Find Academic Supervisors

Josephine VaughanView profile

Lecturer

• Environmental Sustainability
• Building Materials
• Embodied Carbon
• +3 more

Dr. Josephine Vaughan is a Lecturer in Construction Management (Building) at the University of Newcastle's School of Architecture and Built Environment, part of the College of Engineering, Science and Environment. She holds a PhD in Architecture from the University of Newcastle, complemented by a Bachelor of Science (Architecture) from the University of Sydney and a Graduate Certificate in Ecologically Sustainable Development from TAFE NSW. Her research focuses on ecologically sustainable construction practices, particularly in building materials and embodied carbon reduction. Notable projects include developing removable brick mortar for reuse and researching hempcrete as a sustainable alternative. She collaborates with industry partners like Brickworks and RMIT, and actively engages with organizations such as MECLA and the MidCoast Council’s Sustainable Building Futures Partnership. Research interests span environmental sustainability, circular economy, and community-focused design. Over 50 publications and industry reports highlight her contributions, including award-winning work on thermal comfort in classrooms and embodied carbon analysis. Key grants include funding for circular economy mortar development and material management research. Education: PhD in Architecture, University of Newcastle Bachelor of Architecture, University of Newcastle Bachelor of Science (Architecture), University of Sydney Graduate Certificate in Ecologically Sustainable Development, TAFE NSW Her work aligns with UN Sustainable Development Goals (SDGs 3,7,11,12), emphasizing health, energy, sustainable cities, and responsible consumption. Awards include the 2024 MDPI Best Paper Award and 2023 Global Engagement Excellence Award. She also chairs the MECLA Construction Materials & Assemblies Working Group and coordinates student industry experiences. Recent articles explore thermal comfort, circular economy barriers, and traditional water knowledge applications. Grants total over $682,000, supporting projects like material inventories and mortar innovation. Collaborative international work includes teaching programs in India and Malaysia, reflecting her global impact in sustainable built environment practices.

Asli Ozgun-KocaView profile

Professor

• Mathematics Education
• Teacher Education
• Secondary Education
• +7 more

Asli Ozgun-Koca is a Professor of Mathematics Education in the College of Education at Wayne State University. Her work spans teaching, research, and leadership in mathematics teacher education, with a focus on secondary and elementary levels. She is actively involved in national and state-funded initiatives to improve mathematics instruction and equity. B.S. in Mathematics Education, Hacettepe University, Turkiye (1993) M.S. in Mathematics, Middle East Technical University, Turkiye (1996) Ph.D. in Mathematics Education, The Ohio State University (2001) Dr. Ozgun-Koca's research centers on mathematics education, particularly the integration of technology in teaching, professional development for teachers, lesson study, and fostering mathematical knowledge for teaching. She emphasizes equitable practices and the use of real-world, interdisciplinary contexts to enhance learning. Her work explores how teachers analyze tasks and student work to improve instruction, especially in proportional reasoning and statistics. The recent publications and presentations reflect a strong trend in using technology (e.g., GeoGebra) to deepen conceptual understanding, designing integrated STEM and literature-based tasks, and improving feedback and task selection in teacher education. Her scholarship consistently addresses equity, teacher learning, and innovative pedagogies. President's Awards for Excellence in Teaching (2015) COE Faculty Research Award (2014) Career Development Chair Award (2013) Dr. Ozgun-Koca has secured major grants from the NSF and Michigan Department of Education, including SSTEPs, TeachDETROIT, and REALM projects, focusing on evidence-based pedagogies, teacher fellowships, and equity in mathematics education. She advises graduate students and collaborates widely on research. She teaches courses such as Methods and Materials of Instruction, Advanced Studies in Teaching Algebra and Statistics, and Detroit by the Numbers, reflecting her commitment to practical, context-rich teacher preparation. She is a key figure in lesson study adaptations for preservice teachers and leads professional development initiatives that connect theory and practice. Her work is disseminated through national conferences and leading journals in mathematics education.

• Compositional Data Analysis
• Multivariate Statistical Analysis
• Data Fusion Methods
• +5 more

Daunis i Estadella, Pepus is an Associate Professor in the Department of Computer Science, Applied Mathematics and Statistics at the University of Girona, where he is also the Vice-Rector for Quality and Transparency since December 2017. He is a core member of the recognized research group GR-EADC (Research Group in Statistics and Compositional Data Analysis), supported by the Catalan government. His research interests include: Compositional Data Analysis Data Fusion Methods Multivariate Statistical Analysis Applications in Medical Imaging, Radiology, and Public Health Statistical Methodology in Geology and Archaeology The recent articles reflect a strong trend in applying advanced statistical techniques—particularly compositional data analysis and data fusion—to interdisciplinary domains such as healthcare, consumer behavior, geosciences, and archaeology. His work emphasizes methodological innovation and real-world application, especially in integrating heterogeneous data sources and improving multivariate analysis in medical and social contexts. Scientific contributions and recognitions include: Active publication in high-impact journals like Computational Statistics & Data Analysis and American Journal of Neuroradiology ORCID: 0000-0001-6134-9255 Researcher ID: B-9082-2011 Scopus Author ID: 14041287900 He has supervised various research projects and played key administrative roles, including former Coordinator of University Access Exams (PAU) and departmental secretary. He has contributed significantly to academic governance and statistical education. His work bridges theoretical statistics with practical applications across health, engineering, and social sciences. He is affiliated with the Grup de Recerca en Estadística i Anàlisi de Dades Composicionals (GR-EADC), a consolidated research team focused on advancing statistical methods for compositional and multivariate data.

Mustafa ÖzuysalView profile

Assistant Professor

• Computer Vision
• Object Detection
• Object Tracking
• +5 more

Mustafa Özuysal is an Assistant Professor in the Department of Computer Engineering at the College of Engineering, Izmir Institute of Technology (İYTE), where he leads the Visual Intelligence Research Group. His research focuses on computer vision, including object detection, tracking-by-detection, and real-time scene text recognition, with applications on mobile devices. Research Interests: Large-scale object detection Object detection and tracking on mobile platforms Real-time scene text recognition Feature learning from image and video sequences Augmented reality and camera egomotion estimation His scholarly work includes influential publications in IEEE TPAMI, IET Computer Vision, and top-tier conferences such as CVPR and ECCV, particularly in local feature descriptors like BRIEF and keypoint recognition using random ferns. His research emphasizes efficient, real-time algorithms suitable for embedded and mobile systems. Scientific Contributions: Co-developer of the BRIEF descriptor, widely used in computer vision for fast binary feature matching. Contributor to tracking-by-detection frameworks and homography estimation methods robust to occlusions and viewpoint changes. Dr. Özuysal has taught a range of undergraduate and graduate courses, including Introduction to Image Understanding, Vision-Based Tracking and Modeling, Data Structures, and Mobile Application Development. He advises the Visual Intelligence Research Group and continues to advance research in scalable and efficient vision systems.

Massimiliano Lo TurcoView profile

Professor

• 3D modeling
• Reconstructive modeling
• Augmented Reality (AR)
• +9 more

Massimiliano Lo Turco is a Full Professor at the Department of Architecture and Design (DAD) of the Polytechnic University of Turin. Specializing in digital modeling and cultural heritage, he actively contributes to the fields of Building Information Modeling (BIM), Heritage BIM (HBIM), and 3D reconstruction. University: Polytechnic University of Turin Department: Department of Architecture and Design (DAD) Academic Rank: Professor Research interests include: 3D modeling, reconstructive modeling, augmented/virtual reality, descriptive geometry, architectural representation history, digital cultural heritage, and parametric design. His work often bridges computational tools with heritage conservation. Recent publications demonstrate expertise in: HBIM for Baroque facades, digital preservation of Balinese architecture, parametric design education, and AI-BIM integration. These works align with his broader focus on digital strategies for heritage and sustainable architecture. Scientific awards: Effective member of Italian Union for Drawing (2015-) Associate Editor of Dn - Building Information Modeling, Data & Semantics (2018-) Grants and collaborations: Scientific Director for PhD scholarships in architectural heritage, Contract Manager for agreements with ASL Vercelli, Principal Investigator for research with CNR, and leader of multiple commercial and non-commercial projects with institutions like Museo Egizio and LINKS Foundation.

Mathieu HuruguenView profile

Lecturer

• Mathematics
• Geometry
• Linear Algebra
• +5 more

Mathieu Huruguen is a Lecturer at EPFL, specializing in foundational mathematics education. He delivers preparatory courses focusing on geometry, linear algebra, and analysis, emphasizing visualization and geometric contexts in dimensions 2 and 3. His teaching includes: Euclidean and hyperbolic geometries (historical foundations to modern acceptance) Linear Algebra (set theory, logic, and geometric applications) Analysis II (special functions: trigonometric, logarithmic, exponential) Mathematical education for engineering and science preparatory programs

Hans van DijkView profile

Researcher

• Biomedical Engineering
• Clinical Neurophysiology
• Electrophysiology
• +7 more

Hans van Dijk serves as a Senior Researcher in the Signal Processing Systems group within the Department of Electrical Engineering at Eindhoven University of Technology. He simultaneously holds leadership and research positions at multiple institutions, heading the Clinical Physics department at Kempenhaeghe (an institute specializing in Epileptology and Sleep medicine) and working as a Senior Researcher at the University Hospital in Ulm, Germany. His multidisciplinary career bridges engineering, clinical neurophysiology, and sleep medicine. Dr. van Dijk's research focuses on biomedical engineering applications in Clinical Neurophysiology, with particular expertise in electrophysiological techniques including EEG, EMG, and ECG. His work centers on developing and applying signal processing methods to diagnose neurological disorders, with specific emphasis on seizure detection using EEG , High-Density EMG for facial and masticatory muscles , and alternative diagnostic methods for sleep disorders . His recent publications demonstrate a strong focus on applying machine learning techniques to sleep medicine and epilepsy monitoring. Analysis of Dr. van Dijk's recent publications (2021-2025) reveals a consistent research trajectory in developing advanced signal processing methods for clinical neurophysiology. His work spans three main domains: epilepsy monitoring and seizure detection (particularly in children), sleep disorder diagnostics (using multimodal approaches beyond traditional polysomnography), and advanced EMG techniques for motor unit analysis. His research increasingly incorporates deep learning and multi-modal sensor fusion approaches to improve diagnostic accuracy while reducing the invasiveness of monitoring procedures. 2699 citations according to Scopus metrics 101 research outputs documented in institutional repository Active research collaboration with Philips Research and Kempenhaeghe Contributions to UN Sustainable Development Goals through medical diagnostics research Dr. van Dijk supervises research activities with 8 documented supervised works, collaborating extensively with clinical and engineering researchers across multiple institutions. His research program integrates signal processing expertise with clinical needs in neurology and sleep medicine, developing practical solutions for monitoring and diagnosing neurological disorders. His work at Kempenhaeghe focuses on translating engineering innovations into clinical practice for epilepsy and sleep disorder patients.

Christopher PalView profile

Associate Professor

• Artificial Intelligence
• Computer Vision
• Pattern Recognition
• +6 more

Christopher Pal is a Full Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal. With a Ph.D. from the University of Waterloo, he has held academic positions at the University of Rochester and the University of Toronto, and industry roles at Interval Research and Microsoft Research's Interactive Visual Media Group. Fields of Expertise: Artificial Intelligence, Computer Vision, Pattern Recognition, Machine Learning, and Natural Language Processing Affiliations: CIFAR Chair in Artificial Intelligence, Institute for Data Valorization (IVADO) Member His research focuses on deep learning applications in visual question answering , medical image segmentation , and generative models . Recent work involves multimodal data analysis for climate modeling and vision-language systems for code generation. Key projects include CarbonSense for climate flux modeling and GeoCoder for geometry problem-solving AI. His 15 most recent publications (2023-2025) span topics from diffusion models to multi-agent systems , with emphasis on video generation , 3D animation , and environmental applications . Scientific recognition includes: CIFAR Chair in Artificial Intelligence IVADO Institute Membership Top-2% cited researcher (2021) He has supervised 22 Ph.D. and Master's students, with recent graduates working on generative AI , reinforcement learning , and medical imaging . Current research grants include MITACS-funded projects in software engineering agents and drone imagery analysis for tropical forest conservation.

Bruce BartlettView profile

Associate Professor

• Low-dimensional topology
• Topological quantum field theory
• Mathematical physics
• +5 more

Bruce Bartlett is an Associate Professor in the Department of Mathematical Sciences within the Faculty of Science at Stellenbosch University, South Africa. His academic career spans positions including Senior Lecturer (2017-2023), Lecturer (2009-2013) at Stellenbosch University, and Research Fellow at Oxford University's Mathematical Institute (2013-2016) in the Quantum Mathematics and Computation group. His research focuses on low-dimensional topology and mathematical physics, with primary expertise in topological quantum field theory (TQFT). Key areas include modular categories, quantum invariants of 3-manifolds, conformal field theory, and applications to quantum computing. His work bridges abstract category theory with physical interpretations in quantum gravity and condensed matter systems. Recent interdisciplinary projects include statistical analysis of South African voter turnout (2019, 2024) and orbital mechanics simulations of Apollo missions. Analysis of his publication trends reveals consistent contributions to topological quantum field theory since 2010, with increasing interdisciplinary work in mathematical physics and data science applications. His most active research periods (2014-2017) produced foundational work on higher categories and modular forms, while recent years show expansion into public policy analysis and science communication through blog posts and media interviews. As an active member of the academic community, Bartlett maintains significant online presence through MathOverflow (1,831 reputation), TeX-LaTeX StackExchange (1,177 reputation), and specialized mathematics blogs. His work demonstrates strong connections between pure mathematics and physical applications, particularly in quantum computing frameworks.

• Numerical Analysis
• Partial Differential Equations
• Mathematical Physics
• +3 more

Eddy Brandon De Leon Aguilar is a Researcher at the Technical University of Munich (TUM) within the Department of Mathematics, School of Computation, Information and Technology. He specializes in the Numerics of Partial Differential Equations group, focusing on numerical solutions for high-dimensional time-dependent PDEs arising from physics, particularly through time-dependent Gaussian approximations. Dr. de Leon Aguilar completed his doctoral studies at the Université de Bourgogne in Dijon, France, where he subsequently held a temporary research position before joining TUM. His academic trajectory demonstrates a consistent focus on computational mathematical physics. His research integrates advanced numerical methods with theoretical physics, emphasizing: Numerical Analysis of Partial Differential Equations Mathematical Physics and General Relativity applications Theta function theory and Riemann surface geometry Spacetime visualization through ray tracing algorithms Computational approaches to the Schottky problem Gravitational lensing and black hole shadow modeling Recent publications (2024-2025) reveal a concentrated research program at the intersection of numerical mathematics and theoretical physics. Key themes include computational solutions to algebraic geometry problems, visualization of complex spacetimes, and ray tracing applications in general relativity. A unifying thread across these works is the innovative use of theta functions and Gaussian-based numerical techniques for solving high-dimensional physical systems. No scientific awards are documented in the available materials. Dr. de Leon Aguilar's current research activities center on the Numerics of Partial Differential Equations group at TUM, where he collaborates on developing efficient computational frameworks for time-dependent PDEs. His work bridges abstract mathematical theory with practical numerical implementations for physics applications, particularly in gravitational physics and geometric analysis.

Svetlana V. PorosevaView profile

Professor

• Turbulence Modeling
• Uncertainty Quantification
• Computational Fluid Dynamics
• +4 more

Dr. Svetlana V. Poroseva is a Professor at the Department of Mechanical Engineering, University of New Mexico (UNM), with a distinguished career in turbulence physics, uncertainty quantification, and bio-inspired design. Her work bridges computational fluid dynamics (CFD) with applications in renewable energy, power systems survivability, and aerospace engineering. Her educational background includes a Ph.D. in Fluid and Plasma Mechanics (1996) and an M.S. in Physics (1989) from Novosibirsk State University, Russia. She has held faculty positions at UNM since 2010, progressing from Assistant to Professor (2023). Her research focuses on high-order turbulence closures, data-driven modeling, and evidence theory for multi-model predictions, with a strong emphasis on quantifying uncertainty in simulations. Dr. Poroseva’s recent publications highlight advancements in bio-inspired rotor design, DNS analysis of mixing layers, and solar energy accessibility studies. She has developed software tools like FIESTA and Power System Graph Converter, both under open licenses. Her work spans turbulent flow validation, power grid topology optimization, and aerosol transmission modeling, particularly during the pandemic. Scientific Awards UNM School of Engineering Dean’s Excellence Lectureship Award (2022) Harrison Faculty Excellence Award (2021-2022) Rainforest Innovation Award (2022) AIAA Associate Fellow (2013) Fellowships at Stanford, CNRS, and CISM She advises numerous graduate and undergraduate students, leads the UNM AIAA Student Chapter, and collaborates internationally on projects involving NASA, Sandia, and European institutions.

Ulrich KortenkampView profile

Professor

• Mathematics Education
• Digital Learning Environments
• Place Value Understanding
• +3 more

Prof. Dr. Ulrich Kortenkamp is a Professor for Mathematics Education at the University of Potsdam since October 2014, holding a position in the Institute of Mathematics within the Faculty of Mathematics and Natural Sciences. He also serves as an Adjunct Professor at Griffith University in Gold Coast, Australia since May 2020. His academic career spans multiple institutions across Germany including Martin Luther University Halle-Wittenberg, University of Applied Sciences Karlsruhe, and TU Berlin. Prof. Kortenkamp's research focuses on mathematics education, particularly in the areas of digital learning environments, computational thinking development, place value understanding, and teacher education. His work bridges theoretical frameworks with practical applications in classroom settings, with a strong emphasis on the integration of technology in mathematics instruction. He has extensively studied how digital tools, particularly the Fingu app, can enhance early mathematical understanding and how language affects place value comprehension across different cultural contexts. His recent publications reveal a strong focus on sustainable development in teacher education, cross-linguistic studies of place value understanding, the impact of digital tools on early mathematics development, geometry education, and the integration of subject knowledge with didactic approaches in teacher preparation. His research consistently addresses how digital environments can transform mathematics teaching while maintaining strong conceptual foundations. Ars legendi Faculty Prize in Mathematics category (2020) for outstanding achievements in teaching, advising, and mentoring, awarded by the Stifterverband (Donors' Association) along with major German scientific societies Prof. Kortenkamp leads several significant research projects including DigiProMIN (developing digitally supported continuing education modules for mathematics teachers), Mathematics Education in the Digital Age (fostering international exchange between University of Potsdam and Griffith University), and Place Value Understanding (investigating primary school children's mathematical development across institutions in Germany and Australia). He is also involved in the SPIES-M project focused on quality initiatives for teacher education and the QuaMath project aimed at promoting teaching quality in mathematics through teacher training courses. He directs a research group focused on mathematics didactics at the University of Potsdam, collaborating with colleagues including Prof. Dr. Birte Friedrich and Prof. Dr. Sebastian Geisler, and working with a team of researchers on various aspects of mathematics education research, including digital learning environments, teacher professional development, and early mathematics concepts.

Tamás BenedekView profile

Associate Professor

• Fluid Mechanics
• Aeroacoustics
• Computational Fluid Dynamics (CFD)
• +3 more

Tamás Benedek is an Associate Professor at the Department of Fluid Mechanics, Budapest University of Technology and Economics (Faculty of Mechanical Engineering). His research focuses on aeroacoustics, computational fluid dynamics (CFD), and turbomachinery design optimization. He has published extensively on axial and radial flow fans, noise reduction techniques, and vortex dynamics. Education: Ph.D. in Fluid Mechanics (2018, BME) M.Sc. in Fluid Mechanics (2012, BME) Research Interests include: Tip leakage vortex quantification in axial fans Phased array microphone techniques for noise source localization CFD simulation of aeroacoustic phenomena Industrial fan design optimization for contaminated gas flows Acoustic duct design and flow-induced noise control Beamforming methods for rotating machinery diagnostics Publications highlight his work on: URANS simulations for vortex dynamics Hybrid CFD-experimental noise modeling Statistical analysis of turbulent flow effects on noise Blade geometry influence on aerodynamic loss coefficients Flow separation mechanisms in ducted systems Acoustic-transparent duct design Contact: benedek.tamas@gpk.bme.hu

Shira EpsteinView profile

Senior Lecturer

• Makerspace Development
• Engineering Education
• 3D Printing and Fabrication
• +5 more

Shira Epstein serves as Senior Lecturer in the Electrical and Computer Engineering Department at the University of Massachusetts Amherst College of Engineering and holds the position of Director of Campus Makerspaces. She also coordinates the Senior Design Project course and functions as an iCons Teaching Fellow. Her academic home is firmly within the engineering discipline, specifically in the Electrical and Computer Engineering department where she contributes to both teaching and makerspace development initiatives. Her educational background includes a Bachelor of Science in Electrical Engineering from the University of Southern California and a Master's degree in Computer Science from UMass Amherst. This dual foundation in both electrical engineering and computer science informs her interdisciplinary approach to education and makerspace development. Epstein's research and professional interests center around makerspace development, engineering education, and the application of geometric principles to practical fabrication. Her work with polyhedral structures using 3D printed magnetic tiles demonstrates how mathematical concepts can be transformed into tangible educational tools. She has developed modular construction systems that enable users to repeatedly assemble and disassemble complex geometric forms, distributing any manufacturing errors evenly through magnetic guidance. Her focus extends to creating accessible fabrication environments that serve students across all disciplines. Analysis of her publication history reveals a consistent focus on geometric modeling and educational fabrication tools, with significant contributions to polyhedral construction systems using OpenSCAD and 3D printing technology. Her work bridges theoretical geometry with practical applications in educational settings, emphasizing modular design principles and magnetic assembly systems that enhance the learning experience. As Director of Campus Makerspaces, Epstein launched the UMass Amherst Makerspace in 2019, creating a facility in Agricultural Engineering Building North Rooms 120 & 122 that serves as an interdisciplinary hub open to students, faculty, and staff from all majors. The makerspace operates with extensive hours (10am to 9pm daily during academic semesters) and provides access to tools, equipment, training, and mentorship. She oversees a student team of approximately 15 members representing diverse engineering and computer science disciplines who staff the facility and support users. The makerspace functions as a focal point for the campus maker community, hosting events and workshops while facilitating connections between makers and connecting groups with expertise and other maker resources. Epstein's leadership has established the space as a critical resource for hands-on learning and interdisciplinary collaboration across the university.

Barb CutlerView profile

Associate Professor

• Computer Graphics
• Interactive Visualization
• Computational Geometry
• +3 more

Barb Cutler is an Associate Professor in the Computer Science Department at Rensselaer Polytechnic Institute (RPI) and an affiliated faculty member at EMPAC (Experimental Media and Performing Arts Center). She specializes in computer graphics, interactive visualization, computational geometry, and open-source educational software. Previously, she was a student and Post-Doctoral Lecturer at MIT's Department of Electrical Engineering and Computer Science. Education: PhD in Electrical Engineering and Computer Science, MIT, August 2003 MEng in Electrical Engineering and Computer Science, MIT, June 1999 Research Interests: Her research spans computer graphics , interactive visualization , computational geometry , and the development of open-source educational tools . She has made significant contributions to architectural daylighting design, spatially augmented reality, and procedural modeling. Her work often integrates advanced visualization techniques with practical applications in education and architecture. Scientific Awards: NSF Early CAREER Award (2009) Rensselaer School of Science Outstanding Teaching Award (2017) Rensselaer Trustees' Outstanding Teacher Award (2019) Teaching & Advising: Barb Cutler has taught a wide range of courses including Data Structures, Advanced Computer Graphics, Interactive Visualization, and Computational Geometry. She has advised numerous PhD and MS students, many of whom have gone on to positions at leading companies and institutions. She is currently advising Evan Maicus, a PhD student in Computer Science. Lab & Projects: She leads the development of Submitty , an open-source homework submission, autograding, and TA grading system used widely in computer science education. Her lab focuses on innovative educational technologies and advanced visualization systems.