Find Academic Supervisors

Christa CuchieroView profile

Professor

• Mathematical Finance
• Stochastic Processes
• Risk Management
• +6 more

Christa Cuchiero is a Professor at the Department of Statistics and Operations Research , University of Vienna , and an elected member of the Austrian Young Academy (Junge Akademie) since 2020. Her research bridges rigorous mathematics and cutting-edge applications in finance, machine learning, and stochastic analysis. Education: Christa earned her M.Sc. in 2006 from TU Wien with a thesis on affine interest-rate models, her Ph.D. in 2011 from ETH Zürich on affine and polynomial processes, and completed her Habilitation at the University of Vienna in 2018 on high-dimensional finance beyond classical paradigms. Research Interests: Her work centers on affine and polynomial processes , stochastic portfolio theory , signature methods , and infinite-dimensional stochastic analysis . Recent projects explore signature-based neural SDEs for option calibration, measure-valued diffusions for energy markets, and universal approximation properties of signature transforms. Awards & Recognition: Among her accolades are the FWF START Award 2019 , the Bruti-Liberati Visiting Fellowship 2018 , the ETH Medal 2012 for an outstanding Ph.D. dissertation, and the Prix de l’Institut Europlace de Finance 2017 for the best paper in finance. Contact: christa.cuchiero@univie.ac.at , Kolingasse 14-16, 05.47, 1090 Wien, Austria.

• Wireless Sensing
• Radar Technology
• Machine Learning
• +7 more

Kevin Chetty is a Professor of Wireless Sensing at University College London (UCL), leading the Urban Wireless Sensing Lab within the Department of Security and Crime Science. His work bridges radar technology, machine learning, and healthcare applications, with a focus on passive sensing systems. Education: PhD in Medical Ultrasound Physics (Imperial College London, 2004-2007), MRes in Image and X-Ray Physics (King's College London, 2003), BSc in Physics (King's College London, 1999) Research spans radar micro-Doppler signature analysis for human behavior classification, software-defined radar development, and integrated communication-sensing systems, with applications in security, healthcare, and smart environments. Recent work emphasizes privacy-preserving technologies and edge processing for real-time operations. Scientific awards include the 2022 IET Radar Systems Best Paper Runner-Up, 2022 IEEE Radar Conference 2nd Place, and 2015 National Instruments Engineering Impact Award. He has received funding from government and industry sectors in telecommunications, IoT, security, and healthcare. Teaching roles: Programme Convener for MSc Crime Science and IEP Minor in Crime and Security Engineering; Module Convener for Security Technologies and Crime Mapping & Spatial Analysis Consultancy: Huawei Technologies (2020-2022), Metropolitan Police Service (2019)

Aaron YoungView profile

Associate Professor

• Human Augmentation
• Wearable Robotics
• Assistive Devices
• +7 more

Aaron Young is an Associate Professor in the Woodruff School of Mechanical Engineering at Georgia Institute of Technology and a program faculty member in the Biomedical Engineering School. He serves as Director of the Exoskeleton and Prosthetic Intelligent Controls (EPIC) Lab, focusing on robotic human augmentation through advanced control systems for prosthetics and exoskeletons. Education: Postdoctoral Fellow, University of Michigan (2014-2016) Ph.D., Northwestern University (2014) M.S., Northwestern University (2011) B.S., Purdue University (2009) Dr. Young's research addresses clinically viable control systems for wearable robotic devices, emphasizing intent recognition , EMG signal processing , and machine learning integration. His work targets mobility impairments from stroke, amputation, cerebral palsy, and neurological injuries, aiming to reduce metabolic costs, restore natural biomechanics, and enhance community ambulation. Key innovations include data-driven control frameworks , biomechanical terrain adaptation , and anthropometry-based personalization . His recent publications highlight advancements in deep learning for real-time biomechanics , EMG-informed joint estimation , and adaptive assistance systems . The EPIC Lab's facilities feature a terrain park with force plates , motion capture systems , and HumoTech simulation platforms for device testing. Scientific Awards: New Faces of Engineering (IEEE USA, 2017) Military Health System Team Award (2015) NSF Graduate Fellowship (2010) NDSEG Fellowship (2010) IEEE EMBC 3rd Place (2013) Projects include NSF-funded hip exoskeletons for stroke survivors, DoD-powered prostheses for amputees, and Pediatric knee exoskeletons for cerebral palsy. The lab cultivates interdisciplinary expertise in robotics , biomedical engineering , and human-machine interaction .

Sasan MahmoodiView profile

Associate Professor

• Medical Image Analysis
• Biometrics
• Computer Vision
• +1 more

Dr. Sasan Mahmoodi is an Associate Professor at the School of Electronic and Computer Science , University of Southampton. His research focuses on Medical Image Analysis , Biometrics , and Computer Vision , with applications in healthcare and security systems. Research Groups: Vision, Learning and Control; Institute for Life Sciences; Centre for Machine Intelligence His work spans deep learning , rule-based AI , and pattern recognition in medical imaging, including applications for neonatal brain injury prognosis and radiographic knee osteoarthritis classification. He also contributes to biometric technologies like facial profile recognition and gait analysis. Recent publications highlight his expertise in: Domain adaptation for biometric systems Infrared gait recognition databases Motion artefact correction in HRpQCT imaging Histopathology image segmentation using U-Net variants Dr. Mahmoodi supervises PhD students in computer science and human health development and collaborates on interdisciplinary projects involving machine learning and medical imaging.

• Geospatial Technology
• Machine Learning
• Natural Hazard Prediction
• +7 more

Dr. Husam Al-Najjar is a Lecturer at the School of Computer Science within the Faculty of Engineering and Information Technology at the University of Technology Sydney (UTS). He serves as the Course Director for the Bachelor of Information Systems (BIS) program. With expertise in geospatial technology and machine learning, Dr. Al-Najjar focuses on predicting and mitigating natural hazards and environmental issues to contribute to a sustainable digital earth. Dr. Al-Najjar earned his PhD from the University of Technology Sydney. Before joining academia, he worked in project management and has received numerous prestigious awards, scholarships, and grants throughout his career. Dr. Al-Najjar's research primarily centers on the application of machine learning techniques to address complex environmental challenges. His work spans geospatial AI, natural hazard prediction (particularly landslides and bushfires), and sustainable development. He has developed innovative approaches that integrate physical models with machine learning algorithms to improve prediction accuracy in data-scarce environments. His research also extends to remote sensing applications, urban planning, and smart city technologies, with a strong emphasis on practical solutions for real-world problems. Analysis of Dr. Al-Najjar's recent publications reveals a strong focus on applying explainable AI techniques to natural hazard prediction, particularly landslides. His work consistently bridges the gap between theoretical machine learning approaches and practical geospatial applications. He has made significant contributions to integrating physical models with AI, developing methods for handling imbalanced data through generative adversarial networks, and improving feature selection for remote sensing applications in environmental monitoring. Best Paper Award at the ISPRS Geospatial Week in Enschede, the Netherlands As an educator, Dr. Al-Najjar is actively involved in mentoring and teaching. He serves as Course Director for the Bachelor of Information Systems program and teaches courses in GIS, Information Systems, IS development methodologies, Design & Innovation, and Project Management. He welcomes prospective PhD candidates interested in his research areas and emphasizes the importance of detailed research proposals that demonstrate novelty and significance. His teaching philosophy focuses on fostering an engaging and inclusive learning environment that promotes student success and well-being. Dr. Al-Najjar is affiliated with 'The Trustworthy Digital Society' concentration at UTS and serves as a referee and holds editorial roles in respected journals. His work contributes to the development of geospatial AI frameworks that support decision-making in environmental management and disaster preparedness.

Cornelius FaberView profile

Professor

• MRI cell tracking
• infection imaging
• MR methodology
• +6 more

Cornelius Faber is a University Professor in the Department of Radiology at the University of Münster, Germany, where he leads the Experimental Nuclear Magnetic Resonance research group. His work focuses on developing and implementing novel MRI techniques that extend the boundaries of magnetic resonance imaging in terms of spatial and temporal resolution, sensitivity, and specificity for physiological, structural, and molecular changes. He actively participates in the "Cells in Motion" interdisciplinary research initiative at the university. Professor Faber's research spans multiple critical areas in medical imaging and biomedical science. His primary expertise lies in MRI cell tracking , enabling visualization of cellular dynamics in vivo. He has made significant contributions to infection imaging , developing methods to detect and characterize microbial infections using MRI. His work on MR methodology development has advanced quantitative imaging techniques, while his research on multimodal integration in MR and MRI contrast mechanisms has provided deeper insights into molecular and cellular processes. His research bridges physics, engineering, and biomedical applications, with particular relevance to inflammation, cancer, neurological disorders, and cardiovascular disease. Analysis of Professor Faber's extensive publication record reveals a clear evolution from fundamental MRI technique development toward increasingly sophisticated applications in disease models. His recent work demonstrates a strong trend toward multimodal imaging approaches that combine MRI with complementary techniques such as mass spectrometry, optical imaging, and PET. This integration creates comprehensive diagnostic platforms that provide both anatomical and molecular information. A notable pattern is the focus on cellular dynamics, particularly immune cell behavior in inflammatory conditions and tumor microenvironments, with applications spanning neuroscience, oncology, and cardiology. Professor Faber leads a multidisciplinary research team of approximately 15 members, including scientists, doctoral students, technicians, and medical students. His laboratory is deeply integrated with the University of Münster's research infrastructure, particularly the Multiscale Imaging Centre. The group's work contributes significantly to advancing preclinical MRI methodologies while maintaining strong clinical relevance, with numerous publications in high-impact journals across medical imaging, neuroscience, and biomedical engineering disciplines.

Erez RazView profile

Professor

• Cell Migration
• Germ Cell Development
• Embryonic Development
• +4 more

Professor Erez Raz serves as Director of the Institute of Cell Biology at the University of Münster and is affiliated with the Center for Molecular Biology of Inflammation (ZMBE). He is a prominent member of the Cluster of Excellence "Cells in Motion" and serves on the board of the CiM-IMPRS graduate program. His research group "AG Raz: Cell biology in vivo - Germ-cell development" investigates fundamental mechanisms of cell migration in living organisms. Professor Raz's research focuses on cell migration, cell-fate maintenance, and organogenesis within live vertebrate embryos. His laboratory primarily employs zebrafish as a model organism due to its transparent embryos that develop externally, enabling high-resolution live imaging of cellular processes. His work has revealed critical mechanisms of how cells navigate within developing organisms, with significant implications for understanding pathological conditions like cancer metastasis and inflammatory processes where cell migration becomes dysregulated. His recent publications demonstrate a sustained focus on molecular mechanisms controlling germ cell migration, including the roles of RNA-binding proteins like Dnd1, bleb formation dynamics, mitochondrial regulation of germ cell fitness, and tissue microenvironment influences on cell protrusion types. His research uniquely integrates approaches from cell biology, biophysics, genetics, and mathematical modeling to gain comprehensive insights into cellular migration dynamics. Over 100 publications spanning two decades Extensive collaborations across disciplines Methodological innovations in cell imaging and manipulation Professor Raz has successfully mentored numerous doctoral students and postdoctoral researchers, fostering interdisciplinary collaborations between biologists, physicists, mathematicians, and clinicians. His laboratory has developed innovative techniques for cell ablation, mRNA labeling, and in vivo manipulations using optical tweezers, contributing significantly to methodological advances in the field. His laboratory participates in the Multiscale Imaging Centre and the "Cells in Motion" research network, providing access to state-of-the-art imaging capabilities for studying cellular dynamics at multiple scales, from molecular interactions to whole-organism development.

Charles G HoogstratenView profile

Associate Professor

• RNA Biochemistry
• Structural Biology
• Biophysics
• +3 more

Charles G Hoogstraten is an Associate Professor at the Department of Biochemistry & Molecular Biology, Michigan State University, and serves as Assistant Director for Undergraduate Education. His research focuses on RNA conformational dynamics and molecular function, utilizing advanced biophysical techniques such as NMR spectroscopy, surface plasmon resonance (SPR), and molecular dynamics simulations. Ph.D. (1995) - University of Wisconsin-Madison B.S. (1990) - Michigan State University, Chemistry & Biochemistry Previous appointments: UC Davis (1998-2002), University of Colorado, Boulder (1995-98) His work investigates the relationship between RNA structural flexibility and catalytic function, particularly in ribozymes like the hairpin ribozyme. Key contributions include developing novel isotope labeling methods and chemically constrained nucleotides to study RNA backbone dynamics and docking mechanisms. Collaborations with computational biologists enhance atomic-level understanding of these processes. Recent publications highlight his expertise in RNA tertiary structure, metal ion coordination, and spectroscopic analysis. His lab applies techniques such as SPR for docking kinetics, CD difference assays for equilibrium studies, and MD simulations to map RNA energy landscapes. Howard Hughes Medical Institute Predoctoral Fellowship Helen Hay Whitney Postdoctoral Fellowship Hoogstraten teaches advanced biochemistry courses (BMB 461, BMB 829) and leads the Hoogstraten Lab, which bridges experimental biophysics with computational modeling to unravel RNA-catalyzed reactions.

Tim RogersView profile

Professor

• Stochastic Processes
• Random Matrix Theory
• Collective Behavior
• +4 more

Professor Tim Rogers is affiliated with the University of Bath as a faculty member in the Department of Mathematical Sciences . He is actively involved in research spanning complex systems, network theory, and stochastic processes. PhD in Random Matrix Theory from King's College London (2010) His research focuses on emergent behavior in random systems , including: Collective Behavior : Crowd dynamics, lane formation, and noise-enhanced synchronization Epidemics & Networks : Spread prediction, node risk assessment, and misinformation impacts Ecology & Evolution : Trait emergence, species boundaries, and demographic noise effects Random Matrix Theory : Spectral analysis and applications to complex systems Publication trends reflect interdisciplinary work bridging Physics, Biology, and Mathematics , with a focus on network structures , stochastic modeling , and emergence phenomena . Scientific awards include: 2015 : Editor's Choice for Europhys. Lett. 109, 28005 2016 : Highlight of Journal of Physics A 2017 : Editor's Suggestion for Phys. Rev. E 92, 032708 He has supervised numerous PhD students and postdocs on projects related to stochastic dynamics , network modeling , and mathematical biology , with ongoing grants from agencies like EPSRC and The Leverhulme Trust .

Qipei MeiView profile

Assistant Professor

• Civil Engineering
• Artificial Intelligence
• Robotics
• +4 more

Qipei Mei is an Assistant Professor in the Department of Civil and Environmental Engineering at the University of Alberta's Faculty of Engineering. With an MSc in Computer Science and a PhD in Structural Engineering, he bridges civil engineering with artificial intelligence to enhance infrastructure productivity and sustainability. His research spans AI-driven design automation, robotics for construction safety, and IoT-based condition assessment. PhD, Structural Engineering - University of Alberta (2020) MSc, Computer Science - Georgia Institute of Technology (2018) MSc, Structural Engineering - University of Alberta (2014) B.E., Civil Engineering - Huazhong University of Science and Technology (2011) Mei's work focuses on three key areas: leveraging data-driven methods for design automation, applying sensing/robotics to construction operations, and using digital twins for infrastructure assessment. His team explores generative AI for housing design, robotic construction in remote communities, and smart monitoring systems. Recent publications highlight advancements in: lateral capacity prediction for monopile foundations, transformer-based architectural layout analysis, large language models for building code compliance, vision-language models for safety hazard detection, and sensor networks for bridge monitoring. These works demonstrate interdisciplinary integration of AI, structural engineering, and IoT. Mei actively collaborates with diverse researchers and welcomes graduate students to his Smart Infrastructure Technologies (SITE) Research Group, part of the Infrastructure and Human Tech Lab (IHT-Lab). He teaches advanced topics in structural and civil engineering while pursuing industry-funded projects through NSERC, CFI, and Alberta Innovates.

• Human-Computer Interaction
• Virtual Reality
• Augmented Reality
• +5 more

Lung-Pan Cheng is an Associate Professor in the Department of Computer Science and Information Engineering at National Taiwan University, where he leads the Human-Computer Interaction Laboratory. His research focuses on bridging the gap between physical and virtual realities through innovative interface technologies. Cheng's research expertise spans human-computer interaction, augmented/virtual reality, and tactile feedback systems. His work explores how people exist across three types of reality: physical reality governed by physics, imagined realities where things act by wishes, and programmable virtual realities. By examining the mismatches between these realities, Cheng develops novel interfaces, techniques, and devices that extend and interface these realities toward an ultimate unified experience. His recent publications reveal strong trends in haptic feedback systems, procedural generation in VR, and tangible interaction techniques. Cheng's work often involves creating physical props and mechanisms that enhance virtual experiences, with a particular focus on how humans can interact with and manipulate virtual objects through physical interfaces. His research has significant implications for VR training, gaming, and therapeutic applications. Best Paper Award at CHI 2022 for AirRacket: Perceptual Design of Ungrounded, Directional Force Feedback to Improve Virtual Racket Sports Experiences SIC People's Choice Award at UIST 2022 for Garnish into Thin Air Cheng has secured numerous research grants supporting his work in VR and haptic interfaces, with collaborations spanning multiple institutions. His laboratory develops working prototypes that demonstrate practical applications of his theoretical concepts, often resulting in award-winning publications at top HCI conferences. Current projects appear to focus on advanced fabrication techniques for interactive objects, perceptual illusions in VR, and novel haptic feedback mechanisms that don't require traditional grounded hardware. The Human-Computer Interaction Laboratory under Cheng's direction consists of graduate students and researchers working on various aspects of tangible and virtual interfaces. The team frequently publishes in premier venues like CHI, UIST, and IEEE VR, demonstrating consistent productivity and impact in the field. Current research directions include density-varying soft fabrication, polarized light mosaics, and systems for creating infinite virtual spaces within limited physical environments.

Michael VogelView profile

Professor

• Molecular Dynamics
• Condensed Matter Physics
• Glass Transition
• +6 more

Prof. Michael Vogel is a Professor at the Institute for Condensed Matter Physics at Darmstadt University of Technology (Technische Universität Darmstadt), where he leads the Molecular Dynamics in Condensed Matter research group. His work focuses on understanding the microscopic structure and dynamics of condensed matter systems and relating these to macroscopic properties. Research Interests Prof. Vogel's research spans several key areas in condensed matter physics and physical chemistry. His group investigates the structure and dynamics of condensed matter—from simple liquids and soft matter to crystalline and amorphous solids. Specific research focuses include: Water Anomalies: Exploring the fundamental understanding of water's anomalies, particularly testing the hypothesis of a transition between two liquid phases in supercooled water. Ion Transport: Studying microscopic mechanisms of ion movement in energy materials, with applications to lithium-ion batteries and fuel cells. Glass Transition: Investigating cooperative and heterogeneous motion processes during the glass transition to contribute to fundamental understanding. Protein Dynamics: Examining the interplay between protein and solvent dynamics, particularly in biological function. Ionic Liquids: Analyzing structural and dynamic heterogeneities in ionic liquids and their relationship to macroscopic properties. Liquids at Interfaces: Understanding how interfaces alter the properties of liquids, especially water, when confined in nanoscopic geometries. Research Methodology Prof. Vogel's group combines modern experimental techniques, particularly nuclear magnetic resonance (NMR) spectroscopy, with computational approaches like molecular dynamics simulations. This dual approach allows for comprehensive characterization of both local molecular motions and long-range transport properties. Their work often involves analyzing systems under confinement, at interfaces, or in supercooled states to reveal fundamental mechanisms that govern material behavior. Scientific Contributions Prof. Vogel has made significant contributions to understanding: The role of dynamic heterogeneities in glass-forming systems Mechanisms of ion transport in solid-state electrolytes The behavior of water in confined geometries and at interfaces The coupling between protein and solvent dynamics Structural and dynamic properties of ionic liquids Research Team and Facilities Prof. Vogel leads an active research group at TU Darmstadt with access to advanced NMR facilities and computational resources. His team regularly publishes in high-impact journals across physics, chemistry, and materials science. The group collaborates with other research institutions and participates in interdisciplinary projects such as the DFG Research Group 1583 on "Hydrogen-bonding liquids in the presence of internal interfaces of different hydroaffinity."

Amanda WatsonView profile

Assistant Professor

• Wearable Technology
• Biomedical Engineering
• Cyber-Physical Systems
• +2 more

Amanda Watson is an Assistant Professor in Electrical and Computer Engineering at the University of Virginia, with joint appointments in Computer Science. She leads the Watson Research Lab within the UVA Link Lab, a multidisciplinary center for Cyber-Physical Systems (CPS) and Internet of Medical Things (IoMT) research. Her work bridges wearable technology with healthcare and athletic performance applications, focusing on noninvasive monitoring, physiological signal analysis, and safety-critical medical devices. She is also the cofounder and CEO of Luminosity Wearables, commercializing a noninvasive continuous glucose monitor. Education: PhD in Computer Science (2020) - College of William & Mary MSc in Computer Science (2016) - College of William & Mary Bachelors in Computer Science and Mathematics (2014) - Drury University Her research spans multiple domains including: Wearable spectroscopy for nutrition and skin health Machine learning for drug overdose and fall risk detection Biomechanical monitoring in sports medicine Wearable support for visual and neurological impairments IoMT device integration and analytics Recent publications (2024-2025) show strong emphasis on calibration-free physiological monitoring systems, with technical contributions in spectral analysis , multi-wavelength sensing , and rapid prototyping for healthcare wearables. Applications range from maternal health to gerontological social isolation detection. Lab and Team: The Watson Research Lab at UVA develops wearable solutions for clinical and athletic contexts, with ongoing collaborations in the PRECISE Center at University of Pennsylvania and LENS lab at William & Mary alumni network. She works with multidisciplinary teams including engineers, clinicians, and data scientists.

Steve BokerView profile

Professor

• Quantitative Psychology
• Structural Equation Modeling
• Longitudinal Data Analysis
• +5 more

Steve Boker is a Professor of Psychology at the University of Virginia, directing the Human Dynamics Laboratory and the LIFE Academy. His research focuses on quantitative psychology, structural equation modeling (SEM), and dynamical systems analysis for longitudinal and time series data. Dr. Boker has pioneered methods like Differential Structural Equation Modeling (dSEM) , Latent Differential Equations (LDE) , and the Windowed Cross-Correlation (WCC) method. He co-developed the widely used OpenMx SEM software framework and invented the RAMpath method for path diagram analysis. Key Research Areas: Dyadic conversation dynamics, adaptive systems in addiction, motion symmetry in social interactions, maternal-infant coupling, and resilience modeling through longitudinal data. Awards & Honors: 2024 Distinguished Researcher Award (UVA) 2020 Saul Sells Award for lifetime achievement in multivariate psychology Fellow, American Psychological Association Fellow, Association for Psychological Science His methodological contributions span over 150 publications, with recent work emphasizing nonlinear dynamics, surrogate data validation, and complexity metrics like the Tangle index for short time series analysis.

Hansjörg KuttererView profile

Professor

• Geodesy
• Geophysics
• Environmental Science
• +3 more

Prof. Hansjörg Kutterer is a Professor and Dean at the KIT-Department of Civil Engineering, Geo and Environmental Sciences at Karlsruhe Institute of Technology (KIT). His primary affiliation is with KIT's Department of Civil Engineering, Geo and Environmental Sciences. He leads geodetic research initiatives focusing on Earth observation systems, atmospheric modeling, and geophysical data analysis. His research emphasizes advanced applications of GNSS, InSAR, and satellite gravimetry for monitoring climate-related phenomena such as water vapor dynamics, terrestrial water storage changes, and ground motion patterns. Key projects include developing machine learning-enhanced models for tropospheric delay corrections and integrated water vapor estimation in the Upper Rhine Graben region. Prof. Kutterer actively contributes to international geodetic frameworks like the Global Geodetic Observing System (GGOS), particularly through DA-CH regional collaborations. His work bridges geodetic methodologies with interdisciplinary challenges in climate science and environmental engineering. He oversees departmental operations as Dean, fostering innovation in geospatial education and infrastructure. His technical expertise spans geodetic deformation analysis, statistical robust estimation, and the integration of geophysical models with observational data.