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Basics
| Name | Hakan Yekta Yatbaz |
| Label | Lecturer (Assistant Professor) in Autonomous Systems |
| yatbazhakan@gmail.com | |
| Url | https://scholar.google.com/citations?user=5Q596f4AAAAJ&hl=en |
| Summary | Researcher in safe and resilient artificial intelligence for intelligent transport systems. Expertise in run-time monitoring, introspection, and uncertainty quantification for LiDAR-based 3D object detection in autonomous vehicles. |
Work
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2025.02 - Present Postdoctoral Research Assistant
WMG, University of Warwick
Leading research on self-assessment and run-time introspection for perception modules under adverse conditions in the EU EVENTS project.
- Developing self-assessment functionality for 2D/3D object detection
- Investigating early-layer neural activations in LiDAR-based detectors
- Collaborating with European partners on ADS pipelines
- Preparing publications and EU deliverables
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2020.12 - 2025.02 Research Assistant (part-time)
WMG, University of Warwick
Contributed to multiple EU projects on cooperative perception, sensor fusion, and remote operation for autonomous vehicles.
- Simulated autonomous tram using CARLA and YOLOv5
- Developed 5G-based remote vehicle operation system
- Implemented LiDAR fusion for Hi-Drive project
- Designed self-assessment systems for EVENTS project
Education
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2020.10 - 2024.10 Coventry, UK
PhD
University of Warwick
Engineering
- Run-time monitoring of perception module in automated driving systems
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2018.09 - 2020.08 Mersin, Turkey
MSc
Middle East Technical University (NCC)
Computer Engineering
- Lightweight CNN architectures for anomaly detection in e-health
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2013.09 - 2018.06 Mersin, Turkey
BSc
Middle East Technical University (NCC)
Computer Engineering
- P2P communication app for emergency localisation
Awards
- 2020.10.01
- 2018.09.01
- 2019.10.01
IEEE Xtreme 13.0 Programming Competition
IEEE
Ranked 5th in Turkey, 101st in Region 8, and 293rd worldwide.
Certificates
| Associate Fellow of Advance HE | ||
| Advance HE | 2024-01-01 |
Publications
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2024.01.01 Run-Time Introspection of 2D Object Detection in Automated Driving Systems Using Learning Representations
IEEE Transactions on Intelligent Vehicles
Proposed a novel introspection framework for 2D object detection in ADS.
-
2023.01.01 Introspection of DNN-Based Perception Functions in Automated Driving Systems
IEEE Transactions on Intelligent Transportation Systems
Surveyed state-of-the-art introspection approaches and identified open challenges.
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2021.03.01 Activity Recognition and Anomaly Detection in E-health Applications
IEEE Sensors Journal
Designed lightweight CNNs for anomaly detection in e-health data streams.
Skills
| Programming | |
| Python | |
| C++ | |
| C | |
| SQL |
| Machine Learning | |
| PyTorch | |
| OpenMMLab | |
| Ultralytics | |
| OpenPCDet |
| Tools | |
| ROS/ROS2 | |
| Autoware | |
| TensorRT | |
| CARLA | |
| Qt | |
| MQTT | |
| GStreamer |
| Specialisation | |
| Object Detection | |
| Runtime Monitoring | |
| Sensor Fusion | |
| Safe AI |
Languages
| Turkish | |
| Native |
| English | |
| C1 |
Interests
| Artificial Intelligence Safety | |
| Runtime Monitoring | |
| Neural Introspection | |
| Uncertainty Quantification |
| Autonomous Vehicles | |
| 3D Object Detection | |
| Sensor Fusion | |
| LiDAR Perception |
References
| Prof. Enver Ever | |
| Department of Computer Engineering, METU NCC — eever@metu.edu.tr |
| Dr. Roger Woodman | |
| WMG, University of Warwick — r.woodman@warwick.ac.uk |
| Prof. Adnan Yazici | |
| Nazarbayev University — adnan.yazici@nu.edu.kz |
| Dr. Konstantinos Koufos | |
| Queen’s University Belfast |
Projects
- 2023.01 - Present
EU EVENTS Project
Developing resilient perception and decision-making pipelines for automated driving systems under adverse weather and environmental conditions.
- Self-assessment modules
- ADS pipeline integration
- 2022.01 - 2023.12
Hi-Drive Project
Advancing SAE Level 4 automated driving systems through cooperative perception and real-time LiDAR fusion.
- Early and late fusion
- Infrastructure-based perception
- 2021.01 - 2022.12
5G-CAT Project
Developing remote fleet monitoring and drive-by-wire control system for autonomous tram over 5G.
- ROS-based system
- Qt interface