جست‌وجوی استاد و پژوهشگر

• Partial Differential Equations
• Mathematical Biology
• Quantum Mechanics
• +۴ مورد دیگر

Peter Markowich is a Professor at the Department of Mathematics, Faculty of Mathematics, with a prolific research career spanning over three decades. His work bridges Partial Differential Equations (PDEs) , Mathematical Biology , and Quantum Mechanics , focusing on modeling complex systems across disciplines. Key research themes include biological network formation (e.g., blood vessel and plant vein structures), nonlinear Schrödinger equations for quantum systems, and reaction-diffusion dynamics in chemotaxis and pedestrian flow. Recent publications (2023-2025) explore self-regulated biological transportation structures, tensor PDE models, and orbital stability of standing waves in fractional quantum systems. 2025 : Condition number analysis in biological network PDEs 2024 : 1D entropy dissipation models 2023 : Gradient flows for network emergence and Hughes’ pedestrian model theory His methodological contributions include numerical schemes for multiscale problems (e.g., XFEL simulations) and analytical frameworks for existence/uniqueness in singular PDEs. Collaborations span global institutions, with co-authors like Y. Cho, C. Sparber, and H. Hajaiej.

Felix Wiesnerمشاهده پروفایل

استادیار

• Structural Fire Engineering
• Fire Safety of Timber Structures
• Cross-laminated Timber (CLT)
• +۹ مورد دیگر

Dr Felix Wiesner is an Assistant Professor at the University of British Columbia and an Honorary Fellow at the School of Civil Engineering, University of Queensland , contributing to the National Centre for Timber Durability and Design Life . His work focuses on enhancing timber's fire performance through treatments, modifications, and advanced structural analysis. Education: Master of Engineering and PhD in Structural and Fire Safety Engineering (University of Edinburgh), Postgraduate Diploma in Data Science (Harvard University) Key research interests include structural fire engineering , fire safety of engineered timber , and bushfire performance of native Australian species . His recent publications address large-scale fire experiments , smouldering inhibition , and self-extinction frameworks for mass timber. Funded Projects: ARC Research Hub (2021–2026), XLam Australia donation (2020–2021) Collaborations: European COST Action FP1404, BRE Tall Timber Construction, global Fire Safe Use of Wood Dr Wiesner has developed innovative tools like a robotic drilling system for timber instrumentation and award-winning image analysis techniques. He supervises PhD projects on flame spread complexity , smouldering inhibitors , and intumescent coatings , though currently unavailable for new supervision.

Mingyuan Luمشاهده پروفایل

مدرس ارشد

• Materials Engineering
• Mechanical Engineering
• Additive Manufacturing
• +۲ مورد دیگر

Dr. Mingyuan Lu serves as a Senior Lecturer at The University of Queensland's School of Mechanical and Mining Engineering and is an Affiliate of the Centre for Advanced Materials Processing and Manufacturing (AMPAM). With over a decade of research experience, she specializes in nanomechanical characterization and advanced manufacturing techniques for materials engineering applications spanning aerospace, biomedical, and energy sectors. Her educational background includes: PhD in Mechanical and Mining Engineering from The University of Queensland (2014) Masters of Engineering in Materials Science and Engineering from Central South University, China (2009) Bachelor of Engineering in Materials Science and Engineering from Central South University, China (2007) Research interests center on laser-based surface engineering, additive manufacturing of biodegradable scaffolds, and nanomechanical testing methodologies. She pioneered the FIB-machined micro-cantilever bending technique for interfacial adhesion assessment of multilayer systems and developed selective laser sintering processes for bone tissue engineering scaffolds without artificial 3D models. Current projects focus on pre-clinical mouse model testing of scaffolds and laser deposition of titanium oxide coatings for aerospace components. Recent publications (2023-2025) reveal strong interdisciplinary trends: nanomechanical characterization methods dominate 50% of outputs, while additive manufacturing (30%) and computational modeling (20%) address applications in biomedical devices, semiconductor reliability, and petroleum engineering. The work consistently integrates experimental techniques like electron microscopy with simulations for wear resistance, biodegradation, and interfacial failure analysis. No scientific awards, fellowships, or medals are documented in the provided materials. Dr. Lu actively manages major grant funding as Principal Investigator and Associate Advisor. Current projects include the ARC Research Hub for Future Digital Manufacturing (2024-2029) and ARC Training Centre for Innovative Composites (2023-2028). Past grants feature an ARC DECRA award (2019-2024) for micro/nano-mechanical testing and industry collaborations with WIN Semiconductor, Baosteel, and HBIS Group on ceramic coatings and semiconductor reliability. She supervises four PhD students as Principal Advisor with completed projects including PHBV scaffold evaluation and laser surface engineering for tribological applications. She is embedded in UQ's Nanomechanics and Nanomanufacturing research group, leveraging AMPAM's resources for collaborative industry-facing work. Her technical leadership in focused ion beam (FIB) micromachining and laser processing directly supports the Centre's mission in translating materials research into manufacturing solutions.

Michael Mahoneyمشاهده پروفایل

استاد

• Randomized Numerical Linear Algebra
• Machine Learning
• High Dimensional Statistics
• +۳ مورد دیگر

Michael Mahoney is Professor of Statistics at the University of California, Berkeley, with additional affiliations at the International Computer Science Institute (ICSI) where he is Vice President and Director of the Big Data Group, the Lawrence Berkeley National Laboratory (LBNL) where he leads the Machine Learning and Analytics Group, and the EECS department's RISELab. He is also an Amazon Scholar. Education: While specific degrees are not listed in the provided text, his extensive record of teaching, research leadership, and publications indicates doctoral-level training in Statistics and Computer Science. Research Interests: Mahoney's work centers on the applied mathematics of data , spanning algorithmic and statistical foundations of big data, randomized numerical linear algebra (RandNLA), high-dimensional statistics, machine learning, and scientific machine learning. He develops theory, scalable implementations, and real-world applications in internet analytics, social networks, genetics, astronomy, and climate science. Recent software contributions include the RandBLAS and RandLAPACK libraries (standardizing RandNLA routines), Landscaper for visualizing deep-learning loss landscapes, and packages such as FreeAlg , DetKit , Imate , and LeaderBot . Awards & Honors: NeurIPS 2020 Best Paper Award (co-authored work on column subset selection) Director, NSF TRIPODS UC Berkeley FODA Institute Key contributor to the BALLISTIC project for next-generation BLAS/LAPACK Grants & Leadership: Principal Investigator, NSF TRIPODS FODA Institute (Foundations of Data Analysis) Group Lead, Machine Learning and Analytics, LBNL Vice President & Director, Big Data Group, ICSI Advising & Mentoring: Mahoney has an extensive network of current and former PhD students, postdocs, and visiting researchers, including placements at MIT, Stanford, Waterloo, Stevens, Tsinghua, and Georgia Tech. Current advisees include Shengaho Yang, Zhichao Wang, Hyunsuk Kim, and Pu Ren, among many others. Labs & Teams: He directs research efforts across UC Berkeley Statistics, ICSI’s Big Data Group, LBNL’s Machine Learning and Analytics Group, and the RISELab (formerly AMPLab), fostering cross-disciplinary collaboration between statistics, computer science, and domain sciences.

• Applied Mathematics
• Dynamical Systems
• Neuroscience
• +۴ مورد دیگر

Stanislav M. Mintchev is a Professor of Mathematics at The Cooper Union for the Advancement of Science and Art, affiliated with the Albert Nerken School of Engineering and the Department of Mathematics. His work bridges applied mathematics and dynamical systems theory with applications in physical and biological sciences. Education: Ph.D. in Mathematics (2008) from Courant Institute (NYU), B.S. in Physics and Mathematics (2002) from George Washington University Research focuses on applied dynamical systems, particularly traveling wave solutions in pulse-coupled neural networks and data mining algorithms for time-dependent data. His work has implications for signal processing in neuroscience and mathematical biology. Recent publications examine stability of traveling waves, oscillation models, and network resilience. Scientific contributions include collaborations on neuronal network dynamics and mathematical modeling of biological phenomena. Awards include the Educational Innovation Grant Program (2021) and invited presentations at academic conferences. Teaching interests span Linear Algebra, Calculus, and advanced topics like Dynamical Systems and Numerical Methods. He mentors students preparing for the Putnam Examination and has taught diverse courses in mathematics and its applications since 2005. Current research in progress explores traveling waves in coupled oscillator systems and Dirac impulse coupling in neural networks. His work combines analytical rigor with computational simulations to study self-organization phenomena.

• Deep Reinforcement Learning
• Evolutionary Robotics
• Computational Logistics
• +۳ مورد دیگر

Djordje Grbic is a Lecturer at the IT University of Copenhagen, actively contributing to research in artificial intelligence, robotics, and maritime logistics. He is affiliated with the Creative AI Lab, Robotics, Evolution, and Art Lab, and The Maritime Hub Robotics, Evolution and Artificial Life Lab. His research focuses on: Deep reinforcement learning for complex planning tasks Evolutionary computation in artificial life systems AI optimization of maritime container stowage Procedural content generation for games Sequence evolution simulations for biological systems Recent publications (2023-2024) demonstrate expertise in applying deep reinforcement learning to maritime logistics problems and developing systems for sequence evolution simulation. Collaborations span computational logistics, bioinformatics, and game design domains. Current affiliations include: Creative AI Lab (ITU Copenhagen) Robotics, Evolution, and Art Lab The Maritime Hub for logistics research

Christos Chousidisمشاهده پروفایل

مدرس ارشد

• Biomedical Acoustics
• Wireless Audio Networks
• Machine Learning
• +۶ مورد دیگر

Dr. Christos Chousidis is a Senior Lecturer in Audio Electronics at the University of Surrey 's Institute of Sound Recording (IoSR) within the School of Arts and Social Sciences. His research focuses on Biomedical Acoustics and Wireless Audio Networks , with additional expertise in Machine Learning, Audio Signal Processing, and Human-Computer Interaction.

• High Energy Astrophysics
• Dark Matter Detection
• Gamma-ray Astronomy
• +۴ مورد دیگر

Dr. Anthony Brown is an Assistant Professor in the Department of Physics at Durham University, affiliated with the Institute of Hazard, Risk and Resilience. His research focuses on high-energy astrophysics and dark matter detection through gamma-ray observations. Key research areas: Dark Matter Detection, Gamma-ray Astronomy, Cherenkov Telescopes, Cosmic Ray Interactions Instrumentation expertise: Atmospheric Cherenkov Detectors, Balloon-borne Platforms, UAV Calibration Systems Supervision: Mentored three postgraduate research students (Amrit Nayak, Ed Dewit, Ieva Jankute) Recent publications highlight his work on Cherenkov Telescope Array calibration techniques (2022), millisecond pulsar gamma-ray modeling (2024), and dark matter signatures in globular clusters (2018). His research spans ultra-high energy neutrino detection (2021), extragalactic cosmic ray propagation (2017), and multi-messenger astronomy approaches combining gamma-ray and neutrino observations (2015). Scientific contributions include: Development of airborne calibration systems for ground-based observatories Analysis of gamma-ray emission from active galactic nuclei (2017-2024) Investigations into dark matter annihilation signatures in galaxy clusters Innovations in stratospheric imaging telescope performance (2020) Current projects involve the Cherenkov Telescope Array's line search capabilities for dark matter (2024) and studying pulsar geometry effects on emission spectra (2024). His work bridges experimental astrophysics with particle physics, particularly in high-energy cosmic phenomena and neutrino detection.

• Soft Robotics
• Rehabilitation Robotics
• Bioinspired Robotics
• +۳ مورد دیگر

Maria Giannaccini is an Honorary Lecturer at the School of Engineering, University of Aberdeen. Her research focuses on soft robotics, rehabilitation systems, and bioinspired designs, often integrating control systems and human-robot interaction principles. Research Interests: Soft Robotics for Medical Applications Control Systems in Pneumatic Actuators Bioinspired Robotic Simulators Tactile Sensing and Haptic Feedback Human-Robot Cognitive Interaction Recent publications highlight advancements in wearable rehabilitation devices, neural network-based actuator control, and auditory-induced perceptual distortions in robot motion prediction. Her work spans both theoretical and applied robotics, with collaborations across engineering and medical disciplines. Key Article Trends: Soft Robotics: 40% of publications Rehabilitation & Medical Robotics: 30% Control Systems & AI: 25% Human-Robot Interaction: 20% Biomimetic Sensors: 15%

• Computer Science
• Artificial Intelligence
• Bayesian Networks
• +۳ مورد دیگر

Dr. ir. Janneke Bolt is a Researcher at the Department of Information and Computing Sciences , Faculty of Science , Utrecht University . Her work focuses on Bayesian networks , probabilistic graphical models , and independence relations in Artificial Intelligence and Data Science . She has published extensively on topics such as probabilistic independence , loopy propagation , and sensitivity functions . Her recent research includes self-adhesivity in lattices of abstract conditional independence models and Bayesian network applications in medicine . Collaborators include L.C. van der Gaag and S. Renooij . Research Areas: Bayesian Networks Probabilistic Inference Independence Relations Machine Learning Uncertainty Quantification Medical AI Recent Publications (2025-2014): Self-adhesivity in Lattices (2025) Bayesian Networks in Medicine (2024) Semi-Graphoid Rule Generalizations (2023) Lattice-Based Independence Representations (2020) Multi-Dimensional Bayesian Classifier Tuning (2016) Collaborations: L.C. van der Gaag S. Renooij J. de Bock A. Hommersom

Neil Kingمشاهده پروفایل

دانشیار

• Computational Protein Design
• Self-Assembling Protein Nanomaterials
• Vaccine Development
• +۴ مورد دیگر

Neil King, PhD , is an Associate Professor in the Department of Biochemistry at the University of Washington School of Medicine and Deputy Director of the Institute for Protein Design . His research focuses on computational protein design for creating self-assembling protein nanomaterials with applications in vaccine development , targeted drug delivery , and hybrid biomaterials . Education: PhD in Biochemistry (UCLA, Todd Yeates Lab) BS in Biomedical Engineering (Northwestern University) His research interests span: Developing atomic-level accurate nanomaterials using computational tools Next-generation structure-based vaccines for influenza and coronaviruses Membrane-interacting hybrid materials inspired by viral mechanisms Extending design capabilities to machine learning-driven platforms The article trends demonstrate a progression from foundational computational methods (Bale et al., 2016; Sheffler et al., 2023) to AI-enhanced vaccine platforms (2025 preprints) and hybrid biomaterials (Herpoldt et al., 2024; Butterfield et al., 2017). Key subfields include self-assembly algorithms , antigen presentation , membrane fusion systems , machine learning integration , malaria vaccine platforms , and deep mutational scanning . Neil leads a translational research group that combines de novo protein design with preclinical evaluation , supported by grants from the Open Philanthropy Project . His lab has mentored students like Priya (Distinguished Researcher award), Cameron Criswell (PhD graduate), and Cara Chao (PhD graduate).

Heike Valleryمشاهده پروفایل

استاد

• Bipedal Locomotion
• Robotics
• Dynamics
• +۴ مورد دیگر

Prof. Dr.-Ing. Heike Vallery is a leading academic in robotics and rehabilitation engineering, holding a full professorship at RWTH Aachen University's Institute of Automatic Control and a part-time professorship at TU Delft. She also holds an honorary professorship at Erasmus MC Rotterdam's Department for Rehabilitation Medicine. Her research focuses on robotic assistance for gait disorders through minimalistic concepts like wearable gyroscopic actuators. Education : Dipl.-Ing. in Mechanical Engineering (2004), RWTH Aachen Dr.-Ing. (2009), Technische Universität München Research Interests : She specializes in modeling and control of bipedal locomotion, compliant actuation, and assistive devices. Her work bridges robotics, biomechanics, and clinical applications, particularly for neurorehabilitation and prosthetics. Scientific Awards : Alexander von Humboldt Professorship Vidi Fellowship (2016), Netherlands Organisation for Scientific Research euRobotics Technology Transfer Award 1st Prize (2014) Academic Leadership : She leads the Institute of Automatic Control at RWTH Aachen and maintains affiliations with TU Delft and Erasmus MC Rotterdam. Her lab develops solutions like the RYSEN body weight support system and ERiK prosthetic leg.

Uwe Schmockمشاهده پروفایل

استاد

• financial mathematics
• actuarial mathematics
• insurance mathematics
• +۷ مورد دیگر

Uwe Schmock is a Full Professor at the Vienna University of Technology , leading research in Financial and Actuarial Mathematics within the Institute for Statistics and Mathematical Methods in Economics. His work bridges theoretical probability with practical financial and insurance risk modeling. Research interests include large deviations theory , risk aggregation , credit risk models , and stochastic integration . He has contributed to insurance mathematics through catastrophe bond analysis (e.g., WinCAT coupons) and annuity valuation tables. His recent publications focus on U-empirical measures , Panjer's recursion , and exotic options under market constraints. Scientific awards include the Charles A. Hachemeister Prize and the David Garrick Halmstad Memorial Prize . He actively collaborates with institutions like ETH Zurich and the American Casualty Actuarial Society.

Eric C. Alstonمشاهده پروفایل

پژوهشگر ارشد

• Law and Economics
• Institutional Analysis
• Blockchain Governance
• +۵ مورد دیگر

Eric C. Alston is a Research Fellow and Scholar in Residence at the Finance Division of the Leeds School of Business , University of Colorado Boulder . He also serves as Faculty Director for the Hernando de Soto Capital Markets Program and acts as a Research Associate with the Comparative Constitutions Project . MA in Economics, University of Maryland JD, University of Chicago Alston's research spans law and economics , institutional analysis , and digital governance , with a focus on blockchain networks and cryptocurrencies . His work examines the emergence of economic institutions in historical frontiers, constitutional design, and the governance of decentralized digital systems. Current projects include National Science Foundation -funded research on Colorado's development using land records and census data, and a Templeton World Charity Foundation initiative measuring cryptocurrency market dynamics. His publications address topics like blockchain governance , constitutional decentralization , and digital encryption privacy . Recent collaborations explore metaverse asset layers , penalty institutions in staked networks , and institutional complexity in economic systems.

Robin Chhabraمشاهده پروفایل

استادیار

• Robotics
• Soft Robotics
• Artificial General Intelligence
• +۵ مورد دیگر

Dr. Robin Chhabra is an Assistant Professor at the Department of Mechanical, Industrial, and Mechatronics Engineering, Toronto Metropolitan University. Specializing in robotics and mechatronics, his research focuses on soft robotics, embodied artificial intelligence, and space exploration technologies. Canada Research Chair in Cognitive Soft Space Robotics (2018-2024) Director of the ELIXIR Lab (Embodied Learning and Intelligence for eXploration and Innovative soft Robotics) His research integrates geometric mechanics , neuroscience , and artificial general intelligence to develop damage-tolerant, self-aware robotic systems for space applications. Key contributions include: First-of-its-kind meta-package for legged robot morphologies Singularity-free control algorithms for space manipulators Neuromorphic soft robotics prototypes (e.g., silicone inchworm robots) Recent publications emphasize multi-robot coordination , Lie group-based sensor fusion , and biologically inspired control systems for planetary exploration. Awards include: Canada Research Chair in Autonomous Space Robotics and Mechatronics Early Career Discovery Launch Supplement At the ELIXIR Lab, Chhabra mentors graduate students in developing robots capable of creative problem-solving during space disasters like orbital debris encounters or legged locomotion failures. His work spans robotics, control theory, and space systems engineering.