Andras Palffy
Developing AI For Radars Co-Founder at Delft University of Technology
Delft, South Holland, Netherlands
Summary
👤
Senior🎓
Top SchoolAndras Palffy is a machine perception and AI specialist with 11 years’ experience focused on radar-based detection for intelligent vehicles and smart-city applications. As Co-Founder of Perciv AI and a postdoctoral researcher at Delft University of Technology, he bridges deep academic research in multi-sensor road-user detection with product-focused algorithm development for embedded systems. His PhD work uniquely emphasizes vulnerable road user detection using cameras, LiDAR and especially radar, reflecting a rare combination of signal-processing rigor and practical ML deployment. Prior industry roles developing embedded detectors for traffic and pedestrian monitoring sharpen his ability to turn research prototypes into robust real-world solutions. Based in Delft, he blends entrepreneurial drive with a strong academic pedigree from Delft, Cranfield and Pázmány Péter Catholic University.
11 years of coding experience
3 years of employment as a software developer
Master’s Degree, Computer Science Engineer, honours, Master’s Degree, Computer Science Engineer, honours at Pázmány Péter Catholic UniversityDoctor of Philosophy - PhD, Radar based road user detection in intelligent vehicles, Doctor of Philosophy - PhD, Radar based road user detection in intelligent vehicles at Delft University of TechnologyMaster’s Degree, Computational and Software Techniques in Engineering | Digital Signal and Image Processing, 80%, Master’s Degree, Computational and Software Techniques in Engineering | Digital Signal and Image Processing, 80% at Cranfield University
Github Skills (66)
opencv10
image-processing10
deep-learning10
computer-vision10
3d-detection10
kitti10
lidar10
point-cloud10
development-kit10
optical-flow10
automotive10
object-detection9
python9
3d-object-detection9
low-level9
Programming languages (7)
Github contributions (5)
tudelft-iv/view-of-delft-dataset
Apr 2022 - Oct 2022
This repository shares the documentation and development kit of the View of Delft automotive dataset.
Contributions:85 commits, 4 PRs, 62 pushes in 5 months
development-kitautomotivedelftdatasetshares
tudelft-iv/RTCnet
Nov 2019 - Jul 2021
RTCnet is a radar based, single-frame, multi-class detection method for moving road users (pedestrian, cyclist, car), which utilizes low-level radar cube data.
Contributions:16 commits, 4 PRs, 15 pushes in 1 year 7 months
cuberoad-usersframepedestrianradar
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