Research Areas
My PhD research areas include Quantum Artificial Intelligence, Quantum Architecture Search, Reinforcement Learning, and Multi-Agent Systems. Whereas more recently my research interests have shifted to digital transformation, automation, and AI for medical and health applications. Below you will find some topics from my PhD research.
Optimizing Variational Quantum Circuits
Exploring strategies to improve training and performance of variational quantum circuits.
Quantum Circuit Synthesis and Architecture Search
Automated methods for designing and optimizing quantum circuits.
Quantum Kernel Methods and Anomaly Detection
Leveraging quantum kernels for anomaly detection in machine learning.
Quantum Reinforcement Learning
Leveraging quantum mechanics for reinforcement learning
Talks and Posters
I have presented my research at various conferences and workshops on topics like Quantum AI, optimization techniques, and advancements in machine learning. Below you will find a selection of my presentations.
Quantum Advantage Actor Critic
25. February 2024 @ ICAART 2024 - Rome, Italy
Multi-Agent Quantum Reinforcement Learning using Evolutionary Optimization
25. February 2024 @ ICAART 2024 - Rome, Italy
Disentangling Quantum and Classical Contributions in Hybrid Quantum Machine Learning Architectures
25. February 2024 @ ICAART 2024 - Rome, Italy
A Reinforcement Learning Environment for Directed Quantum Circuit Synthesis
25. February 2024 @ ICAART 2024 - Rome, Italy
Aquarium - A Comprehensive Framework for Exploring Predator-Prey Dynamics through Multi-Agent Reinforcement Learning Algorithms
24. February 2024 @ ICAART 2024 - Rome, Italy
Improving Primate Sounds Classification using Binary Presorting
14. July 2023 @ DeLTA 2023 - Rome, Italy