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.
PIMAEX: Multi-Agent Exploration through Peer Incentivization
24. February 2025 @ ICAART 2025 - Porto, Portugal
Optimizing Variational Quantum Circuits Using Metaheuristic Strategies in Reinforcement Learning
19. September 2024 @ QCE 2024 - Montreal, Canada
Quantum Diffusion Models
08. July 2024 @ QSW 2024 - Shenzen, China
A Study on Optimization Techniques for Variational Quantum Circuits in Reinforcement Learning
08. July 2024 @ QSW 2024 - Shenzen, China
Quantum Diffusion Models
19. April 2024 @ HaiQu
Towards Efficient Quantum Anomaly Detection
25. February 2024 @ ICAART 2024 - Rome, Italy