Experience

• Designing and evaluating hand-centric wearable camera systems to capture fine motor movements and micro-scale hand–object interactions using mechanical first principles.
• Developing computer vision and machine learning algorithms for real-time action recognition and assembly process monitoring.
• Collecting, annotating, and analyzing experimental datasets to improve manipulation detection accuracy and system robustness.
• Supporting research validation, literature review, and interdisciplinary collaboration to translate insights into practical improvements.

• Engineering an AI-driven thermal management solution for BMS to eliminate costly internal temperature sensors in EV battery packs and energy storage systems.
• Building a hybrid LSTM + PINN model in Python (PyTorch) that embeds heat transfer physics directly into the loss function, ensuring predictions stay thermally consistent.
• Designing model architecture for real-time edge inference, targeting reduced sensor costs, improved thermal safety, and extended battery lifespan in EV powertrains.
• Independently pivoted from AVL simulation to a real-world data-driven pipeline, accelerating the path to a deployable thermal model.

• Redesigned CFRP reflector assembly, improving structural durability by 10% while reducing material scrap through DFM optimization.
• Performed static structural and thermal FEA with mesh convergence, achieving 0.4 mm positional accuracy.
• Conducted root cause analysis to troubleshoot alignment issues, improving system performance by 20%.
• Collaborated cross-functionally with manufacturing teams to optimize throughput and implement process improvements.

• Designed an AGV chassis using SolidWorks & CATIA with GD&T, tolerance-stack analyses, and rapid prototyping validation.
• Enhanced heat tolerance and structural reliability by 5% through FEA analysis including mesh-convergence studies.
• Reduced manufacturing complexity through DFM principles — bend-radius optimization and part standardization.
• Accelerated issue resolution via structured root-cause analyses and iterative CAD revisions with cross-functional teams.

• Designed sheet metal brackets and mounting components for truck fuel tank assemblies using CATIA V5, ensuring manufacturability and structural reliability.
• Optimized laser cutting processes and material utilization, reducing raw material waste by 30% while maintaining durability.
• Improved assembly alignment accuracy by 22.8% through precise hole positioning and tolerance refinement, minimizing rework during fabrication.
• Increased daily production output by 50 units by streamlining fabrication workflows and improving coordination across manufacturing stages.
• Collaborated with cross-functional teams, including 5 field engineers, to support production and assembly operations.
• Worked with PLC-controlled jigs and sensor-based fixtures for alignment validation, contributing to a ~10% improvement in product reliability through testing and batch comparison.