  Slides  

Pooling in Graph Neural Networks
Advanced Machine Learning course, University of Manitoba (Dec 1, 2021)  |  Slides  
Graph Deep Learning course, USI (Mar 15, 2021)  |  Slides  

Introduction to Graph Neural Networks
Graph Deep Learning course, USI (Mar 1, 2021)  |  Slides  

Spectral Clustering with Graph Neural Networks for Graph Pooling
International Conference on Machine Learning (2020)  |  Slides  

Graph Neural Networks in Tensorflow and Keras with Spektral
Graph Representation Learning and Beyond, ICML (2020)  |  Slides  

Graph Neural Networks e MinCut Pooling (in Italian)
Italian Association for Machine Learning (ML/DS Meetup) (2020)  |  Slides   Video  

Generative Adversarial Networks
Advanced Topics in Machine Learning course, USI (Sep 17, 2020)  |  Slides  

Autoregressive Models for Sequences of Graphs
International Joint Conference on Neural Networks (2019)  |  Slides  

Reviewing

I have served as reviewer for these AI conferences, journals, and workshops:

Conferences

  • Neural Information Processing Systems (NeurIPS)
  • International Conference on Learning Representations (ICLR)
  • International Conference on Machine Learning (ICML)
  • Computer Vision and Pattern Recognition (CVPR)
  • Learning on Graphs Conference (LoG)
  • The Web Conference (WWW)
  • International Joint Conference on Artificial Intelligence (IJCAI)
  • International Joint Conference on Neural Networks (IJCNN)
  • European Symposium on Artificial Neural Networks (ESANN)
  • International Conference on Acoustics, Speech, & Signal Processing (ICASSP)

Journals

  • Journal of Machine Learning Research (JMLR)
  • Transactions on Machine Learning Research (TMLR)
  • Transactions on Neural Networks and Learning Systems (TNNLS)
  • Applied Soft Computing (ASOC)
  • Neurocomputing
  • Transactions on Knowledge Discovery from Data (TKDD)
  • Transactions on Emerging Topics in Computational Intelligence (TETCI)
  • Transactions on Geoscience and Remote Sensing (TGRS)

Workshops

  • New Frontiers in Graph Learning: Challenges, Perspectives, and Solutions (NeurIPS 2022)
  • Graph Neural Networks and Systems (MLSys 2021)
  • Graphs and more Complex structures for Learning and Reasoning (AAAI 2021, 2022)
  • ML Retrospectives (NeurIPS 2020)
  • Graph Representation Learning and Beyond (ICML 2020)
  • Graph Representation Learning (NeurIPS 2019)