Find Academic Supervisors

• Rehabilitation Robotics
• Machine Learning
• Neuromechanics
• +3 more

Yue Wen is an Assistant Professor at the University of Central Florida. His research focuses on rehabilitation robotics, machine learning, neuromechanics, and human-robot interaction. He holds a Ph.D. in Biomedical Engineering from the University of North Carolina at Chapel Hill and North Carolina State University, an M.S. in Control Theory and Engineering from Huazhong University of Science and Technology, and a B.S. in Automation from Wuhan University of Technology. His work integrates neural engineering and robotics to develop adaptive prosthetic systems and rehabilitation technologies. Key areas include real-time neural drive estimation using deep learning, haptic collaboration in motor tasks, and reinforcement learning for personalized prosthesis control. Recent studies explore exoskeleton interaction dynamics and virtual physical coupling in lower-limb robotics. Yue Wen has received the UNC/NC State Research Assistant Scholarship (2014–2019) and was a finalist in the EMBC Student Paper Competition (2015). His research bridges biomechanics, machine learning, and clinical applications, with a focus on improving gait symmetry and user interaction in robotic prosthetics.

• Photogrammetry
• 3D Modeling
• Heritage Documentation
• +5 more

Pierre Grussenmeyer is a University Professor and Lecturer in the Civil Engineering and Topography Department at INSA Strasbourg, where he also heads the Photogrammetry Laboratory within the ICUBE research unit (TRIO Team). His academic role encompasses teaching aerial/architectural photogrammetry, topometry, positional astronomy, and virtual modeling, while leading research in 3D documentation techniques for heritage and urban environments. His research specializes in photogrammetry , 3D modeling , and heritage documentation , with core expertise in camera calibration, close-range photogrammetry, industrial metrology, and photogrammetric software development (TIPHON/ARPENTEUR projects). Current work integrates deep learning for semantic segmentation of heritage structures, BIM for architectural modeling, and multi-sensor fusion (LiDAR, photogrammetry, GPS) for comprehensive spatial analysis of cultural sites and urban infrastructure. Analysis of his 2023-2025 publications reveals accelerating adoption of AI-driven methods, particularly for semantic segmentation of heritage point clouds and NeRF-based 3D reconstruction. His work bridges traditional photogrammetric precision with cutting-edge neural networks, focusing on practical applications like Rhine castle modeling, forensic scene documentation, and automated road marking extraction from mobile scans. Key trends include synthetic data generation for AI training and rigorous benchmarking of state-of-the-art reconstruction algorithms. Grussenmeyer supervises technological research projects (PRT) and end-of-studies projects (PFE) at INSA Strasbourg, while maintaining active industry collaborations through CIFRE theses with the Alsace region. His work extends to professional training through short continuing education programs, equipment expertise services, and R&D studies for working professionals in surveying and heritage sectors. As head of the Photogrammetry Laboratory, he directs research in architectural photogrammetry, industrial metrology, and virtual model development. Current lab initiatives include underwater crime scene documentation, tropical vernacular architecture preservation in Indonesia, and multi-sensor 3D pipelines for Javanese temples, emphasizing practical solutions for heritage conservation through photogrammetric innovation.

• Neuroinformatics
• Cognitive Robotics
• Tactile Sensing
• +4 more

Prof. Dr. Helge Ritter is a distinguished Professor at the University of Bielefeld, holding multiple key positions across several departments and research centers. He is primarily affiliated with the Faculty of Engineering as part of the Neuroinformatics Group, and also serves as a CITEC Coordinator at the Center for Cognitive Interaction Technology. His work spans the Faculty of Psychology and Sport Science in the Department of Psychology (Unit 01 - Neurocognitive Psychology), and he contributes to the Joint Research Center on Cooperative and Cognition-enabled AI. His academic journey has positioned him at the forefront of interdisciplinary research that bridges engineering, cognitive science, and robotics. As a member of the Habilitation Committee and serving as Personal Deputy for Prof. Dr.-Ing. Ulrich Rückert on the Examination Boards for Biomechatronics (Master), he plays a significant role in academic governance and curriculum development. Research Interests Prof. Ritter's research spans the cutting-edge intersection of neuroinformatics, robotics, and artificial intelligence. His work focuses on cognitive robotics , tactile sensing systems , and human-robot interaction , with particular emphasis on how machines can perceive and interact with the physical world through touch and movement. His investigations into modular neural architectures and biologically inspired learning systems have significant implications for both theoretical neuroscience and practical robotics applications. His current research trajectory demonstrates a strong focus on transfer learning between simulation and reality , multi-fingered manipulation , and adaptive kinematic modeling . These efforts contribute to the broader Socio-Technical World research area at Bielefeld University, which 'researches capabilities and mechanisms that enable agents such as humans, robots and AI to act, communicate and learn in complex environments.' Academic Contributions Coordinator at the Center for Cognitive Interaction Technology (CITEC) Member of the Habilitation Committee in the Faculty of Engineering Personal Deputy for Examination Boards in Biomechatronics (Master) Contributor to the Joint Research Center on Cooperative and Cognition-enabled AI Prof. Ritter's work exemplifies Bielefeld University's commitment to 'Transcending Boundaries' between disciplines, people, and science and society. His research bridges theoretical neuroscience with practical robotics applications, creating innovative solutions for human-robot collaboration and cognitive systems.

• Structural Dynamics
• Vibrations
• Multibody Dynamics
• +4 more

Prof. Dr. Daniel Rixen serves as Professor and Chair of Applied Mechanics at the Technical University of Munich (TUM), based at Boltzmannstr. 15 in Garching bei München. His leadership of the Chair of Applied Mechanics (TUMWLAM) encompasses research, teaching, and departmental administration within mechanical engineering. Research focuses on structural dynamics , vibrations , and multibody systems , with pioneering work in frequency-based substructuring , transfer path analysis , and model order reduction . His group develops critical open-source tools including pyFBS for substructuring workflows and OASIS for sensor data acquisition, bridging computational and experimental mechanics. Recent work integrates machine learning for dynamic simulations and real-time flexible body modeling using game engines. Analysis of 2024-2025 publications reveals three dominant trends: (1) Advanced joint identification techniques for bolted connections, (2) Real-time simulation frameworks combining Unity engine physics with ray-traced contact, and (3) Hybrid approaches merging machine learning with traditional dynamics. These efforts consistently emphasize open-source implementation and experimental validation. The Chair of Applied Mechanics functions as his primary research unit, driving innovation in dynamic substructuring methodologies and their industrial applications across automotive, robotics, and sports engineering domains.

Seyed Soheil MansouriView profile

Associate Professor

• Process Design
• Bioprocess Engineering
• Process Systems Engineering
• +5 more

Seyed Soheil Mansouri is an Associate Professor at the Department of Chemical and Biochemical Engineering, Technical University of Denmark. He holds a PhD (2016) and MSc (2013) from DTU. His expertise spans process design, bioprocess engineering, and quantum computing applications in chemical systems. He leads the KT Consortium PROSYS - Process and Systems Engineering Centre. Research focuses on sustainable biomanufacturing, data-driven modeling, and quantum computing for process optimization. Key areas include photobioreactor design, machine learning in biosystems, and hybrid quantum-classical algorithms. He has supervised 14 PhD projects and co-authored 182 publications. Awards include Best Contributed Paper (2018), Best Oral Presentation (2015), and multiple best presentation awards. Active in organizing workshops on quantum computing and biorefineries. Advises on modular manufacturing, bio-succinic acid production, and AI-driven process systems. Develops digital twin technologies for bio-manufacturing and promotes open innovation. His work aligns with UN Sustainable Development Goals, emphasizing education and sustainable industrial practices. Current projects explore quantum computing in bioprocesses and modular vaccine production units.

• Episodic Memory
• Electroencephalography (EEG)
• Cognitive Neuroscience
• +3 more

Dr. Jamie Murray is a Lecturer (Learning, Teaching & Scholarship) at the University of Glasgow's School of Psychology & Neuroscience. He holds roles as Course Lead for Level 3 Physiological Psychology, teaches on Level 2 Research Methods, and supervises undergraduate/post-graduate dissertations. He previously served at the University of Stirling before joining Glasgow in 2021. His research focuses on EEG-based investigations of episodic memory processes, emphasizing naturalistic tasks and social media's impact on memory. He also explores mental imagery's role in memory differentiation. Education: BSc (Hons) Psychology (University of Stirling), PhD in Psychology (University of Stirling under Prof. David Donaldson and Prof. Roger Watt) Research interests include memory precision measurements, media-driven memory formation, and cognitive differences in imagery vividness. His work bridges neuroscience and applied psychology, with recent studies on mixed reality pain management and drawing's impact on recall. He co-leads the Psychology Employability Network and serves as International Mobility Officer. Key research trends: aging-related memory decline, EEG signal analysis, and transdisciplinary applications of cognitive science. His articles span neuroimaging, cognitive aging, and technology-driven interventions. Awards: No specific scientific awards listed. Advising: Supervises multiple student projects without named advisees listed. Grants and funding details are unspecified. Active in interdisciplinary collaborations, particularly with digital health and educational technology. Labs/Teams: Engaged with the School's research groups on cognitive neuroscience and educational psychology, though specific lab names are not mentioned.

Dejan KosticView profile

Professor

• Distributed Systems
• Computer Networks
• Operating Systems
• +6 more

Dejan Kostic is a Chair Professor of Internetworking at KTH Royal Institute of Technology, leading the Networked Systems Laboratory. He is affiliated with RISE Research Institutes of Sweden and the Wallenberg AI, Autonomous Systems and Software Program (WASP). His research focuses on distributed systems, computer networks, operating systems, and machine learning applications in networking. Education: Ph.D. in Computer Science, Duke University M.S. in Computer Science, University of Texas at Dallas B.S. in Computer Engineering, University of Belgrade Research Interests: His work spans distributed systems , high-performance networking , smartNIC offload , AI-driven systems , and network function virtualization (NFV) . Recent projects include energy-efficient AI inferencing (Wallenberg Scholar Project) and scalable federated learning for healthcare applications. Key contributions include the PacketMill framework, FAJITA stateful processing, and the LineFS distributed file system. Publications & Awards: ERC Starting (2010) and Consolidator (2018) Awards Wallenberg Scholar (2024) Best Paper at SOSP 2021 and Community Award at NSDI 2022 Advising & Grants: Supervised over 15 doctoral students, including notable alumni like Hamid Ghasemirahni and Alireza Farshin. Leads projects funded by ERC, WASP, and Swedish Research Council (VR). Active in grant review panels for ERC and Swedish Foundations. Labs & Teams: Heads the Network Systems Laboratory (NSLab) at KTH, collaborating with Ericsson and RISE on industrial projects. Key initiatives include the Networked Systems for Machine Learning course and the Connected Intelligence unit at RISE.

Krzysztof WolskiView profile

Researcher

• Computer Graphics
• Perceptual Quality Assessment
• Image Processing
• +3 more

Krzysztof Wolski is a Researcher in the Department of Computer Graphics at the Max Planck Institute for Informatics, Saarbrücken, specializing in perceptual quality metrics for computer graphics applications. He holds a PhD from Saarland University (2023) and maintains active research collaborations within the Saarland Informatics Campus ecosystem. His educational background includes: PhD in Computer Science (Computer Graphics), Saarland University and Max Planck Institute for Informatics (2018-2023) Master's in Computer Science (Computer Graphics), West Pomeranian University of Technology (2015-2016) Bachelor of Engineering in Computer Science (Computer Graphics), West Pomeranian University of Technology (2011-2015) Wolski's research centers on human visual perception applied to computer graphics, developing quantitative models for image, mesh, and display quality assessment. His work bridges computational methods with perceptual psychology to optimize rendering pipelines, texture mapping, and adaptive display systems, with emphasis on measurable human-visible differences in digital imagery. Analysis of his 2018-2024 publications reveals consistent focus on perceptual metrics, evolving from foundational visible difference prediction (2018-2019) to neural representations (2023) and adversarial scaling (2024). Key themes include dataset creation (Geo-metric for facial distortions), low-light depth perception (Dark Stereo), and neural denoising techniques, demonstrating increasing integration of deep learning with perceptual modeling. No scientific awards were documented in available sources. Information regarding student advising or research grants was not provided in the source material. He operates within the Computer Graphics department (Department 4) at the Max Planck Institute for Informatics, part of the Saarland Informatics Campus consortium that includes DFKI and Saarland University. His work connects with ELLIS Unit SAM and the Saarbrücken Research Center for Visual Computing, facilitating interdisciplinary research in perceptual AI and graphics.

Bernd DammannView profile

Associate Professor

• High-Performance Computing
• Scientific GPU Computing
• Parallel Programming
• +3 more

Bernd Dammann is an Associate Professor in Scientific Computing at the Technical University of Denmark (DTU) , Department of Applied Mathematics and Computer Science. In parallel he serves as Scientific Lead & Architect in the DTU Computing Center (DCC) and co-founded DTU’s GPUlab in 2007, giving him dual roles in both academic research and institutional HPC services. Education Dipl.Phys. in Statistical Physics, University of Mainz, 1992 PhD in Physical Chemistry, DTU, 1996 Research interests Over almost three decades Dammann has focused on computational methods for large-scale scientific problems. His core expertise lies in: High-Performance Computing and parallel programming paradigms (OpenMP, MPI, GPU) Scientific GPU computing and many-core architectures Application tuning and performance optimization for heterogeneous systems Uncertainty quantification, Monte-Carlo methods, and real-time control applications in biomedicine (diabetes technology) Ultrasound beamforming and advanced imaging techniques Publication trends His 34 publications (1996-2025) trace a clear evolution from theoretical physics and surface-science simulations to GPU-accelerated engineering and biomedical systems. Recent work clusters around real-time biomedical control (artificial pancreas, virtual clinical trials) and high-resolution ultrasound imaging, all leveraging GPU acceleration and high-performance computing to achieve real-time performance. Scientific awards & recognition Contributor to 1 patent family and widely downloaded technical reports (>10 k downloads for OpenCL tutorial) Consistently high citation counts on key optimization and control papers (e.g., 93 citations for 2014 Management Science article) Teaching, supervision & grants He teaches or co-teaches multiple DTU courses: High-Performance Computing , Large-scale Computations , Python & HPC , Mathematical Software , and HPC with FORTRAN . While individual students are not named, his role in GPUlab and DCC implies ongoing PhD and MSc supervision, and his projects list six active collaborations including EU and national HPC infrastructure grants. Labs & teams Dammann co-founded GPUlab (2007) and presently leads the HPC architecture team in the DTU Computing Center , a central facility supplying cluster resources to the entire university.

Felix BlankenburgView profile

Professor

• Cognitive Neuroscience
• Neuroimaging
• Somatosensory Processing
• +5 more

Felix Blankenburg is Professor and Chair of the Neurocomputation and Neuroimaging Unit at the Department of Education and Psychology, Freie Universität Berlin. His research investigates neural mechanisms of perception, cognition, and action using multimodal neuroimaging (fMRI, EEG) and neurostimulation (TMS, tDCS), with emphasis on somatosensory processing, sensory attenuation, and perceptual decision-making within virtual reality environments. His primary research focuses on cognitive neuroscience and neuroimaging, exploring how the brain processes tactile information, integrates multisensory cues, and generates conscious perception. Key areas include Bayesian models of sensory prediction, neural correlates of working memory for tactile stimuli, cross-modal influences (e.g., language on touch), and computational mechanisms of perceptual decisions. His work bridges experimental neuroscience with theoretical frameworks like active inference. Recent publications (2023-2025) reveal strong trends in multimodal integration methodologies, predictive coding applications in somatosensation, and clinical translation through neurostimulation. He pioneers concurrent TMS-fMRI and virtual reality paradigms to probe causal brain mechanisms, with growing emphasis on therapeutic applications for mental health as evidenced by the PREACT research unit. Professor Blankenburg supervises PhD students including: Gianluigi Giannini Guido Caccialupi Jona Förster He serves as principal investigator for the DFG-funded Research Unit 5187 PREACT, developing neuroimaging biomarkers to predict psychotherapy response in non-respondent patients through fMRI-based signatures. The Neurocomputation and Neuroimaging Unit, under his leadership, integrates computational modeling with empirical neuroscience. The team comprises postdocs, PhD students, and research staff collaborating on projects spanning tactile perception, decision neuroscience, and clinical applications of neuroimaging.

Kok Chiang LiangView profile

Lecturer

• ASIC Design
• Power Management Unit
• Robotics
• +2 more

Dr. Kok Chiang Liang is a Lecturer and Program Coordinator for Electrical and Electronic Engineering at the School of Engineering , part of the College of Engineering, Science and Environment at Newcastle Australia Institute of Higher Education (NAIHE). He previously worked at DSO National Laboratories and SUSS, receiving multiple awards including the Design Innovation Award and Teaching Excellence Gold Awards . He holds a PhD and BEng (Honours) from Nanyang Technological University (NTU). Education PhD, Electrical & Electronic Engineering, NTU (2014) BEng (Honours), Electrical & Electronic Engineering, NTU As a researcher, Dr. Kok focuses on ASIC design for power management , robotics , artificial intelligence , and energy harvesting applications . His work bridges IoT and sustainable engineering, with over 50 publications in Q1/Q2 journals and conferences. Notably, he has pioneered innovations in medical device design, urban sustainability, and educational technology. His recent articles highlight trends in sustainable electronics and AI integration across domains. He has received significant recognition, including two Best Paper Awards and substantial research seed funding (over S$260,000). Dr. Kok also contributes to community service as a District Councillor and Grassroots Volunteer in Singapore, and serves on the STEM Industrial Advisory Board and IEEE committees . Scientific Awards Design Innovation Award (Individual), DSO National Laboratories (2018) Teaching Excellence Gold Award, SUSS (2020, 2025) Best Paper Award, 3rd ICESA (2021) Best Paper Award, 6th ICPEE (2024) Dr. Kok’s leadership extends to research grants as Principal Investigator and Co-PI, and to policy advisory roles for Singapore’s Ministry of Education. His interdisciplinary approach combines technical innovation with societal impact, reflected in his roles at People’s Action Party Meet-the-People Sessions and Ang Mo Kio Town Council .

Mohammad Tarique HussainView profile

Senior Lecturer

• Cardiac Imaging
• Pediatric Cardiology
• Congenital Heart Disease
• +5 more

Mohammad Tarique Hussain serves as Director of Congenital Cardiac Magnetic Resonance Imaging at Children's Medical Center, affiliated with The University of Texas Southwestern Medical Center's School of Medicine, Department of Pediatric Cardiology. Previously, he worked as an academic senior lecturer and staff pediatric cardiologist in the United Kingdom, where he completed cardiology fellowships at Birmingham Children's Hospital and the Royal Hospital for Sick Children in Glasgow. Dr. Hussain earned his doctoral degree (PhD) in Imaging Sciences from King's College London, following his undergraduate studies at Queens' College, University of Cambridge, where he was elected as a Queens' college scholar for his academic achievements. His doctoral thesis focused on magnetic resonance imaging in pediatric coronary vasculopathy with special attention to post-transplant coronary vasculopathy and aortic correlates of coronary disease. His research program centers on advanced cardiac imaging techniques for pediatric patients, particularly in congenital heart disease, heart transplantation, and cardiomyopathies. Dr. Hussain has pioneered work in interventional cardiac MRI, three-dimensional imaging, and computational modeling, with international recognition including features in BBC Breakfast, BBC News online, and Telegraph. His laboratory develops novel approaches to reduce radiation exposure during procedures while improving diagnostic accuracy through virtual reality planning and 3D printed models. Analysis of Dr. Hussain's recent publications reveals a strong focus on integrating advanced imaging modalities with computational modeling to address specific challenges in pediatric cardiology. His work bridges clinical cardiology with engineering approaches, particularly in creating patient-specific models for procedural planning and physiological assessment. There's a clear progression toward more sophisticated applications of MRI technology, including real-time guidance for cardiac catheterization and biomechanical modeling of cardiovascular function. Dr. Hussain has secured and managed grant-funded research as principal investigator, including NSF funding. His work has been internationally recognized through media coverage highlighting his innovative use of cutting-edge technology to improve children's healthcare outcomes. As a mentor, Dr. Hussain has guided numerous trainees and junior faculty members, building a comprehensive clinical cardiac imaging program and research team at UT Southwestern that includes post-doctoral students, training fellows, collaborators, and peers. His leadership extends to directing the Pediatric Cardiac MR Imaging Lab, where his team continues to advance the field of pediatric cardiovascular imaging.

William Geoffrey WrightView profile

Professor

• Cognitive Neuroscience
• Motor Control
• Sensorimotor Integration
• +3 more

William Geoffrey Wright is a tenured Professor in the Department of Health and Rehabilitation Sciences at Temple University's College of Public Health , where he serves as Graduate Program Director for Physical Therapy. His career includes USAF satellite engineering service, NASA/DoD-funded graduate research on spatial orientation, and postdoctoral work with neurological patient populations across Germany and the United States. Education: PhD in Cognitive Neuroscience (Brandeis University) MA in Experimental Psychology (Northeastern University) BS in Aerospace Engineering (Virginia Tech) Wright's research investigates sensorimotor integration in neurological disorders, focusing on postural control mechanisms in traumatic brain injury (TBI) patients and Parkinson's disease. His lab develops virtual environment (VE) assessment tools for postural deficits, supported by US Army Rapid Innovation Fund grants and Veterans Administration research contracts. His academic output spans multisensory balance disorders , VR-based rehabilitation , and cervical sensorimotor function in athletes. Key collaborations appear in journals like Journal of NeuroEngineering and Rehabilitation and Experimental Brain Research , emphasizing translational applications in clinical settings. Wright leads the MAP Lab and teaches graduate courses including Neuroscience (PHTH 8114), Motor Control and Learning (PHTH 8116), and evidence-based practice series (PHTH 8137/8151). His work bridges aerospace engineering backgrounds with contemporary neurological rehabilitation research.

Ioannis PratikakisView profile

Professor

• Computer Vision
• 3D Image Processing
• Document Image Analysis
• +3 more

Ioannis Pratikakis serves as a Professor in the Department of Electrical and Computer Engineering at Democritus University of Thrace (DUTH), where he has held a faculty position since 2010. Previously, he worked as a collaborating researcher at the Institute of Informatics and Telecommunications of NCSR 'Demokritos' (2003-2010) and completed postdoctoral research at IRISA/INRIA in Rennes, France until 2000. His academic background includes a PhD in digital 3D image processing and analysis from the Vrije Universiteit Brussel (Belgium), awarded in January 1999. Pratikakis's research spans computer vision, 3D image processing, and document analysis, with core expertise in 2D/3D image sequence analysis, pattern recognition, and multimedia information retrieval. His work bridges theoretical computer vision with practical applications in cultural heritage preservation, medical imaging, and human-computer interaction. Analysis of his publication trends reveals sustained innovation in 3D vision systems, particularly in human action recognition from mesh sequences, facial expression analysis, and unsupervised methods for historical document processing. Recent work increasingly integrates deep learning for medical diagnostics while maintaining strong contributions to cultural heritage digitization. He actively leads research through major projects including μtS (historical manuscript transcription), READ (archival document enrichment), and TRANSCRIPTORIUM (handwritten document recognition), alongside European initiatives like H2020-EINFRA-9-2015 and FP7-ICT frameworks. Pratikakis directs research activities within DUTH's Electrical Circuits, Signal and Image Processing Laboratory, mentoring students through undergraduate courses (Computer Vision, Computer Graphics) and postgraduate instruction (Digital Video Editing, 3D Graphics). His professional engagement includes senior IEEE membership, Technical Chamber of Greece affiliation, and leadership in the Hellenic Society for Artificial Intelligence (2010-2014).

Ferran SuñerView profile

Professor

• Technology-based language learning
• Applied cognitive linguistics
• Figurative language across languages and cultures
• +3 more

Prof. Dr. Ferran Suñer is a full Professor at the Université catholique de Louvain (UCLouvain) in Belgium. He holds the Chair in Multilingualism, Interculturality and Language Lab (CU.mil) and is affiliated with the Institute for Language and Communication / Linguistics Research Unit within the Faculty of Philosophy, Arts and Letters (FIAL). His academic work bridges German language pedagogy, cognitive linguistics, and technological innovation in language education. Education: Doctor in German as a Foreign Language and Psycholinguistics (2011), Ludwig-Maximilians Universität München Licencié en philologie allemande (2005), Universitat de Barcelona Research interests focus on technology-enhanced language learning, embodied cognition in language instruction, and cross-cultural metaphor analysis. He develops digital learning scenarios for inclusive education and co-founded the research group Teaching and Acquiring Multilingualism and Multiliteracies (TeAMM) . His work explores how virtual reality, AI, and embodied practices like gesture-based grammar instruction impact second language acquisition. Recent publications (2023-2025) demonstrate trends in AI integration (ChatGPT as learning partner), embodied teaching of German modal verbs, systematic reviews of usage-based language approaches, and cross-cultural studies on metaphor comprehension. He emphasizes mixed-methods research and digital task design to address heterogeneous learning environments. Teaching units at UCLouvain include courses on German language as social practice, didactic research methods, and mixed-methods in applied linguistics.