KRISHNAJYOTH MANALIKKATTIL SATHYAN

Investigated the thermomechanical reliability and lifetime behaviour of printed silver structures on alumina and RO4003C RF substrate under cyclic thermal loading. - Conducted thermal shock testing between −40 °C and 150 °C / 180 °C to evaluate degradation. - Performed quantitative pull-off adhesion testing using a Zwick testing machine on alumina. - Performed cross-cut testing according to DIN EN ISO 2409 on RO4003C after cohesive substrate failure was observed in pull-off testing. - Developed simplifi

• Performed 50+ coating tests and characterization studies on waveguide antennas, ensuring long-term durability and performance • Conducted SEM analyses (Scanning Electron Microscopy) for documentation and microstructure evaluation • Automated the analysis of RF measurements using Python, reducing evaluation time by 30% • Assessed components from production trials, identifying defect trends and recommending corrective actions • Structured and documented feature catalogues and requirement set for testing

I completed my project thesis on Quantum Machine Learning for Visual Inspection, focusing on how quantum computing can enhance image-based defect detection and automated inspection systems. The work explored hybrid and fully quantum neural network architectures, integrating classical CNN layers with parameterized quantum circuits for feature extraction and classification. A structured review and analysis of research studies was conducted to understand performance, qubit utilization, model design, and real-

• Designed and tested 10+ automation scripts in Python for data processing tasks, improving workflow efficiency by 25% • Conducted data analysis using NumPy, Pandas, and Matplotlib on datasets • Collaborated on team projects via GitHub, ensuring version control and seamless integration • Debugged and optimized algorithms, reducing code runtime by 15%

• Produced technical drawings and 3D models using AutoCAD and SolidWorks for engineering and architectural applications • Designed and simulated complex mechanical components, improving design accuracy by 20%