Aldo Battista
Research Scientist - Machine Learning at Meta (Modern Recommender Systems AI) | Ph.D. | Ex NYU Swartz Fellow | NeuroAI | Deep Learning | Statistical Physics | Complex Systems
- Role
- Research Scientist - Machine Learning (Modern Recommender Systems Ai) at Meta
- Location
- New York, NY, US
- LinkedIn followers
- 500 followers
About Aldo Battista
Research Scientist in Machine Learning at Meta (Modern Recommender Systems AI team), bringing a unique interdisciplinary background in Theoretical Physics (Ph.D, École Normale Supérieure) and Computational Neuroscience (Swartz Fellow, NYU). My research leverages advanced machine learning techniques—including deep learning, recurrent neural networks (RNNs), reinforcement learning, multi-task learning, and continual learning—to model and understand complex systems, from neural circuits to large-scale AI applications.Throughout my postdoctoral work at New York University, I developed and trained sophisticated multi-regional and biologically constrained neural network models to investigate fundamental mechanisms of cognition, decision-making, and learning. Key projects involved multi-task learning in prefrontal cortex models and developing hybrid convolutional/recurrent architectures for biological vision.My doctoral research focused on the statistical physics of learning, particularly low-dimensional continuous attractors in high-dimensional data, employing techniques like replica theory and random matrix theory. I have a strong publication record in high-impact journals (Nature Communications, Physical Review Letters) and top-tier conferences (NeurIPS Spotlight).Passionate about bridging theoretical insights with practical AI development, I am proficient in Python, C/C++, PyTorch, JAX/TensorFlow/Keras, and Scikit-learn. Eager to contribute to cutting-edge ML research and build intelligent systems that learn and adapt effectively.Specialties: Machine Learning, Deep Learning, Recurrent Neural Networks (RNNs), Continual Learning, Multi-task Learning, Reinforcement Learning, Computational Neuroscience, NeuroAI, Interpretability, Theoretical Physics, Large-Scale Neural Modeling, Data Analysis, Statistical Physics, Complex Systems, Data Science.
Experience
Research Scientist - Machine Learning (Modern Recommender Systems Ai)
Sep 2025 — Present · New York, NY, US
Education
Sapienza Università di Roma
Master's degree, Theoretical (Statistical) Physics
2015 — 2017
Sapienza Università di Roma
Bachelor's degree, Physics
2013 — 2015
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