Find Academic Supervisors

• Probability
• Statistics
• Biostatistics
• +3 more

Bee Leng Lee is a Professor in the Department of Mathematics and Statistics at San José State University. She holds a Ph.D. and M.S. in Statistics from the University of Wisconsin-Madison and a B.Soc.Sci. in Statistics from the National University of Singapore. Her research focuses on probability, statistics, and biostatistics, with a strong emphasis on Bayesian methods, clinical trial design, and survival analysis. She has contributed to high-impact works such as dose-finding algorithms for phase I trials and applications of statistical methods in resolving legal disputes. Dr. Lee teaches a wide range of courses including Applied Probability and Statistics, Bayesian Data Analysis, Survival Analysis, and Computational Statistics. She has advised numerous student projects, including studies on stepwise variable selection limitations, generalized linear mixed models for categorical data, and Monte Carlo methods for financial derivatives. Her teaching also extends to foundational courses like Calculus I and Finite Mathematics. Her research projects include collaborations with industry sponsors like IBM (Almaden Research Center) on simulations and metamodeling. She actively publishes in top journals, with recent focus on balancing effective sample sizes in Bayesian designs and resolving contract disputes via statistical experimental design. Her work bridges theoretical statistics with practical applications in medicine, engineering, and public policy. Dr. Lee's contributions to statistical education and clinical trial methodology have positioned her as a key figure in advancing data-driven solutions at both academic and applied levels. She mentors students in cutting-edge statistical programming (R) and oversees special study projects that tackle real-world data challenges.

Daochen WangView profile

Assistant Professor

• Quantum Computing
• Quantum Algorithms
• Quantum Cryptography
• +3 more

Daochen Wang is an Assistant Professor of Computer Science at the University of British Columbia (UBC), affiliated with the Faculty of Science. His research focuses on quantum computation, quantum algorithms, and quantum cryptography, with an emphasis on understanding quantum speed-ups and their applications. Education: Ph.D. in Computer Science from the University of Maryland (advisors: Andrew Childs and Carl Miller), BA and MMath in Mathematics from the University of Cambridge. Research interests include quantum algorithm design, post-quantum cryptography, and the theoretical foundations of quantum computing. His work spans quantum graph algorithms, lattice-based security, and variational quantum eigensolvers. Teaching includes undergraduate (CPSC 436Q) and graduate (CPSC 536W) courses on quantum computation. He advises PhD student Xingyu Zhou and undergrad Rain Zimin Yang. Key research contributions include quantum algorithms for reinforcement learning, cryptographic security analysis of post-quantum schemes (e.g., CRYSTALS-Dilithium), and foundational studies on quantum speedups via symmetry analysis.

Brian KwonView profile

Professor

• Spinal Cord Injury Research
• Neuroprotection Strategies
• Biomarkers in Acute SCI
• +3 more

Dr. Brian Kwon is a Professor in the Department of Orthopaedics at the University of British Columbia (UBC), affiliated with the Faculty of Medicine. He is also an attending spine surgeon at Vancouver General Hospital and Principal Investigator at ICORD (International Collaboration on Repair Discoveries). His clinical focus includes adult spine trauma, spinal cord injuries, and non-traumatic conditions like infections and degeneration. Dr. Kwon leads the Kwon Lab for Spinal Cord Injury Research, emphasizing translational research to bridge clinical and laboratory findings. Education: PhD in Neuroscience (UBC, 2004) and a spine surgery fellowship in Philadelphia (2003). His research explores acute spinal cord injury management, biomarkers, implantable sensors, and hemodynamic strategies. Key projects include the International Spinal Cord Injury Biobank (ISCIB), which accelerates global SCI research through specimen sharing. Research Interests: Spinal cord injury mechanisms and therapies Neuroprotection and biomarker development Implantable sensor technology Hemodynamic management post-injury Recent articles focus on surgical techniques, biomarker landscapes, and clinical guidelines for SCI management. Awards: 2022 Distinguished G. Heiner Sell Lectureship from the American Spinal Injury Association (ASIA). Grants include $24M from Canada’s New Frontiers Fund for biomaterial-based SCI treatments. Labs/Teams: Kwon Lab at ICORD, collaborating globally via ISCIB. Advises students including Adam Doelman (SPR award winner), Cam, and Farnaz (ICORD symposium awardees).

Olivier SèteView profile

Researcher

• Numerical Mathematics
• Computational Complex Analysis
• Approximation Theory
• +3 more

Olivier Sète is a postdoctoral researcher in mathematics at Universität Ulm. His work focuses on numerical mathematics, computational complex analysis, and their applications in mathematics and sciences. He has held teaching roles at institutions including TU Berlin and Universität Greifswald, covering courses such as Numerical Linear Algebra, Analysis, and Partial Differential Equations. His research interests include approximation theory, numerical methods for the Helmholtz equation, conformal mapping, potential theory, and harmonic mappings in astrophysics. Notable contributions include the AAA algorithm for rational approximation, which earned the Frontiers of Science Award in 2023. His research spans topics like lemniscatic domains, polynomial pre-images, and stochastic Galerkin methods. He has developed software tools like the Transport of Images Toolbox for computing zeros of harmonic mappings. His work bridges theoretical mathematics with computational applications, addressing challenges in complex analysis and numerical methods. Awards include the Frontiers of Science Award for his work on the AAA algorithm. He has collaborated extensively with researchers such as Yuji Nakatsukasa and Lloyd N. Trefethen. His academic background includes a PhD from TU Berlin (2016) and a Diplom from TU Berlin (2009).

Ankush AggarwalView profile

Senior Lecturer

• Computational Biomechanics
• Cardiovascular Healthcare
• Soft Tissue Mechanics
• +3 more

Dr. Ankush Aggarwal is a Senior Lecturer in Engineering at the University of Glasgow, affiliated with the Glasgow Computational Engineering Centre (GCEC). His research focuses on computational biomechanics applied to cardiovascular healthcare, particularly in understanding soft tissue mechanics, heart valve dynamics, and medical image analysis. He holds a PhD in Mechanical Engineering from UCLA and has held postdoctoral positions at the University of Texas and Swansea University. Education: Bachelor's in Aerospace Engineering (Indian Institute of Technology, Kharagpur) PhD in Mechanical Engineering (University of California, Los Angeles) Research Interests: Dr. Aggarwal's work integrates advanced computational methods with clinical data to address cardiovascular challenges. His projects span four key areas: Computational modeling of heart valve mechanics Image-based strain estimation using 4D echocardiography Stochastic finite element analysis for soft tissues Multi-scale vascular modeling linking molecular to organ-level behavior Recent research trends show focus on translational applications like drug-coated balloon modeling and open-source tools for cardiac image workflows. His team develops Python packages (e.g., pyMechT) to democratize biomechanical simulations. Grants and Collaborations: EPSRC Centre for Future PCI Planning (2024-2027) Chan Zuckerberg Initiative Essential Software Award (2020-2021) National Research Network Fellowship (Swansea University, 2015-2018) Labs/Teams: Active contributor to GCEC, leading interdisciplinary projects combining biomechanics, imaging, and clinical translation. Mentor for 20+ graduate students across PhD, masters, and undergraduate levels.

Ming HanView profile

Professor

• Fiber Optics
• Optical Sensors
• Photonic Devices
• +6 more

Professor Ming Han is a faculty member in the Department of Electrical and Computer Engineering at Michigan State University's College of Engineering. He leads the Han Research Group focused on photonic devices and systems, specializing in fiber-optic sensing and actuation technologies. His work bridges fundamental research with real-world applications across multiple industries and scientific domains including energy research, homeland security, industrial process control, environmental monitoring, and biomedical applications. Dr. Han's research interests center on fiber-optic sensing/actuation devices and systems with particular emphasis on: Developing high-speed, high-resolution temperature sensors using silicon-tipped optical fibers with applications in oceanographic research and fusion energy Creating multiplexed acoustic emission sensors for structural health monitoring in challenging environments Innovating distributed fiber-optic ultrasound generation techniques for non-destructive testing Designing ultraminiature fiber-optic microphones for constrained spaces like ear canals Engineering fiber-optic environmental sensors with temperature self-compensation capabilities Analysis of Professor Han's recent publications reveals a strong focus on advancing fiber-optic sensor technologies with increasing sophistication in sensor design, fabrication methods, and signal processing techniques. His work shows a growing emphasis on multi-parameter sensing systems, integration with machine learning for signal analysis, and expanding applications in extreme environments including fusion plasma diagnostics. The research demonstrates consistent innovation in overcoming limitations of traditional sensing approaches through novel optical configurations and materials. Professor Han has received numerous professional recognitions including: Elevation to Fellow of SPIE for achievements in fiber-optic sensor research and development (2020) Selection as SPIE Community Champion for outstanding volunteerism (2020) Appointment as Associate Editor of Optical Engineering (2018) Selection as Topical Editor for Optics Letters (2022) Receiving the Edgerton Innovation Award and Faculty Research & Creative Activity Award from UNL College of Engineering (2014) Dr. Han has successfully mentored numerous graduate students to completion of their Ph.D. degrees, with graduates finding positions at organizations including Intel, Nusenics, and various academic institutions. His research has been significantly supported through collaborations with Naval Research Laboratory, Oak Ridge National Lab, and other institutions working on applications ranging from oceanographic research to magnetic confinement fusion. The Han Research Group actively recruits undergraduate researchers and participates in outreach activities including the MSU Science Festival and Girls Math Science Day events. The Han Research Group operates state-of-the-art facilities for the design, fabrication, and testing of photonic devices and fiber-optic sensor systems. The group maintains strong collaborations with national laboratories and industry partners, enabling translation of research into practical applications. Current research directions include advancing silicon-tipped fiber-optic sensors for extreme environments and developing AI-enhanced signal processing for structural health monitoring systems with applications in rail inspection and industrial process control.

Frédéric MilaView profile

Professor

• Condensed Matter Theory
• Quantum Magnetism
• Frustrated Spin Systems
• +5 more

Frédéric Mila is a full Professor and Chair of Theoretical Condensed Matter Physics at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Basic Sciences (SB), Institute of Physics (IPHYS), and the Condensed Matter Theory Group (CTMC). He also holds roles in the Doctoral Program in Physics (EDPY) and the School of Physics and Engineering (SPH-ENS). His research centers on quantum magnetism, frustrated systems, and strongly correlated electrons. His research interests include quantum magnetism, frustrated spin systems, quantum phase transitions, tensor network methods, and quantum spin liquids . He employs both analytical approaches and advanced numerical techniques to study complex quantum phenomena in low-dimensional and geometrically frustrated materials. His recent publications reveal a strong focus on magnetization plateaus, quantum dimer models, spin liquids, and high-field quantum phases , particularly in compounds like SrCu2(BO3)2 and theoretical models such as the Shastry-Sutherland and triangular lattice antiferromagnets. His work often bridges theory with experimental findings from neutron scattering and high-field measurements. Scientific Awards: Charpak-Ritz Prize (2024) – Awarded by the French and Swiss Physical Societies. Advising and Grants: Prof. Mila actively mentors a large group of doctoral students and has supervised numerous PhD theses at EPFL. His students have worked on diverse topics including SU(N) spin chains, tensor networks, frustrated magnetism, and quantum Monte Carlo methods. His sustained publication record in top journals indicates continuous funding and active research leadership. Labs and Teams: He leads the Condensed Matter Theory Group (CTMC) at EPFL, which focuses on theoretical and computational aspects of quantum materials. The group collaborates closely with experimentalists and uses state-of-the-art numerical tools to investigate quantum phases of matter.

Gudrun Ahn-ErcanView profile

Professor

• Wood Science
• Applied Mathematics
• Numerical Analysis
• +3 more

Gudrun Ahn-Ercan is a Professor of Numerical Mathematics and Applied Statistics at the Faculty of Wood Engineering, Eberswalde University for Sustainable Development . Her research focuses on mathematical modeling of wood material behavior, particularly springback effects in laminated wood stacks. She collaborates with Alexander Pfriem and Moritz Sanne on projects like the "Bambulator" (renewable material walker), addressing industrial challenges in wood lamination processes. Her work includes peer-reviewed publications such as the 2020 Forests article on springback prediction in beech laminates. Key findings include a statistical formula correlating springback with lamination count and elasticity values, validated through experimental data. She utilizes programming languages like R for regression analysis and finite element modeling to bypass trial-and-error methods. Contact: Gudrun.Ahn-Ercan@hnee.de

Shuai ZhuView profile

Researcher

• Computational Mechanics
• Composite Materials
• Multiphysics Modelling
• +3 more

Shuai Zhu is a Research Associate in the Department of Mechanical Engineering at the University of Bath, specializing in computational mechanics and advanced material systems. His work bridges theoretical modeling with experimental validation to solve complex engineering challenges in aerospace and manufacturing sectors. Education: Doctor of Engineering in Mechanical Engineering, Cardiff University (2021-2024) Dr. Zhu's research centers on multiphysics modeling of composite materials and structures, with expertise in soft robotics, solid mechanics, and computational fluid dynamics. He leverages industry-standard tools like ABAQUS, ANSYS, and COMSOL to simulate material behavior under extreme conditions, focusing on failure mechanisms, manufacturing processes, and structural integrity. His fingerprint reveals deep specialization in carbon fiber composites, stiffened panels, and high-entropy alloys. Analysis of his 2021-2025 publications shows a consistent trajectory in computational mechanics: early work established foundations in co-curing processes and impact dynamics, while recent studies explore crystal plasticity in bi-layered high-entropy alloys and damage accumulation in heterogeneous laminates. This evolution demonstrates growing sophistication in multi-physics coupling and experimental-numerical validation frameworks. Scientific Awards: Best Student Presentation Prize at Cardiff University Advancements in Atomic Force Microscopy (AFM) Symposium (2023) Dr. Zhu actively disseminates findings through international conferences including ICMR2024 and the World Congress on Micro and Nano Manufacturing (2023). While no formal student supervision or grant awards are documented in the source material, his collaborative network spans Cardiff University, Bath, and global institutions as evidenced by multi-author publications. His research directly supports UN Sustainable Development Goals through sustainable manufacturing and advanced materials innovation. He operates within Bath's computational mechanics research ecosystem, collaborating on projects involving carbon fiber composites, laminated structures, and soft robotics systems, with strong industry-aligned applications in aerospace and automotive sectors.

• Wood Mechanics
• Timber Engineering
• Numerical Modeling
• +3 more

Michael Schweigler is a Senior Lecturer at the Department of Building Technology , Linnaeus University , Sweden. His work integrates research, teaching, and supervision, focusing on wood mechanics and timber engineering. He earned his PhD from the Vienna University of Technology (TU Wien) , where he studied dowel joints in timber structures. His expertise bridges experimental and numerical methods in mechanics, applied to sustainable wood materials. Research Focus: Connections in Timber Structures Cross-Laminated Timber (CLT) Wood Building Technology Composite and Hybrid Structures Teaching: Building Technology Steel and Timber Structures Conceptual Structural Design (Master's course) Projects: Competitive Timber Structures Improving CLT Systems Long-Term Mechanical Behavior of Dowel Connections Moisture Effects on South Swedish Hardwood His recent research explores advanced computational models for timber connections, emphasizing nonlinear behavior, embedment properties, and sustainability. Collaborations with industry and standardization groups aim to translate scientific findings into practical design tools. Publications span journals like Wood Material Science & Engineering and Engineering Structures , covering topics such as: CLT wall-to-floor connections Dowel-type fastener performance Thermally modified wood Hybrid timber-steel systems Numerical modeling of multi-fastener joints Embedment behavior under varying load conditions He contributes to scientific datasets , including a comprehensive database of embedment parameters from soft- and hardwoods, supporting global timber engineering research.

Thomas TrösterView profile

Professor

• Lightweight Construction
• Automotive Engineering
• Composite Materials
• +4 more

Professor Thomas Tröster serves as Vice President at the University of Paderborn and holds the Professorship for Lightweight Construction in Automobiles within the Faculty of Mechanical Engineering. He is Chairman of the Institute for Lightweight Construction with Hybrid Systems (ILH) and a board member of the Profile Area Sustainable Materials, Processes and Products. Professor Tröster completed his physics studies at the University of Paderborn (1983-1989), earned his PhD in High Pressure Physics in March 1994, and completed his habilitation in Experimental Physics in 2003. He has held academic positions at the Cologne University of Applied Sciences (2005-2007) and has extensive industry experience with Benteler Automotive Technology GmbH. His research focuses on advanced lightweight construction techniques for automotive applications, with particular expertise in composite materials, additive manufacturing, and multi-material design. Professor Tröster's work bridges theoretical materials science with practical automotive engineering applications, emphasizing resource efficiency and sustainable manufacturing processes. His current research portfolio includes projects on metal-carbon fiber reinforced plastic hybrid structures, anisotropic material behavior analysis, and innovative 3D printing techniques for automotive components. Professor Tröster's recent publications demonstrate a strong focus on composite joining technologies, additive manufacturing optimization, and structural analysis of non-conventional joint designs. His work consistently addresses practical engineering challenges while advancing fundamental understanding of material behaviors under complex loading conditions and manufacturing constraints. Professor Tröster has supervised numerous industry-related research topics including the production and validation of electrically powered autonomous racing cars. He has directed major research initiatives such as the Research College 'Light-Efficient-Mobile' (2014-2022) and leads current projects including power2AM, NeMo.bil, and TRR 285 Subproject B01. As Chairman of the Institute for Lightweight Construction with Hybrid Systems since 2012, Professor Tröster leads a multidisciplinary research team focused on developing innovative lightweight solutions for the automotive industry. The institute maintains strong collaborations with automotive manufacturers and component suppliers, facilitating the rapid transfer of research findings into practical applications.

Kai-Uwe BletzingerView profile

Professor

• Computational Mechanics
• Structural Engineering
• Finite Element Analysis
• +5 more

Kai-Uwe Bletzinger is a Professor and Chair of Statics and Dynamics at the Technical University of Munich's School of Engineering, Department of Civil, Geo and Environmental Engineering. With an extensive publication record spanning from 1991 to 2025 totaling 246 publications, he maintains an active research program in computational structural engineering. His research productivity shows consistent output with significant activity in recent years, particularly in 2022-2025. Professor Bletzinger's research focuses on computational mechanics with specializations in Finite Element Analysis , Shape Optimization , Form Finding , Computer-Aided Design , Membrane Structures , and Fluid-Structure Interaction . His work bridges theoretical computational methods with practical engineering applications, particularly in structural optimization and analysis. The fingerprint of his research shows strong emphasis on numerical methods for structural engineering problems. Analysis of his recent publications (2022-2025) reveals a consistent focus on advancing computational methods for structural optimization, particularly through the Vertex Morphing technique. His work increasingly integrates modern computational approaches including machine learning applications in structural dynamics and digital twin technologies for construction. The research spans fundamental numerical method development to practical applications such as the tensegrity tower for the German Museum in Munich, demonstrating both theoretical depth and practical relevance. While specific awards are not mentioned in the provided text, his extensive publication record in high-impact engineering journals suggests recognition within the computational mechanics community. His research appears to be well-funded given the consistent output and collaborative nature of many publications. Professor Bletzinger's work demonstrates leadership in computational structural engineering, with particular expertise in developing and applying advanced numerical methods to complex structural problems. His research group appears to be active in both fundamental method development and practical engineering applications, contributing significantly to the field of computational mechanics and structural engineering.

• Physics Education Research
• STEM Education
• Quantum Physics
• +3 more

Claudia De Grandi serves as an Associate Professor (Lecturer) in the Department of Physics & Astronomy at the University of Utah, where she has been since 2015. Her academic journey began with theoretical physics research before transitioning to physics education, where she now focuses on developing innovative teaching practices and inclusive learning environments. She has held positions as Helmsley Teaching Scholar (2015-2018), Assistant Professor (Lecturer) (2018-2022), and was promoted to Associate Professor (Lecturer) in 2022. Dr. De Grandi's educational background includes a PhD in Condensed Matter Theory from Boston University (2011) and an MS in Physics from the University of Milan, Italy (2005). Her research interests have evolved from quantum physics to primarily physics education research, with a strong focus on student belonging, assessment methods, and curriculum development for life sciences students. Her scholarly work reveals a clear transition from theoretical quantum physics to physics education research. The earliest publications (2007-2015) focus on quantum dynamics, quenches near critical points, and Bose-Hubbard systems, while her more recent work (2019-2023) centers on educational innovation, student engagement, and inclusive teaching practices. This trajectory demonstrates her successful transition from research physicist to education specialist. Her 2023 textbook "Introductory Physics for the Life Sciences" represents a major contribution to physics education literature, designed specifically for biology and premedical students. Dr. De Grandi has received significant recognition for her teaching excellence: Early Career Teaching Award from University of Utah (February 2023) College of Science Distinguished Educator Award from University of Utah (March 2022) Her teaching philosophy emphasizes active learning, student engagement, and creating inclusive environments. She has taught numerous sections of "Physics for Science & Engineering" and developed the innovative "Being Human in STEM" course. Her research shows particular interest in how assessment formats affect student performance across different demographic groups, with findings indicating that social belonging impacts performance even on non-traditional assessments. She has also pioneered the use of open-source videos for flipped classrooms and developed comprehensive STEM climate surveys through student-faculty collaboration.

• Aerospace Engineering
• Structural Dynamics
• Finite Element Analysis
• +3 more

Dr. Maria Ribeira Vicent is a Research Fellow at the University of Surrey, focusing on spacecraft finite element modeling and structural dynamics. Her work addresses the correlation between computational finite element models (FEMs) and physical spacecraft structures, ensuring accuracy in predicting launch and flight loads. She investigates modal parameter estimation techniques, sensor placement strategies, and FEM reduction methods to enhance efficiency in model validation. Her research employs two large scientific spacecraft as case studies, analyzing vibration test data from base-shake sine-sweep campaigns. Key contributions include identifying optimal pre-test sensor configurations, addressing inaccuracies in FEM reduction, and improving target mode selection criteria aligned with mission-specific loading scenarios. These findings aim to streamline correlation processes and reduce time-to-accuracy in spacecraft structural analysis.

Ajay B. HarishView profile

Senior Lecturer

• Computational Mechanics
• Finite Element Methods
• Machine Learning
• +7 more

Ajay B. Harish serves as a Senior Lecturer in Engineering Simulation and Data Science within the Mechanical and Aerospace Engineering Department at the University of Manchester's School of Engineering. His research bridges computational mechanics with real-world applications across biomedical engineering, materials science, and quantum computing paradigms. Education: Doctor of Engineering, Leibniz Universitat Hannover (2018) Master of Engineering, California Institute of Technology (2009) Bachelor of Technology, National Institute of Technology Karnataka, Surathkal (2007) Dr. Harish's research spans computational mechanics at the intersection of mechanics, materials science, and biology. His work develops advanced computational methods including finite element techniques, machine learning, uncertainty quantification, and quantum computational mechanics. Current applications focus on biomedical engineering challenges such as mathematical ophthalmology, neurovascular and cardiovascular flow modeling, tendon mechanics, and advanced materials development using tensegrity technology. His lab pioneers quantum algorithms for quantum-scale material interactions and chaotic fluid dynamics simulation. Analysis of his recent publications reveals a strong focus on computational mechanics innovations applied to biological systems and advanced materials. His work demonstrates consistent integration of classical and quantum computing approaches to solve complex mechanical problems, with increasing emphasis on biomedical applications and multi-physics coupling in recent years. Scientific Awards: 2024 UK-Italy Trustworthy AI Fellowship by the Alan Turing Institute 2022 Ramanujan Fellowship from the Government of India 2017 Best researcher in Mechanics by Leibniz Foundation 2016 Viktor-Rizkallah Award for best international researcher Dr. Harish actively supervises PhD students and has secured approximately £2 million in competitive research funding from sources including the British Foundation, Alan Turing Institute, Innovate UK, and Impact Acceleration Account. His Fluids Research Group collaborates across multiple institutions, with recent secondments to A*STAR and Jawaharlal Nehru Center for Advanced Scientific Research. He serves on the editorial board of Extreme Mechanics Letters and supports undergraduate, postgraduate, and postdoctoral researchers through hands-on projects with industry implications. Harish Lab at the University of Manchester develops novel computing paradigms for demanding environments, focusing on continuum mechanics through computer modeling and experiments. The lab's three-pronged approach includes quantum computing for quantum-scale interactions, data-driven methods using graph neural networks for biomedical applications, and classical finite element methods for advanced materials and fluid-structure interaction problems.