About
I am a Computer Vision and Robotics PhD researcher at Graz University of Technology in the Learning, Recognition & Perception group at the Institute of Visual Computing, supervised by Prof. Horst Bischof and Horst Possegger.
My research focuses on perception and prediction models for autonomous systems, with particular interests in motion forecasting, behavior prediction, and environment modeling. Passionate about advancing perception systems for robotics and autonomous vehicles, I specialize in developing efficient deep learning models and deploying them for practical use. My work spans both academic research and industrial R&D, utilizing real-world data and simulations to bring advanced models to deployment.
Publications
| DESCENT: Directed Edge Scene Encoding for Airport Surface Movement Prediction |
| SHARP: Short-Window Streaming for Accurate and Robust Prediction in Motion Forecasting |
| ASCENT: Transformer-Based Aircraft Trajectory Prediction in Non-Towered Terminal Airspace |
| Learn to Rank: Visual Attribution by Learning Importance Ranking |
| Streaming Real-Time Trajectory Prediction Using Endpoint-Aware Modeling |
| Lanes Are Not Enough: Enhancing Trajectory Prediction in Intralogistics Through Detailed Environmental Context |
| Leveraging Foundation Models for Labeling Custom Object Masks in LiDAR Point Cloud Sequences |
| Learning to Predict Mixed-Traffic Trajectories in Urban Scenarios from Little Training Data with Refined Environment Modeling |
| Efficient Motion Prediction: A Lightweight & Accurate Trajectory Prediction Model With Fast Training and Inference Speed |
| Action-By-Detection: Efficient Forklift Action Detection for Autonomous Mobile Robots in Warehouses |
| Studierfenster: An Open Science Cloud-Based Medical Imaging Analysis Platform |
| Design and Development of a Web-based Tool for Inpainting of Dissected Aortae in Angiography Images |
Academic Service
Conference Reviewer for major vision, robotics, AI, and transportation venues, including ICCV, ECCV, ICRA, IROS, NeurIPS, and IV.
