Experience

ML Engineer, Reinforcement Learning

• Develop RL locomotion controllers in Isaac Sim and Isaac Lab for industrial quadrupeds.
• Build GPU-accelerated training and evaluation workflows for fast sim-to-real iteration.
• Led and secured a EuroHPC grant for large-scale robustness and scaling experiments.
• Design safety curricula targeting rare locomotion failure modes.

Research Assistant

• Developed inverse and imitation-learning methods for skill assessment and robust reward learning.
• Built reinforcement-learning benchmarks and assistance policies in surgical digital twins.
• Studied causal invariance and Wasserstein objectives under environment shift.
• Supported teaching in advanced machine learning, learning theory, and game theory.

Research Assistant

• Extended sequence-to-sequence models with structured variational inference.
• Investigated hyperbolic Wasserstein autoencoders for hierarchical representations.

Electrical Engineer

• Developed energy-harvesting wireless sensor networks for monitoring electrical machines.

PhD Computer Science (ML/AI)

Reinforcement learning from demonstrations in surgical digital twins.

MSc Electrical Engineering (Intelligent Systems)

Machine learning, statistical learning theory, and probabilistic AI.

BSc Electrical Engineering

Control theory, embedded systems, and electrical engineering.