Find Academic Supervisors

Sven SchmitzView profile

Professor

• Wind Energy
• Aerodynamics
• Rotorcraft Design
• +3 more

Dr. Sven Schmitz is a Professor of Aerospace Engineering at Penn State University, affiliated with the Integrated Energy Systems theme at the Institute for Energy and the Environment (IEE). His research focuses on aerodynamics, wind energy systems, and rotorcraft aeromechanics. Key projects include optimizing wind turbine performance during ice storms and analyzing helicopter rotor hub flows using scaled models in the Garfield Thomas Water Tunnel. He leads efforts in floating offshore wind turbine technologies and mitigation of aviation contrail impacts on climate. Affiliations: Penn State Aerospace Engineering, IEE Faculty Member, Vertical Flight Society contributor Education: Promoted to Professor (2022), with prior academic milestones including a 2021 Atherton Teaching Award Research interests span computational fluid dynamics (CFD), rotor design optimization, and machine learning applications in multirotor performance prediction. Notable contributions include resolving century-old wind turbine equations and advancing coaxial rotor dynamics for urban air mobility. Awards include the 2024 Vertical Flight Society Technical Paper Award and leadership in the 2019 DOE Collegiate Wind Competition. His work bridges academia and industry through collaborations like the Penn State Vertical Lift Research Center of Excellence. Grants/Projects: Multi-Disciplinary Approach to Climate Impacts of Contrails, Next-Gen Floating Offshore Wind Turbines Labs: Applied Research Lab (ARL), Garfield Thomas Water Tunnel

Bing LiView profile

Professor

• Dimension Reduction
• Machine Learning
• Graphical Models
• +4 more

Bing Li is the Verne M. Willaman Professor of Statistics at The Pennsylvania State University, within the Eberly College of Science and the Department of Statistics. His work focuses on advancing statistical methodologies with applications in diverse fields. He has held academic positions since joining Penn State and maintains active research and teaching roles. Education: Ph.D. in Statistics (1992), The University of Chicago M.Sc. in Statistics (1989), University of British Columbia, Vancouver M.Sc. in System Sciences (1986), Beijing Institute of Technology B.Sc. in Automatic Control (1982), Beijing Institute of Technology Research Interests: Bing Li specializes in dimension reduction techniques for high-dimensional data, with a focus on nonlinear methods and their applications in machine learning. He explores graphical models to represent statistical networks and has contributed to estimating equations , semiparametric estimation , and asymptotic theories . His work integrates longitudinal data analysis and addresses challenges in functional data regression and causal inference through innovative frameworks like envelope models and functional additive regression operators. Research Trends: His recent publications emphasize nonlinear and functional extensions of sufficient dimension reduction, causal graph learning, Bayesian statistical methods, and kernel-based testing. Notable themes include leveraging optimal transport for graphical models, developing ensemble neural networks for dimension reduction, and advancing statistical inference for complex data structures like tensor-valued observations. Awards/Honors: No specific honors or awards are explicitly listed beyond his endowed professorship. Advising & Grants: No advising records or grant information are provided in the text. His professional activities likely include mentoring through his departmental role, though explicit details are unavailable. Labs/Teams: Not explicitly mentioned; however, his research is conducted through the Department of Statistics at Penn State, possibly collaborating with interdisciplinary teams given his focus on biological and functional data applications.

Aksel HiorthView profile

Professor

• Reservoir Engineering
• Geochemical Modeling
• Subsurface Flow Modeling
• +3 more

Aksel Hiorth is a Professor of Reservoir Technology at the University of Stavanger (UiS) and Chief Scientist at NORCE. He holds a PhD in theoretical physics from the University of Oslo. His research focuses on subsurface flow modeling, geochemical interactions, and applications of porous media principles in medicine. He leads the Computational Engineering master's program and has pioneered workflows like IORSim for field-scale geochemical simulations. Education: PhD in Theoretical Physics (University of Oslo). Research Interests: Multi-scale reservoir modeling (pore to field scale) Geochemical processes in porous media Non-Newtonian fluid dynamics Medical applications of computational fluid dynamics Publications highlight advancements in physics-informed neural networks (PINNs), lattice Boltzmann methods, and EOR (Enhanced Oil Recovery) technologies. His work addresses challenges in reservoir optimization, water diversion strategies, and fluid-rock interactions in chalk reservoirs. Key innovations include predictive models for wettability alteration and mineral dissolution/precipitation. Awards include SR Bank's Innovation Award (2010), NPD's IOR Prize (2010), and Lyse’s Research Award (2013). He contributed to establishing the National IOR Centre of Norway, recognized for advancing improved oil recovery techniques. Advancing interdisciplinary research: His labs integrate computational engineering with petroleum geoscience, bridging fundamental physics and applied reservoir engineering. Current projects explore sustainable reservoir management and biomedical fluid dynamics solutions.

Andrew T. DuchowskiView profile

Professor

• Visual Perception
• Human-Computer Interaction (HCI)
• Eye Tracking
• +6 more

Andrew T. Duchowski is a Professor and Chair of the Visual Computing Division at Clemson University's School of Computing (part of the College of Engineering and Science). He holds a Ph.D. in Computer Science from Texas A&M University (1997) and a B.Sc. in Computer Science from Simon Fraser University (1990). His academic roles include service as Focus Area Chair at SIGGRAPH 2019 and Co-organizer of multiple workshops such as MobileHCI 2018 and ETRA 2018. His research focuses on eye tracking, visual perception, human-computer interaction, and computer graphics. Key areas include gaze analytics, virtual environments, and applications in healthcare, education, and cultural heritage. He has pioneered methodologies like the 'Gaze Analytics Pipeline' and authored Eye Tracking Methodology: Theory & Practice (Springer, 3rd ed., 2017). R&D interests span cognitive load measurement via pupil dynamics, ambient/focal attention modeling, and gaze-based interaction design. His work bridges computer science with fields like spatial cognition and neuroergonomics. Recent projects include studies on attention in VR, neurocognitive biomarkers, and sustainable cultural landscape management. Awarded multiple honors including the NSF CAREER Award (2000-2003) and Clemson's Faculty Excellence Award (2001), Duchowski has authored over 150 peer-reviewed papers. He led educational initiatives such as the 'Groovy Graphics Assignments' for SIGGRAPH and co-organized global conferences like ETRA and EuroGraphics. His service includes editorial roles in journals like Transactions on Applied Perception and reviewing for NIH, NSF, and international universities.

J. Holly DeBloisView profile

Lecturer

• Algorithms
• Parallel Computing
• CUDA-based Scene Classification
• +2 more

J. Holly DeBlois is a Lecturer in the Department of Computer Science at the University of Massachusetts Boston, actively teaching courses such as CS444 (Operating Systems) , CS410 (Software Engineering) , and CS420 (Theory of Computation) as of Fall 2025. She earned her Ph.D. in Computer Science from UMass Boston in 2019, preceded by an M.S. in Applied Mathematics from Harvard University and a B.A. in Government from Smith College.

John CressmanView profile

Associate Professor

• Neuronal Dynamics
• Non-Equilibrium Physics
• Biophysics
• +3 more

John Cressman is an Associate Professor in the Physics & Astronomy Department at George Mason University, with affiliations in the Neuroscience Program and the Krasnow Institute for Advanced Study. His research focuses on dynamical systems in driven systems, particularly exploring their roles in brain function and non-equilibrium physics. He investigates transient correlated dynamics in biological processes and natural phenomena like tornados and fluid systems. Cressman's work bridges physics and neuroscience, addressing topics such as ion concentration dynamics in neurons, seizure mechanisms, and energy flow in neuronal systems. His research interests emphasize understanding how transient dynamical structures influence biological and physical systems, with a strong focus on neuronal behavior and the physics of non-equilibrium systems. Key themes include the interplay of excitatory and inhibitory conductances during seizures, ion concentration homeostasis, and the application of advanced imaging techniques like NIR-II fluorescent nanoprobes for biomedical applications. Recent articles highlight innovations in nanoparticle-based sensing and imaging, including DNA-based sensors for bioelectrical signals and fluorescent probes for tumor imaging. These studies reflect a trend toward integrating biophysics with cutting-edge nanotechnology for medical and neuroscientific advancements. Cressman’s work also explores turbulence and energy dissipation in complex systems, linking statistical physics principles to experimental observations. Labs and collaborations are centered at the Krasnow Institute, where interdisciplinary approaches to neurophysics and systems biology are prioritized. His research has implications for understanding neurological disorders and developing novel diagnostic tools.

• Cognitive Psychology
• Hydration Science
• Child Development
• +2 more

Professor Caroline Edmonds is affiliated with the Childhood & Social Care research institute at University of East London. Her extensive research examines how hydration affects cognitive functions across different populations, with special focus on children's cognitive performance, neonatal neurology outcomes, and hydration-related interventions. Research interests span cognitive psychology, hydration science, and paediatric neurology. Key investigations explore water intake effects on memory, attention, and motor skills; neurodevelopmental outcomes following neonatal hypoxic-ischaemic encephalopathy; and nature-based interventions for childhood development. Publication trends show consistent focus on hydration-cognition relationships (50% of recent articles), paediatric neurodevelopment (30%), and educational interventions (20%). Methodologies include controlled trials, systematic reviews, and cross-cultural studies in both laboratory and real-world settings.

Robert WhiteView profile

Associate Professor

• MEMS/NEMS
• Acoustic Microsystems
• Microfabrication
• +5 more

Robert White is an Associate Professor in the Department of Mechanical Engineering at Tufts University's School of Engineering. He leads the Microscale Sensors and Systems Lab and advises the Tufts Micro and Nano Fabrication Facility. His expertise spans acoustic microsystems, MEMS/NEMS, microfabrication, and aerodynamic measurement technologies. White holds a PhD from the University of Michigan and MS/BS degrees from MIT. Education: Ph.D., University of Michigan, Mechanical Engineering (2005) M.S., Massachusetts Institute of Technology, Mechanical Engineering (1999) B.S., Massachusetts Institute of Technology, Mechanical Engineering (1999) Research focuses on acoustic sensors for planetary science (e.g., Mars missions), quench detection in superconductors, and high-altitude anemometry. Key contributions include fluid-filled MEMS hydrophones and sonic anemometers. He has over 120 publications and holds multiple patents in sensor design. Awards include AIAA Associate Fellow status and grants from NASA, DOE, and industry partners. Teaching responsibilities include courses in acoustics, mechanics, and MEMS systems. Current projects involve developing sensors for extreme environments and improving aerospace instrumentation. Labs/Teams: Microscale Sensors and Systems Lab Tufts Micro/Nano Fabrication Facility

Dusan SarenacView profile

Assistant Professor

• Quantum Physics
• Neutron Optics
• Neutron Interferometry
• +4 more

Dusan Sarenac is an Assistant Professor in the Department of Physics at the University at Buffalo's College of Arts and Sciences, where he leads innovative research at the intersection of quantum physics and biomedical optics. His work bridges neutron science for materials characterization and vision science for early ocular disease detection, leveraging structured light and quantum phenomena. PhD in Physics (Quantum Information), University of Waterloo, 2018 Dr. Sarenac's research centers on two transformative domains. In neutron science, he pioneers techniques using orbital angular momentum in neutron beams to probe magnetic structures like skyrmion lattices through 3D tomography, collaborating with Oak Ridge National Laboratory and NIST. In vision science, he develops structured light methods that detect pre-symptomatic eye conditions by enhancing entoptic phenomena, enabling early diagnosis of macular degeneration and pathological myopia through partnerships with Waterloo's School of Optometry and Hong Kong's Centre for Eye and Vision Research. His recent publications (2023-2025) reveal a dual trajectory: neutron optics advancements for quantum materials characterization and vision science breakthroughs in ocular diagnostics. The neutron work focuses on orbital angular momentum manipulation for magnetic imaging, while vision research emphasizes structured light perception metrics and macular pigment mapping. Both streams demonstrate interdisciplinary convergence of quantum information science, wave optics, and biological applications. As Principal Investigator for Advanced Optometric Technology at Hong Kong's Centre for Eye and Vision Research since 2020, Dr. Sarenac directs a collaborative team spanning the University of Waterloo, Oak Ridge National Laboratory, and NIST. His projects integrate quantum engineering with clinical optometry to develop non-invasive diagnostic protocols, securing funding for quantum-inspired vision technologies while mentoring emerging researchers in cross-disciplinary methodologies. His laboratory ecosystem involves neutron beamline development at major facilities and clinical vision testing platforms, with future work targeting orbital angular momentum integration for 3D magnetic reconstruction and structured light applications for pre-symptomatic ocular disease screening.

• Computer Vision
• Multimodal Learning
• Audio-Visual Perception
• +4 more

Yapeng Tian is an Assistant Professor of Computer Science at the Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas. His work focuses on advancing core computer vision and audition technologies with applications in AR/VR, healthcare, and human-computer interaction. He holds a PhD from the University of Rochester (2022) and dual engineering degrees from Tsinghua University (2017) and Xidian University (2013). Research Interests: Multisensory perception Audio-visual learning Diffusion models Medical imaging Accessibility technologies Awards: Amazon Research Award (2024) UIST Best Paper Award (2024) Cisco Faculty Research Award (2023) AAAI New Faculty Highlights (2023) Recent work emphasizes efficient multimodal systems, with publications in top venues like CVPR, ICCV, and ICLR. His research bridges theoretical advances with practical applications in healthcare, accessibility, and interactive systems.

Mark WhitesideView profile

Lecturer

• Animal Welfare
• Animal Behaviour
• Cognitive Ecology
• +1 more

Dr. Mark Whiteside is a Lecturer in Animal Welfare at the University of Plymouth, School of Biological and Marine Sciences. His teaching contributions include courses on Methods in Biology (BIOL234) and Animal Behaviour and Welfare Field Course (BIOL224). His research focuses on animal welfare, behavior, cognitive ecology, and conservation biology, with specific interests in pheasant cognition, environmental adaptation, and the application of big-data approaches to understand animal movement patterns. Key investigations include spatial memory, learning abilities, and inhibitory control mechanisms in birds. Publications demonstrate a consistent focus on cognitive ecology and behavioral adaptations, employing field-based observations and experimental paradigms to explore wildlife management implications.

• Educational Technology
• Creativity Assessment
• Learning Analytics
• +4 more

Dr. Rebecca Marrone is a Lecturer at the University of South Australia's UniSA Education Futures, affiliated with the Department of Learning Sciences and Development and the Centre for Change and Complexity in Learning. Her work focuses on creativity assessment, educational technology, learning analytics, and mathematics anxiety reduction. She has contributed to projects like the preschool policy review for 3-year-olds and a pragmatic trial on self-regulated learning in primary schools. Her research spans AI applications in education, decision-making systems, and cross-cultural studies on statistics anxiety. She co-authored studies on automated creativity scoring via neural networks and the impact of AI on human creativity. Education & Professional Background: While specific educational details are not provided, her academic role and publications indicate advanced qualifications in education, psychology, or related fields. Research Interests: Her interests include AI integration in education, experiential learning, and evidence-based policy for early childhood education. She explores how technology can enhance creativity assessment and reduce academic anxiety while advocating for scalable educational interventions. Articles Overview: Her recent work addresses holistic decision-making systems in schools, the psychological impacts of statistics education, and AI's role in creativity. These studies emphasize data-driven approaches to improve teaching methods and student outcomes. Grants & Collaborations: She has collaborated on projects funded by organizations like the Australian Mathematical Sciences Institute and the Royal Commission into Early Childhood Education. Her work often involves international teams, reflecting her global influence in education research. Labs/Teams: Part of the Centre for Change and Complexity in Learning, focusing on innovation in teaching and learning methodologies. She contributes to interdisciplinary teams addressing systemic educational challenges.

Pedro DelicadoView profile

Professor

• Statistics
• Data Science
• Big Data
• +7 more

Pedro Delicado is a Full Professor at the Department of Statistics and Operations Research, Universitat Politècnica de Catalunya (UPC), based in Barcelona. He holds a degree in Mathematics and a doctorate in Economics. His research focuses on advanced statistical methods, data science, functional data analysis, and machine learning applications. He leads the ADBD research group (Analysis of Complex Data for Business Decisions) and collaborates with the Institut de Matemàtiques de la UPC. His current project 'Advanced Statistics and Data Science 2: New data, new models, new challenges' (PID2023-148158OB-I00) addresses modern data challenges, including Big Data, wearable devices, EEG analysis, graph data, and nonlinear dimensionality reduction. He supervises PhD students and has expertise in predictive modeling, explainable AI, and interdisciplinary applications in health, environmental science, and education. Delicado has published extensively in top journals like Machine Learning, Test, and Environmental and Ecological Statistics. He teaches advanced statistics and data science courses, leveraging virtual platforms. His work bridges statistical theory with practical applications, emphasizing interpretability and real-world impact.

Gloria OrchardView profile

Assistant Professor

• Radiation Science
• Medical Physics
• Biological Physics
• +3 more

Gloria Orchard is an Assistant Professor in the Department of Physics and Astronomy at York University, Faculty of Science. Her research focuses on experimental physics in radiation science and medical physics, alongside pedagogical innovations in physics education. She emphasizes active learning strategies such as in-lecture activities, group discussions, and hands-on laboratory experiences to enhance student engagement and problem-solving skills. Her experimental work involves detector development in radiation science, microdosimetry, and neutron field characterization at facilities like CERN. She also explores applications of optoacoustic systems for subsurface imaging and medical diagnostics. Orchard is eligible to supervise graduate students in the Physics and Astronomy program. Gloria Orchard’s research areas include Biological Physics, Pedagogical Research, and Science Education. She has contributed to advancing detector technologies and radiation measurement techniques through collaborations with institutions like CERN. Her educational initiatives aim to refine laboratory curricula and improve teaching methodologies in physics education.

Jasper MbachuView profile

Associate Professor

• Construction Management
• Productivity Improvement
• Digital Technologies in Construction
• +7 more

Dr. Jasper Mbachu is an Associate Professor at Bond University's Faculty of Society & Design, affiliated with the Centre for Comparative Construction Research. His expertise focuses on construction productivity, digital technologies, and sustainable practices. He holds an MBA from Massey University and a PhD in Construction Economics from the University of Port Elizabeth. His research emphasizes BIM integration, prefabrication, AI applications, and cost management in construction projects globally. Education: MBA, Massey University (2006–2007) PhD in Construction Economics, University of Port Elizabeth (2000–2003) Research Interests: Dr. Mbachu explores productivity improvement in construction, digital transformation (e.g., BIM, GIS, AR/VR), sustainable practices, and cost modeling. He has led projects like the OPiC research incubator and FSD grant initiatives, focusing on systems thinking, risk management, and technology adoption in developing countries. Grants & Projects: OPiC: Bond University Optimizing Productivity in Construction Research Incubator (2018–2021) FSD Research Project Grant on Digital Transformation in Construction (2023) Labs/Teams: Active in the Centre for Comparative Construction Research and collaborates internationally on projects involving 3D printing, smart construction, and circular economy transitions.