Hello, I'm Siva Vignesh Krishnan Chidambaram

Computer Vision & AI Engineer

Founding Computer Vision & AI Engineer at SE3 Labs in Munich, focused on state estimation, visual-inertial odometry, and spatial AI for GNSS-denied autonomy. My work spans research and product teams including Aegis Rider, Sevensense Robotics, Astrivis, Sony, and AMZ Racing.

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About Me

My Journey

My path into robotics started at IIT Kharagpur, where I studied Mechanical Engineering and became interested in systems that have to work outside carefully controlled lab settings. That interest took me to ETH Zurich for an MSc in Robotics, Systems and Controls, where I went deeper into perception, state estimation, and controls.

Since then, I have worked across research labs, startups, and high-performance engineering teams including Sony's Robotics Perception Group, Sevensense Robotics, Astrivis, AMZ Racing, Aegis Rider, and now SE3 Labs. The common thread has been building perception systems that remain reliable under motion, uncertainty, and real-time constraints.

2017 BTech, IIT Kharagpur
2021 MSc Robotics, ETH Zurich
2024 State Estimation Engineer, Aegis Rider
2026 Founding CV & AI Engineer, SE3 Labs
Academic Excellence IIT KGP → ETH Zurich

What Drives Me

I am motivated by perception problems where geometry, sensor fusion, and deployment constraints all matter at once. State estimation, visual-inertial odometry, and 3D vision are compelling to me because they turn noisy sensor streams into something actionable enough for robots to trust.

From developing MPC controllers for autonomous racing cars at AMZ Racing to building VIO-based AR tracking pipelines at Aegis Rider, each project has reinforced the same lesson: reliable autonomy is won in the details of calibration, latency, robustness, and system integration.

I am most drawn to teams working on drones, mobile robots, and embodied AI systems where perception is directly tied to safety, performance, and product quality.

Reliable Autonomy Robustness over demos
Research to Product Turning ideas into shipped systems
High-Performance Systems Real-time by design
Innovation Mindset Solving Tomorrow's Problems

Creating Impact

At AMZ Racing, I worked on path planning and high-level controls before leading a four-person controls module. That experience sharpened my ability to build fast, reliable systems under competition pressure.

At Sony's Robotics Perception Group, I worked on depth estimation using an event camera with a laser projector scanned at up to 350 Hz. At Sevensense Robotics, I built a grayscale pallet localization pipeline with 6-DoF pose estimation and multi-object tracking for autonomous mobile robot docking.

At Aegis Rider, I implemented a VIO-based Extended Kalman Filter pipeline for AR helmets operating on motorcycles and cars. Today at SE3 Labs, I work on GNSS-denied navigation and spatial AI for drones as a founding engineer.

10+
Research & Engineering Roles
Across labs, startups, and competition teams
5+
Research Outputs
Publications, presentations, and technical projects
1st
InCube Challenge Winner
Among 20 international teams
Proven Results Innovation That Matters

Technical Expertise

Technologies and tools I work with to bring ideas to life

Python C++ MATLAB State Estimation Visual SLAM Visual-Inertial Odometry Sensor Fusion Extended Kalman Filter GNSS-Denied Navigation 6-DoF Pose Estimation Pose Tracking 3D Computer Vision Computer Vision OpenCV PyTorch Deep Learning Object Detection Depth Estimation Augmented Reality Event Cameras Robotics ROS Control Systems MPC Path Planning Autonomous Drones Git Linux Docker CI/CD
Expert
Advanced
Intermediate

Professional Experience

Current
Jan 2026 — Present

Founding Computer Vision & AI Engineer

SE3 Labs, Munich

Optimizing perception and state estimation algorithms for real-time systems, with a focus on efficient GNSS-denied navigation and spatial AI pipelines for drone operations in challenging environments.

State Estimation Spatial AI GNSS-Denied Navigation Autonomous Drones
Jun 2024 — Dec 2025

Software Engineer — State Estimation

Aegis Rider AG, Zurich

Developed augmented reality helmets for dynamic moving systems such as motorcycles and cars. Implemented a VIO-based tracking pipeline using an Extended Kalman Filter for real-time head and vehicle pose estimation under aggressive motion.

Visual-Inertial Odometry Extended Kalman Filter Augmented Reality Sensor Fusion
Oct 2023 — Apr 2024

Thesis Student Researcher

Sevensense Robotics, Zurich

Developed a grayscale modular vision-based pallet localization system for docking applications of autonomous mobile robots in indoor industrial settings. Implemented a 6-DoF pose estimation module and multi-object pose tracking module, and improved the proof of concept through robustness testing.

6-DoF Pose Estimation Multi-object Tracking Industrial Robotics Computer Vision
Mar 2023 — Aug 2023

3D Computer Vision Intern

Astrivis, Zurich

Worked on a 3D face error evaluation pipeline and built a deep learning pipeline for 3D face reconstruction on mobile phones.

3D Face Reconstruction Deep Learning Mobile Vision Python
Nov 2022 — Mar 2023

Graduate Student Researcher

Sony x Robotics Perception Group, Zurich

Worked with Sony and the Robotics Perception Group under Prof. Davide Scaramuzza on depth estimation using an event camera and a laser projector scanned at up to 350 Hz.

Event Cameras Depth Estimation Laser Scanning Research
Oct 2021 — Aug 2023

Autopilot Software Engineer → Controls Module Lead

AMZ Racing, ETH Zurich

Worked as a path planning and high-level controls engineer for Formula Student Driverless, then led a four-person controls module. Developed an MPC controller for the Skidpad event, reviewed previous seasons, and proposed improvements for the 2022 stack.

Path Planning MPC Autonomous Racing Control Systems
Apr 2021 — Aug 2021

Computer Vision Intern

Niqo Robotics, Bengaluru

Trained and fine-tuned object detection models for crop detection, improving performance on edge cases. Also developed a simulator to visualize weeding blade behavior for faster robot software debugging.

Object Detection Deep Learning Simulation Agricultural Robotics

Key Achievements

Featured Projects

Digital Twin of Switzerland

Digital Twin of Switzerland

Led the winning InCube Challenge 2022 concept for building a digital twin of Switzerland using data collected through Swiss Post vehicles and large-scale geospatial mapping workflows.

Digital Twins 3D Mapping Geospatial Data Computer Vision
GitHub Details
VIO-Based AR Helmet Tracking

VIO-Based AR Helmet Tracking

Built a visual-inertial tracking pipeline for augmented-reality helmets, estimating head and vehicle pose in real time for motorcycles and cars under aggressive motion.

VIO Extended Kalman Filter Augmented Reality Sensor Fusion
GitHub Details
AMZ Racing

AMZ Racing Driverless Stack

Worked on path planning and high-level controls, then led the controls module. Developed an MPC controller for Skidpad and helped shape a faster, more reliable driverless stack.

Path Planning MPC Control Systems Autonomous Racing Robotics
GitHub Details
Vision-Based Pallet Localization

Vision-Based Pallet Localization

Developed a grayscale modular pallet localization system for indoor AMR docking, including 6-DoF pose estimation and multi-object pose tracking for industrial settings.

6-DoF Pose Multi-Object Tracking Industrial Robotics Computer Vision
Related Code Details
Event-Camera Depth Sensing

Event-Camera Depth Sensing

Worked with Sony and ETH Zurich's Robotics Perception Group on depth estimation using an event camera and a laser projector scanned at up to 350 Hz.

Event Cameras Depth Estimation Laser Projection Research
GitHub Details
Agricultural Robotics Perception

Agricultural Robotics Perception

Improved crop-detection models at Niqo Robotics and built a simulator for weeding blade behavior to accelerate debugging in agricultural robots.

Object Detection Agricultural Robotics Simulation Computer Vision
GitHub Details

Let's Connect

Get In Touch

I work at the intersection of robotics, computer vision, and state estimation. If you are building perception, navigation, or autonomy systems, email or LinkedIn is the fastest way to reach me.

sivavigneshk@gmail.com
LinkedIn
GitHub

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