جست‌وجوی استاد و پژوهشگر

Renate Sachseمشاهده پروفایل

پژوهشگر

• Motion Design
• Active and Adaptive Structures
• Biomechanics
• +۶ مورد دیگر

Renate Sachse is a Researcher and Responsible Investigator at the Chair of Structural Analysis, Technical University of Munich (TUM), under Prof. Kai-Uwe Bletzinger. She holds a Dr.-Ing. from the University of Stuttgart and has held postdoctoral positions at Harvard University (Bertoldi Lab) and TU Munich's Institute for Computational Mechanics. Her research focuses on biomimetic adaptive structures, biomechanics, and smart materials. Education M.Sc. in Civil Engineering (University of Stuttgart, 2014) – Thesis: "Isogeometric Contact Analysis of Thin-Walled Structures" B.Sc. in Civil Engineering (University of Stuttgart, 2011) – Thesis: "Elementary School Pavilion Structural Analysis" Study Abroad: École Spéciale des Travaux Publics (ESTP, France, 2012) Research Interests Her work integrates principles from biology and mechanics to design adaptive structures, including motion design, soft robotics, and active metamaterials. Notable projects include studying snapping mechanisms in plants (e.g., Venus flytrap) and developing bio-inspired systems like Flectofold shading devices. She also explores isogeometric analysis and structural optimization for thin-walled and slender structures. Grants & Awards Bertha Benz Prize 2022 (Daimler and Benz Foundation) Klaus Tschira Boost Fund Fellowship (€80,000 interdisciplinary grant) 3rd Place AVK-Prize for Innovations (2017, Flectofold Shading System) GAMM Juniors Fellowship (2020–2022) Teaching & Grants She teaches advanced finite element methods and nonlinear mechanics at TUM and has supervised projects in computational mechanics. Her grants include CareerDesign@TUM funding and the Klaus Tschira Fellowship for high-risk, interdisciplinary research. Labs & Teams Associated with the Chair of Structural Analysis at TUM, collaborating on projects like livMatS (Living Materials Systems) and the Harvard SEAS Bertoldi Lab. Involved in software development (e.g., Carat++, Kiwi!3d) and third-party initiatives (CoDA, FlexWing).

• Statistical Network Analysis
• Machine Learning
• Data Privacy
• +۷ مورد دیگر

Tianxi Li is an Assistant Professor in the Department of Statistics at the University of Minnesota, Twin Cities, within the College of Science and Engineering. Their research integrates statistical methodology with applications in network science, data privacy, and biomedical data analysis. Their research interests lie at the intersection of statistics and network science, focusing on statistical modeling of complex networks , data privacy , network security , and biomedical applications such as neuroimaging and genomics. They develop adaptive and scalable methods for network estimation, community detection, and differential correlation analysis. The recent publications demonstrate a consistent focus on advancing statistical tools for network-structured data, with increasing applications in neuroscience and cancer genomics. The work spans theoretical development (e.g., network growth models) and practical applications (e.g., glioblastoma gene modules), reflecting a balance between methodology and real-world impact. Tianxi Li leads an active research program funded by the National Science Foundation, indicating recognition and support for their innovative work. Principal Investigator, Statistical tools for network security protection: from data privacy to threat detection , NSF (2024–2025) They advise graduate students in statistics and data science, though specific advisees are not listed. Their collaborative network includes researchers in biostatistics, computer science, and machine learning, as evidenced by co-authorships and interdisciplinary projects. Li's work contributes to the UN Sustainable Development Goals, particularly through advancements in data-driven solutions for secure and ethical data analysis.

• Nonlinear control theory
• Adaptive control
• Robust control
• +۵ مورد دیگر

Alessandro Astolfi is a Professor of Nonlinear Control Theory in the Department of Electrical and Electronic Engineering at Imperial College London, where he has been faculty since 1996. He also holds a professorship at the Department of Civil Engineering and Computer Science Engineering at the University of Rome Tor Vergata since 2005. From 2022 to 2025, he serves as College Consul for the Faculty of Engineering and Business School, and previously served as Head of the Control and Power Group from 2010 to 2022. His research expertise spans multiple areas of control theory: Nonlinear control theory Adaptive and robust control Discontinuous stabilization Model reduction Geometric control theory Observer design Astolfi's work has produced significant applications across diverse fields including aerospace systems (under-actuated satellites, autonomous aircraft), power systems (multi-machine systems), game theory (population dynamics, multi-agent systems), and industrial processes (model reduction applications). His research contributions have been recognized with numerous prestigious awards: 2003 Philip Leverhulme Prize for outstanding research achievements of young scholars 2007 IEEE Control Systems Society Antonio Ruberti Young Researcher Prize 2009 IEEE Fellow for contributions to nonlinear control theory 2009 Googol Best New Application Paper Award 2012 George S. Axelby Outstanding Paper Award 2012 IEEE CSS Distinguished Member Award 2015 Sir Harold Hartley Medal from the Institute of Measurement and Control (UK) Professor Astolfi has authored more than 120 journal papers, 30 book chapters, and over 240 conference papers. He co-authored the monograph 'Nonlinear and Adaptive Control with Applications' (Springer-Verlag). He currently serves as Chair of the IEEE CSS Conference Editorial Board and has participated in program committees of numerous international conferences. His research group at Imperial College London maintains strong connections with academic institutions worldwide including ETH Zurich, Rice University, and SUPELEC, with whom he has established visiting lecturer relationships spanning decades.

• Quantum Computing
• Quantum Sensing
• Atomic Physics
• +۳ مورد دیگر

Gavin Brennen is a Professor in Quantum Information Science (Core) at Macquarie University's School of Mathematical and Physical Sciences. He leads the Macquarie Centre for Quantum Engineering (MQCQE) and serves as a Chief Investigator at the Australian Research Council (ARC) Centre of Excellence for Engineered Quantum Systems (EQUS). He is also an Executive Board Member of the Sydney Quantum Academy (SQA). His research focuses on quantum computing, quantum sensing, and atomic physics, with a particular emphasis on quantum error correction and quantum LDPC codes. Key roles and affiliations include directorship of MQCQE, leadership in ARC EQUS, and SQA board membership. He has secured funding for multiple research projects, including Sydney Quantum Academy scholarships (e.g., Brennen/Gharat and Brennen/Vedl) and the Engineered Quantum Matter initiative. His work addresses quantum technologies' applications in sensing, computing, and communication. Research interests span quantum computing architectures, quantum error correction protocols, and atomic systems. Notable projects include high-rate quantum LDPC codes for neutral atom registers, cavity-based quantum gates, and quantum internet protocols. His contributions to quantum crypto-economics and blockchain security further highlight his interdisciplinary impact. He has advised on projects such as the Australian Dark Matter Detector for High-Mass Axions and collaborates internationally. Current efforts prioritize scalable quantum systems, fault-tolerant protocols, and quantum networking. His lab and teams drive innovation in quantum hardware and theoretical frameworks for emerging technologies.

Samuel Johnstonمشاهده پروفایل

مدرس

• Probability
• Stochastic Processes
• Free Probability
• +۷ مورد دیگر

Samuel Johnston is a Lecturer in Probability Theory at the Department of Mathematics, King's College London, affiliated with the Faculty of Natural, Mathematical & Engineering Sciences. He joined King's in 2022 after postdoctoral roles at the University of Bath, University of Graz, and University College Dublin. MMath, University of Oxford (2014) PhD in Probability, University of Bath (2017) Johnston's research spans probability theory, with a focus on stochastic processes involving branching, coalescence, and fragmentation. He actively explores free probability, random matrices, integrable combinatorics, and combinatorial approaches to the Jacobian conjecture. His work intersects with statistical physics and asymptotic geometric analysis. Recent publications highlight coalescent structures in heavy-tailed branching processes, integrable probability models, free probability via entropic transport, and convexity in high dimensions. Keywords include universality classes, Berry-Esseen bounds, and fragmentation-scaling limits. Samuel has not been mentioned to have received specific scientific awards or honors. He advises PhD students Rohan Shiatis (2023-) and Neil Mukerji (2024-). Collaborations span institutions in the UK, USA, Mexico, Austria, and Poland, with invited talks at global conferences including Xiangtan University, Imperial College London, and UCLA.

Bryan Trippمشاهده پروفایل

دانشیار

• Computational Neuroscience
• Deep Learning
• Robotics
• +۱ مورد دیگر

Bryan Tripp is an Associate Professor at the University of Waterloo, specializing in computational neuroscience, deep learning, robotics, and medical AI. He leads the BRAIN Lab, which focuses on developing neural system models that interact with the physical world through robots. His research integrates neurobiological models with advanced machine learning techniques to study visuomotor processes and robotic applications. Tripp teaches courses such as Computational Neuroscience (SYDE 552), Deep Learning (SYDE 577), and Biomedical Engineering Design Workshops (BME 461/462). His lab has achieved milestones including the OREO robotic head, the first spiking neural network model for complex action planning, and comprehensive datasets for robotic grasping. His recent work emphasizes Medical AI applications, with graduate positions available. The BRAIN Lab is affiliated with the Centre for Theoretical Neuroscience and Waterloo.AI, contributing to interdisciplinary AI research initiatives.

• Radiation Detectors
• Materials Physics
• Perovskite Materials
• +۳ مورد دیگر

Professor Paul Sellin is a Professor of Physics at the University of Surrey's School of Mathematics and Physics, with visiting roles at UCL and the University of Wollongong. He holds a PhD in Nuclear Physics from the University of Edinburgh (1992) and a BSc (Hons) in Physics from the University of Birmingham (1988). His research focuses on radiation detector materials, including perovskites, semiconductors, and scintillators, with applications in medical imaging, nuclear security, and high-energy physics. Key interests include perovskite semiconductor development, neutron/gamma detection, and radiation-hard materials. His group collaborates internationally on projects like the DTRA Interaction of Ionizing Radiation with Matter (IIRM) University Research Alliance. Publications highlight advancements in X-ray detection using perovskite nanocomposites, Cu-doped crystals, and organic semiconductors. His work emphasizes material synthesis, charge transport optimization, and device fabrication for low-dose imaging and high-sensitivity detection. Professor Sellin has supervised over 30 postgraduate students, many contributing to seminal studies on perovskite detectors, plastic scintillators, and semiconductor characterization. His contributions span academic networks like the Nuclear Threat Reduction Network (NTR-net) and the STFC NuSec program.

• Electric Power Systems
• Renewable Energy Integration
• Energy Policy and Economics
• +۳ مورد دیگر

Benjamin F. Hobbs serves as the Theodore M. and Kay W. Schad Professor of Environmental Management at Johns Hopkins University, holding a primary appointment in the Department of Environmental Health and Engineering and a joint appointment in the Department of Applied Mathematics and Statistics. He is co-director of the USEPA Yale-JHU SEARCH Center and director of the NSF-funded Electric Power Innovation for a Carbon-free Society (EPICS) Center, focusing on interdisciplinary research at the intersection of energy systems, environmental management, and public health. Hobbs' educational background includes a BS from South Dakota State University (1976), an MS in Resources Management and Policy from SUNY-Syracuse (1978), and a PhD in Environmental Systems Engineering from Cornell University (1983). Prior to joining Johns Hopkins in 1995, he worked at Brookhaven and Oak Ridge National Laboratories and served as a professor at Case Western Reserve University, with additional visiting appointments at institutions including Cambridge University. His research integrates systems analysis, economics, and optimization to address critical challenges in electric utility planning, renewable energy integration, and environmental resource management. Key focus areas include solar forecasting using AI, green infrastructure for urban water management, health impacts of energy transitions, and grid reliability under high renewable penetration. His work emphasizes practical applications through engineering-economic modeling with rich technological and environmental detail. Analysis of his recent publications reveals a strong trend toward addressing grid reliability in decarbonizing systems, with increasing emphasis on market design innovations, resource adequacy under uncertainty, and storage-transmission tradeoffs. His research consistently bridges theoretical optimization with real-world policy implementation, particularly evident in his leadership of the EPICS Center's 100% renewable grid initiatives. Lifetime Achievement Award by Energy Systems Integration Group (ESIG), 2024 Fellow of the Institute of Electrical and Electronics Engineers (IEEE) Fellow of the Institute for Operations Research and Management Science (INFORMS) Hobbs advises graduate students through Johns Hopkins' interdisciplinary programs, with alumni employed as energy consultants, policy analysts, and researchers. His current grants include leadership of the NSF Global Center EPICS and co-direction of the USEPA SEARCH Center, focusing on energy-air-climate-health interactions. He chairs the Market Surveillance Committee for the California Independent System Operator and serves on editorial boards for Energy Economics and other leading energy journals. He leads the Hobbs Energy & Environment Decisions Research Group, which collaborates with institutions including IBM, National Renewable Energy Laboratory, and University of Texas at Dallas. The group participates in the Global Power Systems Transformation Consortium and Columbia-JHU Future Power Markets Forum, conducting fieldwork initially in California and the central United States.

Robert C. Mertonمشاهده پروفایل

استاد

• Finance Theory
• Retirement Finance
• Derivatives Pricing
• +۵ مورد دیگر

Robert C. Merton is the School of Management Distinguished Professor of Finance at MIT Sloan School of Management and John and Natty McArthur University Professor Emeritus at Harvard University. He holds a PhD in Economics from MIT (1970), with prior roles including George Fisher Baker Professor at Harvard Business School and J.C. Penney Professor of Management at MIT Sloan. His work revolutionized finance through the Black-Scholes-Merton options pricing model, earning the 1997 Nobel Prize in Economics. Current research focuses on lifecycle investing, systemic risk measurement, and financial innovation. Education: BS in Engineering Mathematics (Columbia), MS in Applied Mathematics (Caltech), PhD in Economics (MIT). Affiliated with MIT’s Golub Center for Finance and Policy and Harvard initiatives. Recognized via awards from CME Group, World Federation of Exchanges, and Risk magazine. Key publications include Continuous-Time Finance and co-authored works on financial systems and innovation. Research emphasizes translating theory into practice, with recent articles addressing volatility forecasting, trust in lending, bankruptcy frameworks, and performance fee valuation. A prolific academic leader, he advises on policy and systemic risk while maintaining ties to MIT’s finance community through roles like Killian Award recipient (2021).

Jana Kainerstorferمشاهده پروفایل

استاد

• Biomedical Optics
• Neurophotonics
• Medical Devices
• +۳ مورد دیگر

Jana Kainerstorfer is a Professor of Biomedical Engineering at Carnegie Mellon University (CMU), with courtesy appointments in the Neuroscience Institute and Electrical & Computer Engineering. She serves as Associate Department Head for Faculty and Graduate Affairs within the College of Engineering. Her research focuses on developing non-invasive optical imaging methods for disease detection and treatment monitoring, particularly in diffuse optical imaging. Key areas include cerebral hemodynamic monitoring in traumatic brain injury and handheld devices for breast cancer imaging. Dr. Kainerstorfer holds senior membership in the Optical Society of America and has received prestigious awards such as the NIH Trailblazer Award and AHA Scientist Development Grant. She leads the Biophotonics Lab, which bridges engineering and clinical applications, emphasizing translational research. Education: PhD from University of Vienna/NIH (2010), Postdoc at Tufts University Research Interests Her work revolves around biomedical optics , neurophotonics , and medical device innovation . Current projects include: Non-invasive cerebral hemodynamic monitoring Transabdominal fetal pulse oximetry Optical imaging in extreme environments (e.g., freediving physiology) Her lab develops tools like wearable NIRS for marine mammals and self-calibrating pulse oximetry algorithms. Research spans clinical translation and physiological mechanism discovery , with emphasis on microvascular imaging. Awards & Recognition NIH Trailblazer Award (2020) AHA Scientist Development Grant SPIE Fellow (2022) George Tallman Ladd Award (CMU) Lab & Collaborations The Biophotonics Lab collaborates with neurosurgery, oncology, and marine biology teams. Projects address clinical needs in neurocritical care and fetal monitoring, leveraging optical technologies for real-time diagnostics. Ongoing work includes: Optical assessment of cerebral metabolic rates Non-invasive intracranial pressure estimation Multi-modal EEG-NIRS fusion for neural source localization

• Networked Control Systems
• Cyber-Physical Systems
• Cybersecurity
• +۴ مورد دیگر

Professor Daniel Quevedo is a leading academic in Electrical and Computer Engineering at The University of Sydney. Previously, he held positions at Queensland University of Technology and Paderborn University, Germany, where he founded the Chair in Automatic Control. He earned his PhD from the University of Newcastle (Australia) and MSc/Ing. degrees from Universidad Técnica Federico Santa María (Chile). His research focuses on networked control systems, cyber-physical systems, and cybersecurity, with contributions to state estimation, control of power converters, and human-in-the-loop systems. He has pioneered work integrating machine learning, behavioral economics, and advanced mathematics to address challenges in interconnected digital-physical environments. Quevedo serves as Associate Editor for IEEE Transactions on Control of Networked Systems and IEEE Control Systems. He chairs the Committee of Experts for Germany’s Excellence Strategy on Digital Methods and has held leadership roles in IEEE technical committees. Notable awards include the IEEE Axelby Outstanding Paper Award (2018) and multiple fellowships. Teaching includes advanced control systems courses like Reinforcement Learning and Optimal Control. He is a Fellow of the IEEE and has published over 200 peer-reviewed articles, with recent work emphasizing privacy-preserving state estimation, resilient control systems, and energy-efficient wireless control. His research labs explore topics such as human-machine collaboration, cybersecurity in Industry 5.0, and data-driven control strategies. Current projects include secure remote state estimation frameworks and adaptive control under adversarial conditions.

• Solid Mechanics
• Materials Science
• Fracture Mechanics
• +۳ مورد دیگر

Jonas Faleskog is a Professor in the Department of Materials and Structural Mechanics at KTH Royal Institute of Technology. His research focuses on mathematical modeling of material deformation and failure mechanisms, particularly in metallic and polymeric materials. Key areas include ductile and brittle fracture analysis, fracture mechanics, and computational modeling of material behavior under various stress conditions. He leads a research group collaborating internationally to develop models describing material failure at microscopic scales. Faleskog teaches courses such as Fracture Mechanics (SE2139) and Modeling in FEM (SE2860), emphasizing practical applications of theoretical models. His work spans experimental and numerical methods, addressing challenges in material heterogeneity, porosity effects, and environmental degradation. Notable contributions include advancements in weakest-link modeling for brittle failure, probabilistic fracture models, and strain gradient plasticity analysis. His research bridges material science, applied mechanics, and numerical methods to optimize material utilization in engineering systems like reactor tanks, aircraft, and vehicles. Key collaborations involve international teams exploring microstructural influences on fracture behavior. While no specific awards are listed, his extensive publication record reflects sustained contributions to mechanical and materials engineering.

Zhendong Suمشاهده پروفایل

استاد

• Programming Languages
• Compilers
• Software Engineering
• +۳ مورد دیگر

Zhendong Su is a full professor in the Department of Computer Science at ETH Zurich since August 2018. Previously, he held a full professorship at UC Davis from 2003 until June 2019. He earned his Ph.D. in Computer Science from UC Berkeley and dual Bachelor’s degrees in Computer Science and Mathematics from UT Austin in 1995. Affiliations: ETH Zurich: Full Professor (since 2018) UC Davis: Full Professor and Chancellor’s Fellow (2003–2019) IEEE Fellow, ACM Fellow, and Member of Academia Europaea His research focuses on programming languages, compilers, software engineering, computer security, and education technologies . Key contributions include compiler validation (e.g., Project Yin-Yang for SMT solvers and DBMS testing), testing tools like SQLancer, and educational innovations such as the Algot visual programming language. Recent work emphasizes secure AI (e.g., CipherSteal for TEE-shielded models) and compiler reliability (e.g., Artemis/Apollo for JIT validation). He has pioneered techniques like metamorphic testing and equivalence modulo inputs (EMI) for compiler validation, uncovering thousands of bugs in GCC/LLVM and SMT solvers. Awards: ICSE MIP Award (2022), ACM SIGSOFT Impact Paper (2018), NSF CAREER Award, and multiple industrial awards. His students have won IEEE TCSE Rising Star and SIGSOFT Impact Paper awards, securing roles at top universities and companies like Google and NVIDIA. Service: Steering committee member of ISSTA and ESEC/FSE, ACM Distinguished Speaker, and Associate Editor for ACM TOSEM. Program chaired ISSTA 2012 and co-chaired FSE 2016. Labs/Teams: Leads research groups on compiler validation, secure AI, and education technologies. Projects include Yin-Yang (SMT testing), SQLancer (DBMS fuzzing), and Algot (visual programming for education).

Heinz Koepplمشاهده پروفایل

استاد

• Self-Organizing Systems
• Systems Biology
• Control Theory
• +۹ مورد دیگر

Prof. Heinz Koeppl is a Professor in the Department of Electrical Engineering and Information Technology at TU Darmstadt. His research focuses on self-organizing systems, systems biology, and control theory, with applications in synthetic biology, robotics, and stochastic processes. He explores interdisciplinary topics such as genetic circuit design, UAV swarm dynamics, and machine learning-driven modeling of biochemical systems. Key research areas include the development of deep learning frameworks for kinetic modeling, Bayesian optimization for riboswitch design, and mean field control theory for sparse networks. His work bridges theoretical foundations with practical engineering solutions, addressing challenges in molecular communication, gene regulation, and robotic swarm coordination. Publications from 2023–2025 highlight advancements in bio-inspired algorithms, swarm intelligence, and computational biology. Notable contributions include studies on RNA-based circuits, active matter dynamics, and optimization strategies for large-scale systems. His research emphasizes interdisciplinary collaboration, leveraging tools from electrical engineering, mathematics, and life sciences. No scientific awards are explicitly listed in the provided text. Advising and grants details are not available. Prof. Koeppl’s lab focuses on integrating systems biology approaches with engineering principles to solve complex problems in healthcare, environmental sustainability, and technological innovation.

Khac Duc Doمشاهده پروفایل

استاد

• Control of Nonlinear Systems
• Autonomous Marine Vehicles
• Partial Differential Equation Systems
• +۳ مورد دیگر

Professor Khac Duc Do is a faculty member at Curtin University, holding a position in the School of Civil and Mechanical Engineering within the Faculty of Science and Engineering. He serves in the Office of the Provost and is based at Curtin Perth campus. His research focuses on advanced control systems, nonlinear dynamics, and robotics applications in marine, aerospace, and mechanical systems. He earned a PhD with distinction in 2003 and has held prestigious fellowships including ARC Postdoctoral Fellow (2004) and ARC Australian Research Fellow (2009). His teaching includes courses like Advanced Control and Mechatronics, Navigation and Marine Control Systems, and Advanced Control Engineering. Key research interests encompass control of nonlinear systems, stochastic systems, formation control of mobile agents, fluid-structure interaction, and boundary control of PDE-governed systems. His funded projects include wave-energy converter development (2023-2026), inerter-based damper research (2019-2021), and ocean vehicle control systems. Scientific awards include ARC grants totaling over AUD 2 million. Current opportunities include scholarships in control systems/fluid-structure interaction and a postdoc position in wave-energy conversion.