Andreas Kriegler's CV

Summary

PhD student in Computer Vision at TU Wien, set to finish in late 2026.

I am a PhD student in Computer Vision at the CVL at TU Wien. My supervisor is Prof. Margrit Gelautz. My research is funded by the AIT Austrian Institute of Technology where I am further advised by Csaba Beleznai.

My research lies in the intersection of classical Computer Vision, Deep Learning and Computer Graphics. The goal is to develop novel methods for highly generic object pose estimation. We are specifically interested in the geometry of objects and exploit rendering engines to generate synthetic data.

Before joining the PhD program, I received my M.Sc. and B.Sc. degrees in Mechatronics/Robotics from the UAS Technikum Wien, both with distinction.

Education

TU Wien, Dr. techn. (PhD) in Computer Science

University of Applied Sciences Technikum Wien, M.Sc. (with distinction) in Mechatronics/Robotics

University of Applied Sciences Technikum Wien, B.Sc. (with distinction) in Mechatronics/Robotics

University of Natural Resources and Life Sciences Vienna, B.Sc. in Civil Engineering (discontinued)

Experience

AIT Austrian Institute of Technology, PhD Student

TU WIEN, Univ. Research Assistant (external)

AIT Austrian Institute of Technology, Computer Vision Engineer

AIT Austrian Institute of Technology, Diploma Student

SMS Group, Application and Control Engineering Intern

Customer Care Solutions, Call Center Agent

Vienna Red Cross, Paramedic

Academic Work

I Can't Believe It's Not Better Initiative

Teaching (TU Wien, guest lectures)

Reviewing

Editor

Summer Schools

International Computer Vision Summer School (ICVSS)

British Machine Vision Association Computer Vision Summer School

Awards

Scholarships

Certificates

Languages

References

Publications

Review Paper: Body Movement Mirroring and Synchrony in Human-Robot Interaction (10.1145/3682074)

PrimitivePose: Generic Model and Representation for 3D Bounding Box Prediction of Unseen Objects (10.1142/S1793351X23620027)

Towards Scene Understanding for Autonomous Operations on Airport Aprons (10.1007/978-3-031-27066-6_11)

PrimitivePose: 3D Bounding Box Prediction of Unseen Objects via Synthetic Geometric Primitives (10.1109/IRC55401.2022.00040)

Paradigmatic Revolutions in Computer Vision (https://drive.google.com/file/d/1ItDGcljAQOYo-HKHJLcC4gAgapCIQPns/view)

Pose-aware object recognition on a mobile platform via learned geometric representations (10.23919/ASCC56756.2022.9828370)

Visual Semantic Context Encoding for Aerial Data Introspection and Domain Prediction (10.1007/978-3-031-04881-4_34)

Evaluation of Monocular and Stereo Depth Data for Geometry-Assisted Learning of 3D Pose (10.3217/978-3-85125-869-1-01)

The Aircraft Context Dataset: Understanding and Optimizing Data Variability in Aerial Domains (10.1109/ICCVW54120.2021.00426)

Artificial Neural Networks Based Place Categorization (10.1007/978-3-030-62784-3_17)

Vision-based Docking of a Mobile Robot (10.3217/978-3-85125-752-6-03)

FH Technikum Wien: Artificial Neural Networks Based State Transition Modeling and Place Categorization (https://mechatronik-plattform.at/wp-content/uploads/2025/04/Tagungsband_2018_FH-Campus02.pdf)

Theses

Visual Semantic Context Encoding for Data Harvesting and Domain Prediction (https://permalink.obvsg.at/ftw/AC16098872)

Artificial Neural Networks based State Transition Modeling and Place Categorization (https://www.researchgate.net/publication/352211259_Artificial_Neural_Networks_based_State_Transition_Modeling_and_Place_Categorization)

Neuentwicklung der Schlackeauswurferkennung auf der Basis von MATLAB (https://www.researchgate.net/publication/352211347_Neuentwicklung_der_Schlackeauswurferkennung_auf_der_Basis_von_MATLAB)