Fuzail Palnak is a data scientist with nine years’ experience applying machine learning and computer vision to geospatial and robotics problems, currently working at SLB from Pune. He has a strong track record at TomTom and Joanneum Research building production-ready pipelines for semantic segmentation, LiDAR-based navigation, and precision mapping, often deploying models with Docker, ROS2, and NVIDIA Jetson optimizations. His work spans research and engineering—automating vegetation monitoring, real-time building-footprint extraction, and bandwidth-efficient image capture on drones—demonstrating an ability to move prototypes into constrained, real-world deployments. He holds a Master’s in Computer Science with distinction from TU Graz and a first-class bachelor’s in Computer Engineering, combining rigorous academics with applied R&D. Notably, he designs compact, inference-optimized systems (e.g., ICP-based pose estimation and on-device CNNs) that balance accuracy with mission constraints. Colleagues would describe him as a practitioner who bridges remote sensing research and scalable fielded solutions.
9 years of coding experience
7 years of employment as a software developer
Master's degree, Computer Science, mit Auszeichnung bestanden – Pass with distinction, Master's degree, Computer Science, mit Auszeichnung bestanden – Pass with distinction at Technische Universität Graz
A Library build with a purpose to have single line console print across project and avoid unnecessary console prints. The Library has the capability to handle all print statements in one line across the project
Contributions:1 release, 16 commits, 10 PRs in 10 months
Contributions:16 commits, 14 pushes, 1 branch in 2 years 2 months
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