Find Academic Supervisors

Jim Tørresen is a senior researcher at the Department of Informatics , University of Oslo , with a focus on Robotics , Artificial Intelligence , and Human-Robot Interaction . His work spans autonomous systems, machine learning applications, and ethical considerations in AI. Current Affiliation : University of Oslo, Norway Research Interests : Robotics for elderly healthcare and assistive technologies Machine learning in multimodal sensing and personalization Explainable AI and ethical user modeling Adaptive control systems and motion planning Embodied intelligence in creative domains like dance Recent Article Trends include AI-driven healthcare monitoring, social robotics for senior engagement, reinforcement learning in constrained environments, and computational creativity applications. His work emphasizes privacy preservation , real-time interaction , and human-centered design . Collaborations : Frequent collaborations with researchers like Kai Olav Ellefsen , Diana Saplacan Lindblom , and Charles Martin across EU projects and robotics conferences.

• Robotics
• Artificial Intelligence
• Human-Robot Interaction
• +3 more

Christian Rathgeb is a professor at Darmstadt University of Applied Sciences , affiliated with the da/sec Biometrics and Internet Security Research Group . His work focuses on biometric security, template protection, face recognition, and synthetic data applications. Research interests include Privacy-Enhancing Technologies 3D-Aware Face Image Quality Assessment Morphing Attack Detection Demographic Bias Mitigation Contactless Biometric Modalities His recent publications emphasize synthetic data generation, multi-biometric fusion, and forensic applications. Collaborations span institutions like TU Darmstadt, École Polytechnique Fédérale de Lausanne, and University of Vigo. Key projects involve FRCSyn (Face Recognition with Synthetic Data) and MCLFIQ (Mobile Contactless Fingerprint Quality). No explicit awards or student advisement details are provided in available data.

• Biometric Security
• Face Recognition
• Synthetic Data Generation
• +9 more

Xiaoming Liu is a Professor at Michigan State University with extensive contributions to computer vision and biometrics. His research spans face recognition, 3D reconstruction, image forgery detection, and adversarial machine learning, with over 300 publications from 1999 to 2025. His primary research interests include Computer Vision , Biometrics , and Adversarial Machine Learning . Liu's work focuses on developing robust systems for face recognition at scale, detecting image manipulations, and creating 3D reconstruction techniques. Recent projects include SapiensID for human recognition, FRCSyn for synthetic face recognition, and proactive watermarking schemes. Liu's publication trends show increasing focus on multi-modal biometrics (combining face, body, and gait), image forgery detection using hierarchical approaches, and adversarial defense mechanisms . His 2023-2025 work emphasizes synthetic data applications and physics-driven recognition systems. Liu has mentored numerous students including Feng Liu, Minchul Kim, and Xiao Guo, who frequently co-author his papers. His research has been supported by grants enabling projects like FarSight (long-range biometrics) and ProMark (proactive watermarking). He leads research in biometrics security and computer vision, with recent work focusing on ethical AI applications and robust recognition systems. His team develops tools for detecting deepfakes and improving recognition in challenging conditions.

• Computer Vision
• Biometrics
• Face Recognition
• +3 more

Zhen Lei is a researcher at the National Laboratory of Pattern Recognition , Chinese Academy of Sciences, Beijing, China. His work focuses on Computer Vision , Biometrics , and Pattern Recognition . Research trends from his publications include Face Recognition , Anti-Spoofing , Person Re-Identification , 3D Face Reconstruction , and Vision Transformers . He has contributed to Information Fusion , Neural Networks , and Image Processing journals. Recent awards or affiliations with honorifics were not explicitly mentioned. Collaborative efforts are evident through co-authorship with experts in Face Detection , Domain Adaptation , and Medical Imaging .

• Computer Vision
• Pattern Recognition
• Biometrics
• +3 more

Dr. Julio Rogelio Guadarrama Olvera is a researcher and leader of the Humanoid Robotics Group at the Chair of Cognitive Systems, Technical University of Munich (Prof. Gordon Cheng). He holds a Dr.-Ing. (Engineering Doctorate) from TUM, awarded with honors in 2021 for his thesis on humanoid robot whole-body control and biped locomotion. His current role includes postdoctoral research focusing on tactile feedback control, object manipulation, and bipedal locomotion. Education: Bachelor's in Mechatronic Engineering (2011), National Polytechnic Institute, Mexico City Master's in Engineering (2013), Center for Research and Advanced Studies, National Polytechnic Institute, Mexico City PhD in Robotics (2021), Technical University of Munich Research Interests: His work centers on advanced robotics systems, particularly tactile-based control for humanoid robots, bipedal locomotion stability, and human-robot interaction. Key areas include: Development of artificial robot skin for sensory feedback Real-time control algorithms for dynamic environments Ethical and safety frameworks for collaborative robots Applications in healthcare robotics and neuroengineering Teaching: Active in teaching advanced robotics courses such as ' Modelling and Control of Legged Robots ' and ' Practical Course RoboCup@Home ' at TUM. Labs/Teams: Leads the Humanoid Robotics Group within ICS, collaborating with international teams on projects like tactile feedback systems and robot skin technology. Involved in EU and industry-funded robotics initiatives.

• Humanoid Robotics
• Biped Locomotion
• Tactile Feedback Control
• +4 more

James Hays is affiliated with Brown University . His research spans Computer Vision , Robotics , 3D Reconstruction , and Image Synthesis . His recent work focuses on 3D Object Detection (e.g., CoRL 2024 ), Semantic Scene Flow (e.g., ICLR 2024 ), and Multimodal Image Generation (e.g., CVPR 2024 ). He has contributed to datasets like ContactDB and ContactPose for robotic grasp analysis. Key trends in his publications include 3D Perception , Efficient Neural Architectures , and Cross-modal Learning for autonomous systems. While no explicit scientific awards are listed, his work is frequently published in top-tier venues like CVPR , ECCV , and CoRR .

• Computer Vision
• Machine Learning
• Robotics
• +3 more

Dr. Jason Raphael Rambach is a Senior Researcher and Deputy Director at the German Research Center for Artificial Intelligence (DFKI) in Kaiserslautern, leading the team "Spatial Sensing and Machine Perception." His work focuses on Scene Perception and Reasoning using Machine Learning, with affiliations spanning Computer Vision, Augmented Reality, and Robotics. Education Diploma in Computer Engineering, University of Patras, Greece (2012) M.Sc. in Information and Communication Engineering, Technical University of Darmstadt, Germany (2014) PhD in Computer Science, University of Kaiserslautern (2020) Dr. Rambach's research bridges Object Pose Estimation , Semantic Scene Understanding , Hybrid AI , and Robotic Vision . His publications (50+ in top conferences) and projects like EU Horizon HumanTech highlight AI applications in construction and recycling. Recent articles analyze symmetry ambiguity resolution, spherical image segmentation, and radar-camera fusion. Scientific Awards CVPR 2025 Outstanding Reviewer Best Paper Award, ISMAR 2017 Five BOP Challenge Awards (ECCV 2022, ICCV 2023) Best Industrial Paper, ICPRAM 2024 Scan2BIM Third Place (CVPR2023, CVPR2024) As a coordinator of EU Horizon HumanTech and contributor to projects like COPPER, BERTHA, KIMBA, and TWIN4TRUCKS, Dr. Rambach integrates AI into industrial workflows. He reviews for CVPR, T-PAMI, ECCV, ICCV, and organizes workshops on AI in Construction Robotics.

• Computer Vision
• Augmented Reality
• Robotic Vision
• +7 more

Prof. Dr. Didier Stricker is a leading academic in computer science, serving as Scientific Director at the German Research Center for Artificial Intelligence (DFKI) and Professor at the University of Kaiserslautern-Landau (RPTU). His career spans over two decades, including leadership roles at Fraunhofer IGD and founding the Augmented Vision research unit at DFKI/RPTU, which now includes ~30 researchers. Education: Electrical Engineering (Technical University of Grenoble, Karlsruhe) PhD: Computer Vision-based Calibration and Tracking Methods for Augmented Reality (2002, TU Darmstadt) His research focuses on virtual and augmented reality , computer vision , human-computer interaction , and on-body sensor networks . He leads major EU/national projects like LUMINOUS (Language-Augmented XR) and SHARESPACE (Ethical Hybrid Shared Spaces), with industrial partnerships including Sony, Google, and John Deere. Recent publications emphasize 3D reconstruction , neural network optimization , and XR systems . Key trends include event camera processing , scene flow estimation , and multimodal AI for industrial applications . He holds patents in AR tracking and has received the 2006 Innovation Prize from the German Society of Computer Science. Scientific Awards : Innovation Prize (2006) Best Paper/Demonstration Awards at ISMAR, EUSIPCO, CVPR, and ICRA As a reviewer for journals and conferences in VR/AR and computer vision, he contributes to shaping research standards. His lab ( AG Augmented Vision ) combines academic and industrial collaborations to advance cognitive interfaces and extended reality systems.

• Virtual Reality
• Augmented Reality
• Computer Vision
• +4 more

Luciano Baresi is a Full Professor at the Polytechnic University of Milan (Politecnico di Milano), Italy, affiliated with the Department of Electronics, Information and Bioengineering. He earned his laurea (MSc) and PhD in Computer Science from the same institution and has held visiting positions at the University of Oregon (USA), Tongji University (China), and the University of Paderborn (Germany). His research spans software engineering, with current focuses on self-adaptive systems, edge computing, and AI/ML-based software. His work integrates formal methods with practical applications, emphasizing autonomous systems, cloud-edge continuum, and federated learning. Recent publications highlight AI-driven advancements in software testing, resource optimization, and educational tools. Key research themes include: AI/ML for autonomous driving testing and data augmentation Serverless computing at the edge Federated learning system architectures Containerization and cloud resource management Awarded for impactful contributions: RE 2020 Most Influential Paper ICSOC 2020 Best Paper SEAMS 2022 Best Paper He advises 14+ PhD students and leads projects like Ketonet (health app), WHO's Essential Items Estimator, and dynaSpark. As Editor-in-Chief of Proceedings of the ACM on Software Engineering and senior editor for multiple journals, he shapes academic discourse in adaptive systems and software engineering.

• Software Engineering
• Self-Adaptive Systems
• Edge Computing
• +5 more