Mitesh Kumar

Machine Learning for Side-Channel Analysis • Pipeline Engineering: Designed experimental pipelines for power-trace acquisition and analyzed MLbased leakage on post-quantum signature schemes. • Hardware Robustness: Tested the robustness of neural-network-based attacks against measurement noise and sensor misalignment on real hardware oscilloscope recordings. • Literature Synthesis: Reviewed and synthesized literature on deep learning-based side-channel attacks, including profiling and single-trace attac

Transregio 154: Mathematical modeling, simulation and optimization using the example of gas networks. • Mathematical Constraint Modeling: Built a bicriteria optimization model for gas networks using Python (Pyomo), integrating dynamic pressure features to maximize social welfare. • HPC Scaling: Scaled numerical experiments across an HPC cluster using Slurm, resolving mathematical scaling distortions to aggregate and visualize 50+ multi-objective Pareto fronts. • Automated Workflows: Created a non-convex

• Graduated as a Bronze Medalist , ranking 3rd in the graduating class , showcasing academic excellence and a strong foundation in mathematical principles. • Developed expertise in areas such as calculus, linear algebra, probability, and statistics, providing a solid base for data-driven problem-so