Linux Kernel Development - Scalability & Performance, AI Inferencing & HPC Platforms

• Advanced research in embedded systems and IoT at the Penn State Learning Factory.

• Conducted application-based teaching sessions using tools like myDAQ and Arduino Uno.

• Guided undergraduates through hands-on projects, including wearable technology.

• Led a team of Teaching Assistants, ensuring safety compliance and effective inventory management.

• Analyzed and optimized Linux kernel performance, focusing on IPC scheduling and cache utilization.

• Developed enhancements in memory management and kernel diagnostics, contributing to kernel v6.11-rc1.

• Managed project progress using JIRA and version control systems, ensuring timely delivery of patches.

• Conducted in-depth data privacy research focusing on privacy-enhancing technologies and e-contracting interfaces.

• Designed and implemented secure web application architecture using Django, HTML, JavaScript, and MongoDB.

• Collaborated with stakeholders to ensure compliance with data privacy regulations, enhancing user trust and security.

• Optimized database performance and conducted thorough testing, resulting in a robust and responsive application.

In this role, I played a crucial part in the development of cutting-edge embedded software at Arm. This involved diving into product development and software research, contributing to open-source initiatives, and optimising GPU software for optimal performance. I was responsible for meticulously crafting Board Support Packages (BSP) and delved into kernel debugging and system design. Through my proficiency in C++, Python, and other languages, I actively participated in systems development and used Docker to enhance efficiency. This experience significantly deepened my understanding of embedded systems, cementing my prowess in software engineering.