Hello, I'm Siva Vignesh Krishnan Chidambaram

Computer Vision & AI Engineer

Robotics engineer with a strong focus on state estimation, visual-inertial odometry, and Visual SLAM. ETH Zurich MSc graduate, currently Founding CV & AI Engineer at SE3 Labs in Munich — building GNSS-denied navigation and spatial AI pipelines for drones.

View My Work Get In Touch
Scroll to explore

About Me

My Journey

My journey began at IIT Kharagpur with a BTech in Mechanical Engineering, where I discovered my passion for robotics and intelligent systems. After graduating in 2021, I pursued a Master's in Robotics, Systems and Controls at ETH Zurich — one of the world's leading technical universities.

At ETH I worked across AMZ Racing, Sony (Robotics Perception Group), Sevensense Robotics, and Astrivis, building deep expertise in state estimation, Visual SLAM, and 3D computer vision. This foundation led me to Aegis Rider, where I developed VIO-based AR helmet tracking systems, and now to SE3 Labs in Munich as a Founding CV & AI Engineer building spatial AI for drones.

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

What Drives Me

I'm driven by a deep fascination with how machines perceive and understand the world. State estimation, visual-inertial odometry, and Visual SLAM are not just technical disciplines to me — they are the foundation for enabling robots and autonomous systems to operate reliably in the real world, without GPS, without perfect conditions.

From developing MPC controllers for autonomous racing cars at AMZ to building VIO-based AR tracking pipelines at Aegis Rider, every project has sharpened my belief that robust perception is the hardest and most important problem in robotics. I am drawn to systems where correctness and real-time performance are non-negotiable.

I remain deeply interested in advancing research and innovation at the intersection of perception and robotics systems, and I am always open to meaningful conversations, collaborations, and opportunities that push the boundaries of how machines understand and interact with the world.

Innovation First Pushing technological boundaries
Global Impact Solutions that scale worldwide
Future-Focused Building tomorrow's technology
Innovation Mindset Solving Tomorrow's Problems

Creating Impact

At AMZ Racing, I led the controls module as a team of four, developing an MPC controller for the Skidpad event and contributing to one of Europe's leading Formula Student autonomous racing teams across two seasons.

At Sony's Robotics Perception Group (under Prof. Davide Scaramuzza), I worked on depth estimation using an event camera and a laser projector scanned at speeds up to 350 Hz — pushing the state-of-the-art. At Sevensense Robotics, I built a full 6-DoF vision-based pallet localization and multi-object pose tracking system for autonomous mobile robots.

At Aegis Rider, I implemented a VIO-based tracking pipeline using an Extended Kalman Filter for real-time head and vehicle pose estimation under aggressive motion conditions. Now at SE3 Labs, I am building GNSS-denied navigation and spatial AI systems for drones as a founding engineer.

5+
Published Papers
Robotics, optimization & UAVs
4+
Years in Robotics & CV
Research to production systems
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 3D Computer Vision Computer Vision OpenCV PyTorch Deep Learning Object Detection Depth Estimation Augmented Reality 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

Founding engineer building GNSS-denied navigation and spatial AI pipelines for reliable drone operations in challenging environments. Optimizing perception and state estimation algorithms for real-time systems.

State Estimation Spatial AI Autonomous Drones C++
2024 — 2025

Software Engineer — State Estimation

Aegis Rider AG, Zurich

Developed Augmented Reality Technology Helmets for dynamic moving systems (motorcycles, race cars). Implemented a VIO-based tracking pipeline using an Extended Kalman Filter for real-time head and vehicle pose estimation under aggressive motion conditions.

Visual-Inertial Odometry Extended Kalman Filter Augmented Reality C++
Oct 2023 — Apr 2024

Thesis Student Researcher

Sevensense Robotics, Zurich

Developed a grayscale modular vision-based pallet localization system for docking of autonomous mobile robots in industrial settings. Implemented a 6-DoF pose estimation module and multi-object pose tracking module, tested extensively for robustness.

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

3D Computer Vision Intern

Astrivis, Zurich

Built a 3D face error evaluation pipeline and developed a Deep Learning pipeline for 3D face reconstruction on mobile phones.

3D Computer Vision Deep Learning PyTorch Python
Sep 2021 — Apr 2024

MSc Robotics, Systems and Controls

ETH Zurich

Specialized in state estimation, perception, and control systems. Worked across AMZ Racing (Controls Module Lead), Sony Robotics Perception Group (depth estimation with event cameras), and Sevensense Robotics (thesis). Won InCube Challenge 2022.

InCube Challenge Winner 2022
AMZ Racing Controls Module Lead
State Estimation Visual SLAM Control Systems Research
2017 — 2021

BTech, Mechanical Engineering

IIT Kharagpur

Graduated with a strong engineering foundation. Conducted research on Multi-Objective Bonobo Optimizer (co-authored publication), competed in multiple Inter-IIT Tech Meets, and interned at Niqo Robotics and UCL's Surgical Robot Vision Group.

Robotics Optimization Research Publications

Key Achievements

Featured Projects

Digital Twin of Switzerland

Digital Twin of Switzerland

Led a winning team to develop a comprehensive 3D mapping solution using real-time data from Swiss Post vehicles. Won the InCube Challenge 2022 among 20 international participants.

3D Mapping Digital Twins Python Computer Vision
GitHub Details
Autonomous Vehicle Systems

Autonomous Vehicle Systems

Advanced ADAS and computer vision algorithms for next-generation autonomous vehicles at Aegis Rider. Developing perception and control systems for safe autonomous driving.

Computer Vision C++ ROS ADAS
GitHub Details
AMZ Racing

AMZ Racing - Formula Student

Perception and control systems for high-speed autonomous racing with SLAM algorithms and trajectory optimization. Contributed to one of Europe's leading autonomous racing teams.

SLAM Control Systems Racing Robotics
GitHub Details
Computer Vision Pipeline

Real-time CV Pipeline

High-performance computer vision pipeline optimized for edge deployment with custom neural networks. Achieved real-time processing on embedded systems.

PyTorch OpenCV Edge Computing Neural Networks
GitHub Details

Let's Connect

Get In Touch

I'm always interested in discussing new opportunities, innovative projects, and collaborations in robotics, computer vision, and autonomous systems.

LinkedIn Profile
GitHub Portfolio
Google Scholar