Shashwat Pandey
Master Thesis @ SICK AG | Edge AI for Robotics | Computer Vision & Autonomous Perception Professional
About Me
I am a Master's engineer in Perception, Computer Vision, and Edge AI for Robotics with over three years of R&D experience. My focus is translating complex vision models—such as 6D Pose Estimation and Semantic Segmentation—into reliable, real-time industrial solutions. I manage the full deployment lifecycle: from system development using ROS/ROS2, C++, and Python, to model optimization via TensorRT, ONNX, and Deepstream SDK. Currently, I am developing safe human-robot solutions at SICK Sensor Intelligence, leveraging embedded AI on 3D Time-of-Flight (ToF) cameras. I excel at integrating high-performance AI on constrained edge hardware.
Technical Expertise
Core Robotics & OS
- 95%
- 90%
- 95%
AI & Deployment
- 90%
- 85%
- 80%
Perception & Vision
- 90%
- 85%
- 95%
Edge AI & Hardware
- 85%
- 80%
- 75%
Sensors & Data
- 85%
- 80%
- 85%
Software Architecture
- 85%
- 80%
- 90%
Relevant Experience
Master Thesis Student (Safe Robotics / Edge AI)
Waldkirch, Germany | Sep 2025 - PresentSICK Sensor Intelligence
- Developing an Edge AI perception system for human detection using 3D Time-of-Flight (ToF) camera data (SICK safe Visionary2), prioritizing industrial safety and accuracy.
- Focused on model optimization and quantization using ONNXRuntime for real-time inference on embedded AI accelerators directly on camera hardware.
- Integrating real-time object detection, segmentation, and 6D pose estimation into a production pipeline.
Computer Vision Intern (Full-time)
Ditzingen, Germany | Mar 2025 - Aug 2025TRUMPF GmbH + Co. KG
- Implemented a robust industrial visual inspection pipeline using YOLOv8 and SegFormer-B3, achieving significant gains in segmentation accuracy for complex manufacturing geometries.
- Engineered a low-latency real-time system on Raspberry Pi, integrating camera capture and inference for quality inspection on constrained edge hardware.
- Designed advanced transfer learning strategies by fine-tuning on proprietary automotive datasets.
Werkstudent – Software Developer
Augsburg, Germany | Apr 2024 – Oct 2024KELO Robotics GmbH
- Migrated the entire C++ robotic software stack from ROS1 to ROS2 Rolling, including creating new packages and setting up **Gazebo simulation**.
- Led hardware setup and software integration for a Collaborative Mobile Robot, including **Python ARM API** integration.
- Optimized system performance by debugging memory consumption and lag issues, implementing **multi-threading** and analyzing node spinning behavior.
- Developed and maintained Docker containers for seamless testing across different ROS2 distribution versions.
Computer Vision Engineer (Full-time)
Noida, India | Apr 2022 - Jan 2023Kritikal Solutions
- Developed end-to-end 360° bird-eye view software stack as part of ADAS (calibration, stitching, blending).
- Explored Apple's TrueDepth cameras; developed multi-view 3D reconstruction using photogrammetry (SfM), ICP, and point-cloud registration.
- Deployed Deep Learning models on Nvidia TRITON server using Deepstream SDK for high-performance, real-time inference.
Computer Vision and Robotics Developer (Part-time)
London, United Kingdom | Sep 2020 - Jul 2021Swift Robotics
- Designed and implemented a ROS-based UV disinfection robot using Intel RealSense D455 depth cameras for autonomous room coverage and monitoring.
- Worked on 3D mapping, localization, and obstacle avoidance modules leveraging depth maps via Stereo-SGBM and WLS filtering.
- Established a secure wireless control system connecting Raspberry Pi nodes to a mobile app for real-time monitoring.
Key Projects
Person Following Mobile Robot (ROS2)
Sep 2023 - Jan 2024
A complete ROS2-based system for person following and obstacle avoidance. Utilized Intel RealSense D455 for sensor fusion (RGB+Depth), pose estimation, and safety maintenance.
Github RepositoryAI-based Anomaly Detection (Audio)
Dec 2023 - Jan 2024
Developed an anomaly detection system using autoencoders on audio features. Achieved 95.8% accuracy via reconstruction error, ideal for predictive maintenance.
Github RepositoryWinner Project: IBM Hack Challenge
Aug 2021 - Oct 2021
Developed a web app with an intelligent recommendation engine for OTT platforms, integrating real-time genre analytics and a chatbot with IBM Watson Assistant.
View DemoResearch & Education
DTLMV2 - Deep Transfer Learning Mask Classifier (Elsevier)
Published in ELSEVIER - Applied Soft Computing Journal (2022)
MobileNet V2 model trained using Imagenet weights on a custom dataset, achieving 97% accuracy. Showcases expertise in transfer learning and model validation for real-time systems.
[Full Text/Abstract Link]Average model of DC-DC converters
Research Paper (2022)
State space analysis of practical DC-DC converters to determine the high gain operating point, considering coil resistance. (Electrical Engineering Background)
[Full Text/Abstract Link]Education & Certifications
M.Sc. Autonomous Systems
Hochschule Bonn-Rhein-Sieg (H-BRS) | Mar 2023 - Present
B.Tech. Electrical & Electronics Engineering
Bharati Vidyapeeth's College of Engineering | 2018-2022
Key Certifications: