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sherin joseph roy

@SHERIN JOSEPH ROY

Sherin Joseph Roy

I build software that drives cars. Currently developing a vision-first, Phase-2 ...
Bangalore, India sherinjosephroy.link Joined November 2025
811 Points • 14 Badges • 5 Connections • 5 Followers • 24 Following
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About

I build software that drives cars. Currently developing a vision-first, Phase-2 autonomous prototype on a Tata EV platform. My focus is on End-to-End Behavioral Cloning—bypassing t... Show more

Language & Tools

Languages & Technologies:

Core Languages: Python (Deep Learning / Data Pipelines), C++ (Real-time Control / ROS 2), C (Embedded Microcontrollers)

AI & Computer Vision: PyTorch, OpenCV, NVIDIA TensorRT (Edge Optimization)

Robotics & Middleware: ROS 2 (Humble/Foxy), Linux (Ubuntu), MCAP (Data Logging & Curation)

Vehicle Networks: High-Speed CAN, CAN-FD, SavvyCAN, Vector/SocketCAN

Hardware Compute: NVIDIA Jetson Architecture (Orin NX / AGX), Teensy 4.x (Real-time MITM Gateways)

Sensors & Interfaces: GMSL2 Cameras (e-con Systems), RTK GPS / IMU Sensor Fusion, I2C / SPI / UART

Currently Exploring

Trying to build a self-driving car from Bangalore, India. Specifically, building a Phase-2 Drive-by-Wire prototype on an EV platform using end-to-end behavioral cloning and NVIDIA Jetson edge compute.

Achievements

Deployed a highly optimized, 250k-parameter PyTorch behavioral cloning model (PilotNet) onto an NVIDIA Jetson Orin for real-time edge inference.

Fun Fact

My self-driving AI’s absolute hardest edge-cases aren't rain or unmarked lanes—they are Bangalore auto-rickshaws cutting across three lanes of traffic.

Random Dev Quote

In web dev, a bug crashes a browser. In autonomous vehicle dev, a bug crashes tons of metal.

Latest Video

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Contributions
Joined: 7 months (since Nov 14, 2025)
Full Name: Sherin Joseph Roy
Headline:
About: I build software that drives cars. Currently developing a vision-first, Phase-2 autonomous prototype on a Tata EV platform. My focus is on End-to-End Behavioral Cloning—bypassing traditional modular robotics pipelines by training lightweight convolutional neural networks (like PilotNet) to map raw camera pixels directly to physical steering and braking commands.

I handle the full AV stack: from hardware integration (NVIDIA Jetson, GMSL cameras, RTK GPS) to CAN bus reverse-engineering, data pipeline curation, and deep learning inference on edge compute.

Core Stack: Python, C++, ROS 2, PyTorch, OpenCV, CAN-FD.
Location: Bangalore, India
Website: sherinjosephroy.link
Languges & Tools: Languages & Technologies:

Core Languages: Python (Deep Learning / Data Pipelines), C++ (Real-time Control / ROS 2), C (Embedded Microcontrollers)

AI & Computer Vision: PyTorch, OpenCV, NVIDIA TensorRT (Edge Optimization)

Robotics & Middleware: ROS 2 (Humble/Foxy), Linux (Ubuntu), MCAP (Data Logging & Curation)

Vehicle Networks: High-Speed CAN, CAN-FD, SavvyCAN, Vector/SocketCAN

Hardware Compute: NVIDIA Jetson Architecture (Orin NX / AGX), Teensy 4.x (Real-time MITM Gateways)

Sensors & Interfaces: GMSL2 Cameras (e-con Systems), RTK GPS / IMU Sensor Fusion, I2C / SPI / UART
Currently Exploring: Trying to build a self-driving car from Bangalore, India. Specifically, building a Phase-2 Drive-by-Wire prototype on an EV platform using end-to-end behavioral cloning and NVIDIA Jetson edge compute.
Achievements: Deployed a highly optimized, 250k-parameter PyTorch behavioral cloning model (PilotNet) onto an NVIDIA Jetson Orin for real-time edge inference.
Fun Fact: My self-driving AI’s absolute hardest edge-cases aren't rain or unmarked lanes—they are Bangalore auto-rickshaws cutting across three lanes of traffic.
Random Dev Quote: In web dev, a bug crashes a browser. In autonomous vehicle dev, a bug crashes tons of metal.
Latest Video: https://youtu.be/xc3Cs2sERjI?si=C4UB54FZ0P0CQxyq
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