Research
My research focuses on the intersection of Artificial Intelligence and Quantum Computing, exploring how quantum technologies can enhance machine learning methodologies. Specifically, I investigate the integration of quantum computing with AI to develop novel approaches within Quantum AI. By leveraging quantum algorithms and variational quantum circuits, my work aims to tackle complex optimization and learning problems that surpass the capabilities of classical computing, paving the way for more efficient and scalable intelligent systems.
Research Areas
My research areas include Quantum Artificial Intelligence, Automated Circuit Design, Reinforcement Learning, and Multi-Agent Systems. I aim to develop innovative solutions that leverage quantum computing to enhance AI methodologies and solve complex problems.

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, sharing insights on Quantum AI, optimization techniques, and advancements in machine learning. My talks and posters highlight the potential of quantum technologies in transforming AI and solving real-world challenges.

PIMAEX: Multi-Agent Exploration through Peer Incentivization
24. February 2025 @ ICAART 2025 - Porto, Portugal

Quantum Artificial Intelligence and Optimization (QAIO) - Introduction
24. February 2025 @ QAIO 2025 - Porto, Portugal

Optimizing Variational Quantum Circuits Using Metaheuristic Strategies in Reinforcement Learning
19. September 2024 @ QCE 2024 - Montreal, Canada

A Study on Optimization Techniques for Variational Quantum Circuits in Reinforcement Learning
08. July 2024 @ QSW 2024 - Shenzen, China

Quantum Diffusion Models
08. July 2024 @ QSW 2024 - Shenzen, China

Quantum Diffusion Models
19. April 2024 @ HaiQu

A Reinforcement Learning Environment for Directed Quantum Circuit Synthesis
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

Multi-Agent Quantum Reinforcement Learning using Evolutionary Optimization
25. February 2024 @ ICAART 2024 - Rome, Italy

Quantum Advantage Actor Critic
25. February 2024 @ ICAART 2024 - Rome, Italy

Towards Efficient Quantum Anomaly Detection
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

Improving Convergence for Quantum Variational Classifiers using Weight Re-Mapping
26. February 2023 @ ICAART 2023 - Lisbon, Portugal

Compression of GPS Trajectories using Autoencoders
25. February 2023 @ ICAART 2023 - Lisbon, Portugal

Learning to Participate through Trading of Reward Shares
25. February 2023 @ ICAART 2023 - Lisbon, Portugal

React Redux
27. May 2022 @ LMU Munich