Find Academic Supervisors

Benjamin BusamView profile

Researcher

• 3D Computer Vision
• Multi-Modal Sensor Fusion
• Collaborative Robotics
• +6 more

Dr. Benjamin Busam is a Senior Research Scientist at the Technical University of Munich , affiliated with the Chair for Computer Science Applications in Medicine under Prof. Nassir Navab. Starting September 2025, he will hold the Professorship for Photogrammetry and Remote Sensing at TUM. His career includes leadership roles at FRAMOS Imaging Systems and Huawei Research in London. Education: Mathematics (TUM), Mathematics and Physics (ParisTech, University of Melbourne), PhD in Mathematics (TUM, 2014) His research focuses on 3D computer vision , multi-modal sensor fusion , and their applications in collaborative robotics and augmented reality . He specializes in projective geometry , 6D pose estimation , and neural radiance fields , with a particular emphasis on photometrically challenging environments. Recent publications highlight advancements in 3D scene understanding , neural rendering , and medical imaging , often leveraging machine learning and vision-language models . His work has been recognized through awards like the EMVA Young Professional Award (2015) and Innovation Pioneer of the Year (2019) , along with multiple Outstanding Reviewer distinctions at leading conferences. Dr. Busam has supervised numerous PhD and MSc students on topics including 6D pose estimation , medical augmented reality , and robotic ultrasound , collaborating with institutions like MIT , École Polytechnique , and University of Padova .

Anna Maria OberländerView profile

Assistant Professor

• Digital Transformation
• Digital Innovation
• Information Systems
• +7 more

Anna Maria Oberländer is Assistant Professor for Information Systems and Digital Transformation at the University of Bayreuth's Faculty of Law and Economics. She also serves as Deputy Academic Director of the Research Center Finance & Information Management and holds a leading position at Fraunhofer FIT's Branch Business & Information Systems Engineering, where she co-heads a research group and manages the Digital Innovation Lab as one of its co-founders. Dr. Oberländer earned her Master of Science with honors from the Elite Graduate Program Finance & Information Management at the University of Technology Munich and the University of Augsburg in 2015, including a research visit at Queensland University of Technology. She was accepted into the 16th class of the Bavarian EliteAcademy, receiving leadership training across Germany, Belgium, China, and Vietnam. Prior to academia, she worked as a strategy consultant at McKinsey & Company from 2015 to 2018, supporting clients in Advanced Industries and Financial Services with digital transformations. She completed her dissertation at the University of Bayreuth's Law and Economics Faculty in 2020. Her research focuses on understanding and designing digital transformation and innovation from established companies' perspectives. She examines digital transformation processes and patterns, the relationship between organizational digital transformation and digital ecosystems, organizational ambidexterity, resource-based digital opportunities for incumbents, and the socio-technical and economic impacts of IoT and AI technologies. Her work spans theoretical frameworks like the OCO (Orientation, Cooperation, Orchestration) Theory for understanding digital ecosystems' influence on transformation. Dr. Oberländer's recent publications reveal a strong trend toward integrated digital-sustainability research (twin transformation), AI strategy and implementation, digital ecosystem dynamics, and industry-specific digital innovation. Her work bridges theoretical frameworks with practical applications across diverse sectors including public administration, manufacturing, and smart cities. She has developed capability maturity models for twin transformation and explored semantic search adoption in SMEs. Science Award 2020 from Universitätsverein Bayreuth e.V. With extensive industry experience at Siemens, Siemens Financial Services, Allianz, and McKinsey & Company, Dr. Oberländer brings practical insights to her academic work. Her Fraunhofer FIT role connects her research to real-world applications through the Digital Innovation Lab. She has led collaborative research projects across multiple industries, including the print industry's sustainability potential with AI, dairy industry digital innovation, and public administration digitalization. Dr. Oberländer co-heads a research group at Fraunhofer FIT and manages the Digital Innovation Lab, which serves as a hub for collaborative research between academia and industry. Her work with the Research Center Finance & Information Management facilitates interdisciplinary collaboration across finance and information systems domains.

• Autonomous Driving
• Sensor Fusion
• Intelligent Transportation Systems
• +5 more

Prof. Dr.-Ing. Christoph Stiller is a full professor at the Karlsruher Institut für Technologie (KIT) and serves as the director of the Institute of Measurement and Control Technology (Institut für Mess- und Regelungstechnik, MRT). His work focuses on autonomous driving, sensor fusion, probabilistic estimation, HD mapping, motion planning, and intelligent transportation systems. Education: Details on his academic degrees are not provided in the text, but he holds the title of Dr.-Ing. indicating a doctoral degree in engineering. Research Interests: Prof. Stiller's research spans a wide array of topics critical to the development of autonomous vehicles. His work includes: Sensor Fusion: Integrating data from LiDAR, cameras, and radar to create robust perception systems. HD Mapping & Localization: Developing high-definition maps and precise localization techniques for urban and highway environments. Motion Planning & Decision Making: Creating algorithms for safe and efficient trajectory planning under uncertainty. Machine Learning & AI: Applying deep learning and reinforcement learning to perception, prediction, and control tasks. Publication Trends: His recent publications (2023–2025) emphasize robust traffic light detection, image stitching for panoramic views, motion prediction using redundancy reduction, and safety-enhanced model predictive control. The work increasingly integrates learning-based methods with classical control and estimation theory. Scientific Awards: No specific awards are listed in the provided text. Teaching & Supervision: Prof. Stiller teaches foundational and advanced courses in measurement and control systems, probabilistic estimation, and autonomous driving. He holds regular office hours during both summer and winter semesters and is actively involved in advising students and researchers. Labs & Teams: He leads the Institute of Measurement and Control Technology (MRT) at KIT, which is engaged in cutting-edge research in autonomous systems. The institute collaborates with industry and academia on large-scale projects such as UNICARagil and various European initiatives.

Yuanbo XiangliView profile

Researcher

• 3D Computer Vision
• Deep Generative Modeling
• Photorealistic Scene Reconstruction
• +3 more

Yuanbo Xiangli is a postdoctoral researcher at Cornell University , advised by Prof. Noah Snavely. Previously, he obtained his Ph.D. from the Multimedia Lab in the Department of Information Engineering at the Chinese University of Hong Kong (CUHK) , supervised by Prof. Dahua Lin. His research focuses on 3D computer vision and deep generative modeling for urban scene reconstruction. 3D scene reconstruction from sparse images Neural rendering and Gaussian splatting Deep generative modeling for urban environments Multi-source geospatial data processing City-scale modeling and synthetic datasets His recent work includes advanced NeRF extensions (BungeeNeRF, GridNeRF), Gaussian splatting enhancements (GSDF, Scaffold-GS), and urban scene datasets (MatrixCity, OmniCity). A pioneer in combining classical vision techniques with modern deep learning approaches. ICLR 2020 Spotlight Award Collaborates with leading researchers in photorealistic rendering, including Noah Snavely and Dahua Lin. Develops systems enabling efficient 3D reconstruction from diverse data sources like satellite imagery and street-level panoramas.

Colin AtkinsonView profile

Professor

• Model-Driven Development
• Dynamic Software Analysis
• Software Search
• +3 more

Colin Atkinson is a Professor in the School of Business Informatics and Mathematics at the University of Mannheim, where he has led the Software Engineering Group since April 2003. He additionally serves as head of the Examination Board for the Bachelor Business Informatics course, with administrative support from secretary Simone Kehrberg. His educational background includes a Ph.D. and M.Sc. in Computer Science from Imperial College, London (awarded in 1990 and 1985 respectively), and a B.Sc. in Mathematical Physics from the University of Nottingham (1983). Prior academic appointments include professorships at the University of Kaiserslautern and the affiliated Fraunhofer Institute for Experimental Software Engineering, followed by an Assistant Professorship in Software Engineering at the University of Houston – Clear Lake from 1991 to 1997. Professor Atkinson's research concentrates on Model-Driven Development with specialized focus on deep modeling and view-based modeling techniques, complemented by significant contributions to Dynamic Software Analysis and Software Search methodologies within the broader domain of Software Engineering. His work bridges theoretical frameworks with practical applications in software system construction and analysis.

Diogo Carbonera LuvizonView profile

Researcher

• Computer Vision
• Computer Graphics
• Deep Learning
• +4 more

Diogo Carbonera Luvizon is a Researcher at the Max-Planck-Institut für Informatik (MPI-INF) in Saarbrücken, Germany, and a member of the Visual Computing and Artificial Intelligence (VIA) Research Center. He holds a PhD in Computer Vision and Machine Learning from CY Cergy Paris University (2019), and Bachelor's and Master's degrees in Engineering and Applied Computing from UTFPR, Brazil. His research focuses on solving complex problems in Computer Vision, Computer Graphics, and Deep Learning, particularly in human modeling and real-time systems. Education: PhD (2019) - CY Cergy Paris University; M.Sc. (2015) - UTFPR; B.Sc. (2011) - UTFPR. Research interests include 3D human pose estimation, action recognition, multitask learning, and novel view synthesis. He has contributed to patents on multiplane image generation (Samsung) and vehicle speed measurement systems. His work has been recognized with awards like the Best Paper Honorable Mention at GCPR-VMV 2022 and Best Presentation Award at ETIS Lab (2018). He has developed open-source tools, including the deephar repository for human action recognition and pose estimation. His current affiliations include MPI-INF and the VIA Research Center, a partnership between MPI-INF and Google.

• Radar Image Analysis
• Out-of-distribution Detection
• One-Class Deep Neural Networks
• +5 more

Mustafa Kahya is a Scientific Staff member and Ph.D. candidate at the Chair of Media Technology within the Munich Institute of Robotics and Machine Intelligence (MIRMI) at the Technical University of Munich (TUM). He works under the supervision of Prof. Dr.-Ing. Eckehard Steinbach and is actively involved in research related to radar systems and machine learning. His academic background includes a B.Sc. in Computer Engineering from Istanbul Technical University (2017) and an M.Sc. in Informatics from TUM (2021). During his master's studies, he conducted research on 3D Reconstruction and Multi-view Shape from Shading at the TUM Computer Vision Group. Kahya's research focuses on Radar Image Analysis , Out-of-distribution Detection , One-Class Deep Neural Networks , Anomaly Detection , and Generative Models . His work primarily centers on applying deep learning techniques to short-range FMCW radar systems for various applications including human presence detection, facial authentication, and activity recognition. His publications demonstrate a strong trend toward real-time radar-based systems with emphasis on out-of-distribution detection capabilities. Kahya has been actively publishing in top-tier conferences and journals from 2023 through 2025, with multiple first-author publications in IEEE venues including ICASSP, ICIP, and IEEE Sensors. His research has been part of several significant projects including the Centre for Tactile Internet with Human-in-the-Loop (CeTI) and DFG-funded research on Teleoperation over 5G. As a Ph.D. candidate at the Chair of Media Technology, Kahya contributes to the research group's work in computer vision, machine learning, and radar systems. His work bridges the gap between traditional computer vision techniques and novel radar-based sensing modalities, creating opportunities for applications in environments where optical systems face limitations.

• Medical Imaging
• Deep Learning Applications
• Ultrasound Imaging
• +3 more

Mehrdad Salehi is a researcher at the Chair of Computer Science Applications in Medicine at the Technical University of Munich (TUM) . His work focuses on the intersection of computer science and medical imaging, with expertise in ultrasound technology, deep learning, and surgical navigation systems. Key research areas include sonification of medical data, 3D ultrasound reconstruction, and machine learning-based segmentation. He has contributed to innovative projects like PRO-TIP calibration phantoms and ColibriDoc autonomous docking systems. His publications highlight trends in acoustic feedback mechanisms, neural radiance fields for medical imaging, and real-time image analysis. He can be reached at mehrdad.salehi@tum.de .

Xieyuanli ChenView profile

Associate Professor

• Robotics
• Autonomous Systems
• Computer Vision
• +3 more

Xieyuanli Chen is an Associate Professor at the National University of Defense Technology (NUDT), China. He holds a Dr.-Ing. (summa cum laude) from the University of Bonn (2022), a Master's in Robotics from NUDT (2017), and a Bachelor's in Electrical Engineering from Hunan University (2015). His research focuses on robot learning, perception, and navigation, with an emphasis on LiDAR-based SLAM, autonomous systems, and semantic perception. Education: PhD: University of Bonn, 2018-2022 (supervised by Prof. Cyrill Stachniss) Master's: NUDT, 2015-2017 Bachelor's: Hunan University, 2011-2015 Research interests include robotics, autonomous systems, computer vision, and LiDAR perception. He has authored over 90 papers in top venues like TRO, RSS, ICRA, and CVPR. He serves as an Associate Editor for IEEE RA-L, ICRA, and IROS, and is a member of the RoboCup Rescue Robot League Technical Committee. Awards include the RSS Pioneer Award (2021), Best-in-Class RoboCup awards, and recognition as a World’s Top 2% Scientist (2024). His work spans LiDAR localization, moving object segmentation, and efficient semantic mapping. He advises students in robotics and autonomous systems. Labs/Teams: Active in the PRBonn group (University of Bonn) and leads research at NUDT on LiDAR-based perception systems.

• Human-Computer Interaction
• Interaction Design
• Usability Engineering
• +13 more

Prof. Dr. Harald Reiterer is a leading researcher in Human-Computer Interaction at the University of Konstanz, where he has served as Professor since 2009. His academic journey includes a Ph.D. (1991) and habilitation (1995) from the University of Vienna, followed by roles including Senior Researcher at Fraunhofer FIT and Associate Professor at Konstanz. He currently holds multiple leadership roles: Dean of the Faculty of Sciences , Senator of Section 1 , and Consulting Dean . Ph.D. in Computer Science (University of Vienna, 1991) Venia Legendi (Habilitation) in HCI (University of Vienna, 1995) His research focuses on: Interaction Design for mixed reality environments Information Visualization in immersive contexts Hybrid User Interfaces combining physical and virtual elements 3D Object Manipulation in handheld AR Behavioral Analytics through mHealth interventions Recent work explores: Avatar representation in Augmented Reality (2024) Node selection efficiency in Virtual Reality (2024) Peripheral vision toolkits for Head-Mounted Displays (2023) Hybrid interface optimization for Mixed Reality (2023) Smartphone AR extensions for Spatial Memory (2023) Key scientific contributions: Landeslehrpreis 2021 for interdisciplinary exhibition design Development of Colibri cross-reality toolkit (2023) Foundational work on Re-locations for remote collaboration (2022) He leads numerous projects including: SMARTACT (Smart Mobility, 2015-2023) SFB TRR 161 (2009-2027) on XR interface measurement Blended Library (2011-2015) for future library design

Ulrike KlugeView profile

Professor

• Migration Studies
• Mental Health
• Transcultural Psychiatry
• +4 more

Prof. Dr. phil. Dipl. Psych. Ulrike Kluge is a Professor and Head of the Center of Cross-Cultural Psychiatry and Psychotherapy (ZIPP) at Charité – Universitätsmedizin Berlin. She concurrently leads the Research Division for Intercultural Migration and Care Research within Social Psychiatry and serves as a Senior Researcher at the Berlin Institute for Integration and Migration Research (Humboldt University). Her work focuses on intercultural mental health services and migration-related psychosocial challenges. Research Focus: Kluge specializes in critical migration studies examining psychological impacts of displacement, ethno-psychoanalysis, psychotherapy with cultural interpreters, and group-analytic approaches in transcultural contexts. Her research portfolio includes qualitative investigations into: Mental health consequences of racism and structural discrimination Refugee-host community dynamics Language barriers in healthcare Innovative care models for forced migrants Intercultural opening of mental health systems Key Projects: FOCUS: Forced displacement and refugee-host community solidarity TransVer: Network for intercultural opening of psychosocial care systems reWoven: Refugee women and psychosocial volunteer engagement SeGeMi: Study group on Mental Health and Migration Effectiveness studies on native-language counseling Professional Engagement: She develops training programs for clinicians working with refugees, provides supervision services, and coordinates Berlin-wide networks for refugee mental health care. Her work significantly contributes to professionalizing psychosocial support for asylum seekers through the 'Welcome Culture at Charité' initiative.

Amine MhedhbiView profile

Assistant Professor

• Data and Information Management
• Graph Databases
• Artificial Intelligence Systems
• +3 more

Amine Mhedhbi is an Assistant Professor at Polytechnique Montréal , where he leads the Data & AI Systems Lab . He earned his PhD in 2023 from the University of Waterloo. His work bridges data management , graph databases , and AI systems , with a focus on performance, debuggability, and user interface design for data applications. Education : PhD (University of Waterloo, 2023) Research Interests center on modern analytical data systems , including multimodal data management , language model integration , and graph query optimization . His projects like FLockMTL and GraphflowDB aim to combine semantic analysis, AI, and traditional database operations. Scientific Awards include the NSERC Discovery Grant , the Cheriton School Distinguished Dissertation Award , the VLDB Best Paper Award , and fellowships from Microsoft and Meta . Key Collaborations : Semih Salihoğlu, Jimmy Lin, Elena L. Glassman Labs & Teams : Affiliated with DAIS Lab , IVADO , and co-founded the applied research team at Distyl AI in 2023.

• Business Process Management
• Process Mining
• Complex Event Processing
• +5 more

Prof. Dr. Matthias Weidlich is a faculty member at Humboldt University of Berlin within the Institute of Computer Science under the Faculty of Mathematics and Natural Sciences . His research focuses on Process Mining , Complex Event Processing , and Data Privacy with applications in Business Process Management and Scientific Workflows . Research Interests: Business Process Management and Process Mining Complex Event Processing and Stream Data Analysis Data Privacy and Security in Process Systems Scientific Workflow Systems and User Behavior Heterogeneous Network Embeddings Algorithm Design and Optimization Recent Publications (2023-2025) demonstrate expertise in: Efficient stream processing techniques Privacy-preserving process mining frameworks Scientific workflow analysis tools Graph neural network applications Multi-modal data integration Adaptive querying systems Contact: Office: Unter den Linden 6, 10099 Berlin Phone: 030 2093-41277 Email: matthias.weidlich@hu-berlin.de Web: hu.berlin/data

• Data Visualization
• Visual Analytics
• Computer Science
• +4 more

Jonathan Roberts is a researcher at Bangor University, UK, with a focus on data visualization, visual analytics, and educational technology. His work bridges computer science and creative design, particularly in data art exhibitions and authentic learning. Key research areas: Data Visualization, Visual Analytics, Educational Technology, Digital Art Recent publications explore generative AI in visualization design, multiple-view patterns for time series data, and frameworks for creative learning. His collaborations span institutions like QUT, University of Manchester, and University of Cambridge. Notable awards include VAST 2012 Honorable Mention and VAST 2010 Analytic Process Recognition. He contributes to visualization pedagogy and has co-authored works on haptic interfaces, immersive analytics, and coastal data modeling.

Oliver StaadtView profile

Professor

• Virtual Reality
• Augmented Reality
• Computer Graphics
• +7 more

Prof. Dr. sc. techn. ETH Oliver Staadt is Full Professor of Computer Science and Chair of Visual Computing at the University of Rostock , Germany. Since 2023 he also serves as Director of the Institute for Visual and Analytic Computing within the Faculty of Computer Science and Electrical Engineering . Previously he was Dean (2016–2018) and Vice Dean (2010–2016) of the same faculty. Education Ph.D. in Computer Science, ETH Zürich (2001) M.Sc. in Computer Science, TU Darmstadt (1994) Research Interests Prof. Staadt’s research spans virtual and augmented reality , computer graphics , visualization , telepresence , immersive analytics , and human–computer interaction . A particular focus lies on real-time rendering and display technologies for large high-resolution display systems, depth-image enhancement for RGB-D sensors, and interaction techniques that leverage spatial cognition and eye-tracking. His work is frequently applied to collaborative settings and microgravity environments, including experiments aboard parabolic flights and the International Space Station. Recent Publication Trends Between 2019 and 2021 his output centers on foveated rendering , AR viewpoint guidance , collaborative analytics on wall-sized displays , and embodied interaction metaphors . Earlier work addressed bandwidth-efficient telepresence, depth-image filtering, and physically-based animation. The corpus reveals a steady evolution from fundamental graphics algorithms toward applied immersive systems. Scientific Awards & Honors Fellow of the Eurographics Association Associate Editor, IEEE Transactions on Visualization and Computer Graphics (past) Associate Editor, Computers & Graphics (past) Associate Editor, Computer Animation and Virtual Worlds (past) Associate Editor, Frontiers in Virtual Reality (current) Chair, Expert Group on Virtual & Augmented Reality, German Informatics Society (2013–2020) Advising & Funding He has successfully supervised more than ten PhD graduates whose dissertations range from collision detection and physically-based animation to 3D interaction in microgravity and predictive user modeling. Current PhD researchers include Bipul Mohanto, Mana Takhsha, and Sven Kluge. His projects are supported by national and EU programs such as EVOCATION, SMOOTH, ARGuide, 3DPick, DIVA, and Telepresence. Labs & Teams Prof. Staadt leads the Visual Computing Group at Rostock, operating state-of-the-art facilities including large tiled display walls, VR/AR laboratories, and motion-capture systems. The institute hosts interdisciplinary collaborations with partners in visualization, computer vision, psychology, and aerospace engineering.