Remmy Zen

My full name is Remmy Augusta Menzata Zen. I am a postdoctoral researcher at the Max Planck Institute for the Science of Light working under the Munich Quantum Valley initiative on discovering better quantum computers with machine learning with particular focus on discovering fault-tolerant protocols.

My main research interest is in applying machine learning to quantum physics, in particular, and science, in general.

I received my PhD degree from the School of Computing, National University of Singapore. My dissertation topic was on transfer learning for neural-network quantum states.

• May 2024 - Our paper Tackling Decision Processes with Non-Cumulative Objectives using Reinforcement Learning is now on arXiv.
  
• March 2024 - Presented our paper at the APS March Meeting.
  
• March 2024 - Our paper Supervised Training of Neural-Network Quantum States for the Next Nearest Neighbor Ising model is published in Computer Physics Communications.
  
• February 2024 - Our paper Quantum Circuit Discovery for Fault-Tolerant Logical State Preparation with Reinforcement Learning is now on arXiv.
  
• December 2023 - Our work on "Discovering Quantum Circuits for Logical State Preparation with Deep Reinforcement Learning" has been accepted at the Machine Learning for Physical Sciences Workshop at Neural Information Processing (NeurIPS) 2023. Paper | Poster
  
• December 2023 - Our work on "Discovering Quantum Error Correcting Codes with Deep Reinforcement Learning" has been accepted at the Machine Learning for Physical Sciences Workshop at Neural Information Processing (NeurIPS) 2023. Paper | Poster
  
• December 2023 - Our paper Boosting the Gottesman-Kitaev-Preskill quantum error correction with non-Markovian feedback is now on arXiv.
  
• November 2023 - Our paper Simultaneous Discovery of Quantum Error Correction Codes and Encoders with a Noise-Aware Reinforcement Learning Agent is now on arXiv.