جست‌وجوی استاد و پژوهشگر

Torsten Sattlerمشاهده پروفایل

استاد پژوهشی

• 3D computer vision
• Machine learning
• Image-based localization
• +۱۰ مورد دیگر

Torsten Sattler is a Senior Researcher at the Czech Institute of Informatics, Robotics and Cybernetics (CIIRC) at the Czech Technical University in Prague (CTU), where he heads the Spatial Intelligence group. Previously, he was a tenured Associate Professor at Chalmers University of Technology in Sweden and spent five years as a PostDoc and Senior Researcher at ETH Zurich in Switzerland. He received his PhD from RWTH Aachen University in Germany. His research focuses on the intersection of 3D computer vision and machine learning, with specific interests in image-based localization, 3D mapping and reconstruction, neural scene representations, and applications in robotics and AR/VR. He aims to make localization and mapping algorithms more robust by incorporating higher-level scene understanding. Dr. Sattler has published extensively at top computer vision conferences including CVPR, ICCV, and ECCV, with recent papers focusing on robust visual localization in changing environments, neural scene representations, and 3D reconstruction. His work has direct applications in autonomous systems and augmented reality. Best Paper Candidate at CVPR 2021 Best Paper Award at Photogrammetric Image Analysis 2019 Multiple Outstanding Reviewer Awards from 2015-2021 Ranked among top-10 computer scientists in Czech Republic by Research.com He currently supervises five PhD students and has served in various leadership roles including program chair for ECCV 2024, general chair for 3DV 2022, and area chair for multiple major conferences. His lab benefits from connections to the RICAIP Centre, one of the largest EU projects in AI and Industry 4.0, providing access to state-of-the-art infrastructure and industrial collaborations.

Philipp Bruneمشاهده پروفایل

استاد

• Artificial Intelligence
• Facial Emotion Recognition
• Cybersecurity
• +۵ مورد دیگر

Professor Dr. Philipp Brune serves as a prominent academic leader at Neu-Ulm University of Applied Sciences (HNU), holding multiple key positions including Academic Head of TTZ Günzburg, Head of the Master of Artificial Intelligence and Data Analytics program, Head of the Centre for Secure IT Applications and Infrastructures, and Head of the Institute of Agile Product and System Development within the Faculty of Information Management. His career demonstrates a notable transition from physics research (evident in his early 2000-2004 publications) to his current focus on cutting-edge information systems and artificial intelligence. Dr. Brune's research program spans several interconnected domains with particular emphasis on facial emotion recognition systems, legacy system modernization, and secure IT infrastructure development. His work investigates fundamental challenges in AI interpretability, data quality for emotion recognition, and practical approaches to modernizing legacy applications. He has made substantial contributions to understanding the limitations of current facial expression recognition technologies and developing more robust, trustworthy alternatives. Analysis of his recent publications reveals a clear research trajectory toward explainable and trustworthy AI systems, with increasing sophistication in addressing data quality issues and model interpretability challenges. His work bridges theoretical computer science with practical applications across healthcare, marketing, and smart city technologies, demonstrating strong translational research capabilities. As an educator, Dr. Brune has developed innovative pedagogical approaches specifically tailored for non-computer science majors, with research examining student motivation in programming courses and effective methods for teaching cybersecurity concepts. His leadership in the Master of Artificial Intelligence and Data Analytics program shapes curriculum development for next-generation AI professionals. Dr. Brune directs multiple research initiatives including the Centre for Secure IT Applications and Infrastructures, which addresses critical cybersecurity challenges in modern IT environments, and the Institute of Agile Product and System Development, which explores innovative software development methodologies. His collaborative research approach is evident through extensive co-authorship networks spanning multiple institutions and disciplines.

• Computer Vision
• Machine Learning
• Adversarial Robustness
• +۴ مورد دیگر

Jenny Schmalfuss is a Doctoral Researcher at the Institute for Visualization and Interactive Systems (VIS) within the Faculty of Computer Science, Electrical Engineering, and Information Technology at the University of Stuttgart. She is also a scholar of the International Max Planck Research School for Intelligent Systems (IMPRS-IS). Her research focuses on computer vision and machine learning, specifically investigating robustness of deep learning methods against distribution shifts and adversarial attacks. Her primary research interests include computer vision, machine learning, and the intersection of these fields with robustness analysis. She has made significant contributions to understanding weaknesses in vision language models and motion estimation techniques like optical flow. Her work explores how to quantify and improve model robustness through adversarial testing frameworks. Her publication record shows a strong focus on adversarial robustness in motion estimation, with multiple papers at top-tier conferences including CVPR, ICCV, and ECCV. Recent work includes the PARC framework for analyzing vision language models (CVPR 2025), Distracting Downpour for weather-based adversarial attacks (ICCV 2023), and foundational work on adversarial snow attacks (ECCV AROW 2022). Poster Award at ICVSS 2023 Best Paper Award at ECCV AROW Workshop 2022 Best SimTech Bachelor's thesis 2021 (supervised) Jenny actively supervises numerous Master's theses, Bachelor's theses, and research projects annually, focusing primarily on optical flow robustness, adversarial attacks, and motion estimation. She has also completed an internship with NVIDIA's Autonomous Vehicle Perception Research Group in Santa Clara, CA, USA from April to November 2024, and previously worked as a research intern at the National University of Singapore and University of Houston. She teaches regularly in the Computer Vision and Intelligent Systems program, organizing colloquia and supervising seminars on Recent Advances in Computer Vision since 2021. Her teaching portfolio includes coordinating tutorials for Computer Vision and Imaging Science courses.