Sitiveni Nawalowalo

42 Korolevu Lane, Suva, Fiji
+679 331 4827 | sitiveni.nawalowalo@email.com
https://linkedin.com/in/sitiveninawalowalo

PROFESSIONAL SUMMARY

Accomplished Staff Research Engineer with extensive experience in advanced algorithm development, embedded systems design, and machine learning applications for resource-constrained environments. Proven track record of leading innovative R&D initiatives from concept through production, specializing in computer vision, sensor fusion, and low-power embedded solutions. Expert in translating cutting-edge research into scalable, production-ready systems.

PROFESSIONAL EXPERIENCE

Staff Research Engineer
TechCore Systems, San Jose, California
January 2020 – Present

• Lead research and development of novel algorithms for embedded computer vision systems, achieving 40% reduction in power consumption while maintaining real-time performance on microcontroller platforms
• Architect and implement machine learning pipelines for sensor data processing, deploying models on resource-constrained devices with sub-100ms inference latency
• Direct cross-functional teams of 8+ engineers in developing firmware solutions for next-generation IoT products, resulting in three patent applications
• Design and execute comprehensive simulation frameworks for stress testing embedded software across diverse environmental conditions and edge cases
• Collaborate with product teams to transition research prototypes into production systems, successfully delivering five major product features over four years
• Mentor junior engineers and researchers in algorithm optimization, embedded C development, and systems design best practices

Senior Research Engineer
Quantum Innovations Ltd., Mountain View, California
March 2016 – December 2019

• Developed advanced image processing algorithms for low-power embedded platforms, reducing computational complexity by 35% through novel optimization techniques
• Implemented sensor fusion algorithms combining multiple data streams to improve system accuracy and robustness in challenging operational scenarios
• Conducted extensive research on dilution of precision effects in positioning systems, publishing findings in peer-reviewed conferences
• Designed and prototyped embedded software architectures for real-time signal processing applications using C++ and Embedded C
• Performed raw data analysis and developed MATLAB simulation tools to validate algorithm performance prior to hardware implementation
• Collaborated with hardware teams to optimize firmware-hardware interfaces, achieving 25% improvement in system throughput

Research Engineer
Nexus Engineering Solutions, Palo Alto, California
June 2013 – February 2016

• Developed machine learning models for automated sensor calibration and anomaly detection in embedded systems
• Implemented computer vision algorithms for object detection and tracking on ARM-based microcontrollers
• Created comprehensive test frameworks for validating algorithm performance across diverse operating conditions
• Contributed to software development lifecycle including requirements analysis, design documentation, code reviews, and integration testing
• Participated in innovation workshops and generated multiple invention disclosures related to energy-efficient computing techniques

EDUCATION

Master of Science in Computer Science
Stanford University, Palo Alto, California
Graduated: May 2013
Concentration: Machine Learning and Computer Vision
Thesis: "Energy-Efficient Algorithms for Real-Time Image Processing on Embedded Platforms"

Bachelor of Science in Electrical Engineering
University of California, Berkeley, Berkeley, California
Graduated: May 2011
Concentration: Embedded Systems and Signal Processing

TECHNICAL SKILLS

Programming Languages: C++, Embedded C, MATLAB, Python
Specializations: Machine Learning, Computer Vision, Image Processing, Algorithm Development
Embedded Systems: Microcontrollers, Firmware Development, Low-power Design, Real-time Systems
Tools & Platforms: Embedded Software Development, Simulation Frameworks, Systems Design
Domains: Sensor Fusion, Energy Technology, R&D Engineering, Innovation

PUBLICATIONS & PATENTS

• Co-author of 7 peer-reviewed conference papers on embedded machine learning and computer vision
• 3 pending patents in low-power algorithm optimization and sensor processing techniques
• Regular presenter at industry conferences on embedded AI and energy-efficient computing

PROFESSIONAL AFFILIATIONS

• Member, Institute of Electrical and Electronics Engineers (IEEE)
• Member, Association for Computing Machinery (ACM)