• Streamlined Machine Learning algorithms by migrating from Python to Java, resulting in faster and more efficient processes • Worked in the Machine Learning research for anomaly detection and diagnostics team

• Improved rover simulation software for ExoMars ESA contract (C++): – Achieved > ×3.0 speedup with SIMD matrix operations, better code structure, and concurrency – Developed realistic visualization in a game engine (C#; OpenGL) – Created pseudo-3D engine for fast visualization – Conducted thorough analysis of simulation accuracy by validating with real test data – Implemented a Gaussian process regression (GPR) algorithm to enhance terrain data accuracy for the proposed landing site

• Developed and validated novel AI-based metrics using uncertainty quantification (UQ) techniques, enabling automatic identification of sustainability in chemistry • Leveraged BERT and XGBoost models to predict sustainable properties in chemical reactions, leading to more informed decision-making • Enhanced Monte Carlo tree search algorithm by integrating AI-based metrics, ultimately enabling the identification of sustainable chemical synthesis paths