Research

Forecasting and optimization under constraints and uncertainty for sustainable industrial energy systems

Principal Investigator. Contract research project in collaboration with Ing. Punzenberger COPA-DATA GmbH. Developing advanced RL and optimization methods for managing industrial energy systems under uncertainty.

Intelligent Novel Support for Personalized Instruction and Robust Evaluation in STEM Lessons

Principal Investigator (PLUS partner). Application-oriented basic research project funded by Land Salzburg (WISS2030) in collaboration with PH Salzburg. Focusing on AI-driven personalized learning and evaluation in primary education.

Deep Reinforcement Learning for Large and Complex Systems

International collaboration with University of Malta and CERN. Focusing on solving complex control problems for the Large Hadron Collider (LHC). Methodologies are transferable to autonomous driving and manufacturing.

The Gamma Factory is an ambitious CERN initiative to create a "super light source" by colliding laser pulses with partially stripped ions in the LHC. My involvement focuses on the accelerator physics challenges of maintaining stable ion beams and optimizing the collision luminosity, leveraging the same advanced control techniques used for the standard LHC runs.

A collaborative project with the University of Education Salzburg (PH Salzburg) to personalize STEM education in primary schools. We are developing an AI-driven intelligent tutoring system that adapts to individual student needs, providing robust evaluation and personalized feedback to enhance learning outcomes.

Researching Multi-Agent Reinforcement Learning (MARL) applications in 5G/6G wireless communication. Focusing on optimizing UAV-assisted networks to minimize information age (AoI) and energy consumption, enabling autonomous, self-optimizing aerial network swarms.

Reinforcement Learning for Intelligent Control of Piezoelectric Dental Devices

This project explores the application of Reinforcement Learning (RL) to enhance the control of piezoelectric dental handpieces. Moving beyond conventional PID systems, the research focuses on designing intelligent agents capable of adapting to complex physical dynamics. Laya utilizes her strong foundation in mathematics and simulation to develop robust controllers that improve the precision and efficiency of medical devices.

Data Science STIWA II

Research project with STIWA Group. Focusing on assembly line optimization using Hierarchical Reinforcement Learning to manage complex, multi-stage decisions in high-speed manufacturing.

Reinforcement Learning in Nautical Robotics

Expansion into maritime systems. Transferring control theory expertise to autonomous boats and submersibles, leveraging similarities between fluid dynamics and beam physics.

Exact Solutions of Indirect Transverse Field Effects in Elongated Structures with Applications to CERN LHC and PS

My doctoral research focused on the derivation of exact solutions for indirect transverse field effects in elongated structures, with direct applications to the CERN Large Hadron Collider (LHC) and Proton Synchrotron (PS). This work addressed the critical challenge of Indirect Space Charge Driven (ISCD) effects, which serve as a fundamental limit to beam stability and intensity.

I developed a novel theoretical framework utilizing complex Green functions to accurately model ISCD tune-shifts, providing the first comprehensive explanation for intensity-dependent phenomena observed in the PS Multi-Turn Extraction. Key contributions include the derivation of closed-form solutions for magnetic interactions in accelerator components and the development of new operators for tune-shift estimation. These models provide essential insights for mitigating beam instabilities in current operations and are scalable for future projects like the High-Luminosity LHC (HL-LHC).

Stylolites are rough surfaces formed by pressure solution in rocks. This research applied statistical physics and non-linear dynamics to model their formation and morphology. By treating rock deformation as a complex system, we derived scaling laws that describe the roughness of these geological features, drawing parallels to crack propagation and growth processes in physics.