Krishnaprasad Sreekumar Nair

• Teaching Assistant for EEE 591: Real-Time Digital Signal Processing • Mentored students in designing and optimizing real-time DSP algorithms on ARM Cortex-M architectures, with a strong focus on energy-efficient execution, memory hierarchy usage, and low-power embedded system design. • Supported RISC-V–based DSP optimization projects by guiding architectural trade-off analysis and simulation-based power-performance evaluation, deepening expertise in low-power CPU microarchitecture and SoC integration

• Assisted in the development and organization of course materials for CSE180 at Arizona State University. • Verified assignments and projects to ensure clarity and accessibility for students. • Provided support to students facing challenges, enhancing their understanding of course content.

•Designed, implemented, and validated an FIR filter to improve Adjacent Channel Rejection for an MSI Radio. •Simulated memory hierarchy for future DSP processors by evaluating and determining optimal cache hierarchy configurations to significantly enhance system performance for Motorola Solutions radios. •Developed an ML-driven Retrieval-Augmented Generation (RAG) framework for DSP log summarization, significantly accelerating root-cause analysis and improving debug efficiency for critical issues

• Graded labs and exams for CSE-100 - Introduction to C++ for 190+ students. • Assisted students with technical queries and hands-on sessions. • Collaborated with professors to ensure smooth grading process and student support.

•Automated and Optimized Multimedia Video Core Tests for Snapdragon Chipset’s quality assurance, identifying key areas for automation and notably boosting test efficiency by 30% on a YoY basis. •Innovated new methodologies to evaluate Late Stage Reprojection in XR Chipsets by producing XR Content (Eye and Depth) exploiting Blender with head pose estimation in a 6DoF Environment. •Pioneered the development of a Video Encoder Compression Validation Framework for Snapdragon Chipset harnessing a Python framework validating parameters such as fps, bitrate, GOP, Codec etc... •Engineered an end-to-end Automated Python Test Framework for a chipset in Augmented Reality (XR2 Gen2, XR2 Gen3, AR2 Gen 2), enhancing efficiency by 60% and reducing manual testing. •Spearheaded XR Automation, raising automation levels from 0% to 77% within a year, driving efficiency and consistency in testing, and enhancing overall project throughput. •Proposed and presented a poster at QBUZZ, Qualcomm India’s Technical Conference, and filed a patent on upgrading user experience for AR/VR/MR chipsets. •Led Knowledge-Sharing Initiatives, hosting multiple sessions related to video encoder/decoder technologies within the XR pipeline to upskill peers and cross-functional teams.

• WiFi Display (WFD) Application Quality: Focused on maintaining quality standards for WiFi Display applications, ensuring stable performance and compatibility across devices. Conducted thorough testing and optimisation to uphold Qualcomm's quality benchmarks. • Transition to XR Chipsets Execution: Progressed to XR (Extended Reality) chipset projects, contributing to the development and execution of testing frameworks for XR applications. Utilized Python and C++ to automate test processes, streamlining testing workflows and enhancing efficiency. • Tools & Technologies: Utilized Git for version control and Perforce for codebase management, supporting collaborative development and efficient project management across team

• Software engineer in Embedded Systems • Developed Software using C++ and Python. • Worked with protocols- SNMP, DCP/F, TL1. • Operated in a Linux OS environment. • Contributed in debugging in CLI of a Gateway

IoT Development: Experimented with IoT applications using the ESP8266 NodeMCU development board, contributing to the integration of various systems via a Wi-Fi Access Point. Programming & System Integration: Developed applications in C++ and Python, enabling seamless connectivity and data exchange between devices for efficient IoT solutions.

Circuit Simulation: Gained practical experience in circuit design by using Proteus for simulating and testing electronic circuits, enhancing understanding of circuit behavior prior to physical implementation. PCB Design: Experimented with Altium for PCB layout design, learning essential skills in layout optimization, component placement, and design verification for efficient, high-quality PCB production.

Coursework • CSE520-Computer Architecture II • EEE508-Image and Video Proc & Compression • EEE554 - Probability and Random Process • CSE551 - Foundations of Algorithms • EEE598 - Realtime DSP • EEE598 - Machine Learning Basics with Deployment to FPGAs • EEE505 - Time Frequency Signal Processing • EEE607 - Speech Processing and Compression • CEN599 - Thesis (Resource Management in OTA)