👋 Hi, I’m Ashwattha Phatak

🎓 M.S. in Computer Science @ NC State University (GPA 3.93)
💻 Specializing in Operating Systems, Embedded Systems, and Autonomous Platforms
📍 Raleigh, NC | 📧 ashwatthap@gmail.com | 🔗 LinkedIn | 💾 GitHub

🧭 About Me

I’m a systems-minded software engineer passionate about building efficient, fault-tolerant embedded and autonomous systems.
I enjoy working close to hardware — debugging drivers, optimizing schedulers, and building OTA infrastructures for edge devices.
Currently exploring how data representation and memory management shape performance in autonomous driving and robotics.

⚙️ Technical Skills

Languages: Python, C++, C, Golang, Bash
Embedded & OS: Embedded Linux (L4T, OpenWRT), RTOS, Xinu OS, Device Drivers
Frameworks & Libraries: ROS (1/2), OpenCV, Open3D, TensorFlow, PyTorch
Domains: Operating Systems, Embedded Systems, Advanced Robotics, Computer Networks, Real-Time Systems, Autonomous Perception
Tools & Platforms: NVIDIA Jetson, Docker, QEMU, Git

💼 Experience

🛰️ Precision Sustainable Agriculture — Systems Software Intern

Raleigh, NC | May 2025 – Present

• Built one-touch commissioning workflows for Wi-Fi modems, switches, and Jetson AGX Orin devices for seamless hardware setup.
• Designed and deployed OTA update infrastructure for NVIDIA Jetson devices, enabling touchless software deployment to field units.
• Implemented real-time health monitoring for OAK-D cameras, GPS modules, SMB protocols, and network switches.
• Migrated from ROS1 rosbag → modern logging pipeline, improving data throughput and reliability.

🤖 Systems Lab – Dr. Yoon Man-ki | Research Assistant, Autonomous Systems

Jan 2025 – May 2025

• Investigated LiDAR range-image compression and accountability for autonomous driving data.
• Benchmarked compression pipelines for machine learning tasks to optimize storage and latency.

💼 State Street Corporation — Software Engineer / Automation Intern

Bangalore, India | Jan 2023 – Jul 2024

• Automated infrastructure monitoring and log parsing tools (Python, Bash), saving 10+ hours per week.
• Improved change success rate by 70% for critical financial systems and authored 150+ technical articles.
• Developed React.js dashboards for reliability analytics and reduced cloud migration incidents by 20%.

🧩 Projects

🔹 DeltaFS – Distributed Versioned File System

C++, Linux, Sockets, Multithreading

• WAFL-inspired copy-on-write file system with block-level delta storage and crash-consistent journaling.
• Built distributed metadata replication layer for multi-node consistency and fast recovery.

🔹 Parallelized PointPillars

Python, CUDA, C++

• GPU-optimized 3D object detection pipeline using TensorRT (31× speedup over serial baseline).
• Designed parallel voxelization and NMS modules with < 2% accuracy drop.

🔹 Xinu OS Kernel Development

C, Xinu, QEMU

• Implemented new round-robin schedulers with Linux-like fairness (100% process completion).
• Added demand paging with multi-level page tables (16 MB → 4 GB virtual space, 40% fewer page faults).

🔹 Autonomous Vehicle Stop Sign Detection

CARLA, TensorFlow

• CNN-based traffic sign classifier achieving 98.7% accuracy.
• Integrated probability-based control logic for slowdown (60%) and stop (90%).

🎯 Interests

Embedded Systems • Kernel Design • Autonomous Robotics • Systems Reliability • Open-Source Software

📫 Let’s Connect

💌 ashwatthap@gmail.com | 🌐 LinkedIn | 💻 GitHub