جستجوی استاد راهنمای دانشگاهی

Emily Soمشاهده پروفایل

استاد

• Disaster Risk Reduction
• Earthquake Engineering
• Urban Resilience
• +۵ مورد دیگر

Professor Emily So serves as Deputy Head of the School of Arts and Humanities at the University of Cambridge and directs the Cambridge University Centre for Risk in the Built Environment (CURBE). A chartered civil engineer with extensive field experience, she holds leadership roles in the Open-Oxford-Cambridge AHRC Doctoral Training Partnership and chairs the Faculty EDI Committee. Her research focuses on urban risk and resilience , particularly in earthquake-prone regions. Combining structural engineering with epidemiological approaches, she develops innovative casualty estimation models and engages directly with affected communities worldwide. Her work spans seismic safety, disaster epidemiology, and remote sensing applications for rapid damage assessment. Professor So's publication trends reveal strong emphasis on machine learning for disaster risk modeling , with recent work featuring graph neural networks, deep clustering for urban morphology, and LSTM-based population forecasting. Her research bridges engineering, social sciences, and data science to address resilience in developing nations. 2010 Shah Family Innovation Prize (Earthquake Engineering Research Institute) Fellow of the Institution of Civil Engineers (FICE) Scientific Advisory Group for Emergencies (SAGE) member advising UK government As Director of CURBE, she leads interdisciplinary collaborations with EEFIT, Global Earthquake Model (GEM), World Bank, and USGS. Her field investigations following major earthquakes inform practical solutions for vulnerable communities, notably contributing to the 2017 World Building of the Year design in China. Current work includes sabbatical research for 2025-2026 focused on decolonizing architectural approaches to disaster resilience. Professor So maintains active roles in professional organizations and international disaster response frameworks, with her CURBE team developing methodologies now implemented globally for seismic safety improvements.

Eva Ascarzaمشاهده پروفایل

استاد

• customer retention
• personalization and targeting
• marketing AI
• +۱۲ مورد دیگر

Eva Ascarza is a Professor of Business Administration in the Marketing Unit at Harvard Business School (HBS) . She co-founded the Customer Intelligence Lab at HBS's D 3 Institute, focusing on responsible and effective customer data utilization. Research Interests include: Customer retention and churn analysis Algorithmic bias in marketing AI Field experimentation (A/B testing) for targeting optimization Customer lifetime value (CLV) modeling Dynamic personalization strategies Scientific Awards and Recognitions: 2023 Weitz-Winer-O'Dell Award (winner) 2022 Paul E. Green Award (PNAS publication) 2020 Marketing Science Institute (MSI) Scholar 2019 Erin Anderson Award for Emerging Female Scholar 2018 Paul E. Green Award (JMR publication) 2014 Frank M. Bass Outstanding Dissertation Award Her articles demonstrate cutting-edge applications of statistical modeling , Bayesian methods , and fair AI frameworks in modern marketing challenges.

Zhonghai Luمشاهده پروفایل

استاد

• Computer Architecture
• Embedded Systems
• Network-on-Chip (NoC)
• +۷ مورد دیگر

Zhonghai Lu is a Professor of Electronic Systems Design (specializing in Dependable and Autonomous Systems) at KTH Royal Institute of Technology, part of the Department of Electrical Engineering in the School of Electrical Engineering and Computer Science (EECS). He serves as Program Director for KTH's Embedded Systems master's program and Director of Studies at the Division of Electronics and Embedded Systems. His research focuses on Network-on-Chip (NoC), computer architecture, embedded systems, and Prognostics and Health Management (PHM) of power electronics. He leads a research group exploring in-network processing and embedded intelligence, transforming passive networks into active computational frameworks. Lu holds a BSc from Beijing Normal University (1989), MSc and PhD from KTH (2002, 2007), and an MBA in Innovation and Growth from the University of Turku (2012). He has authored over 240 scientific papers, including journal articles and peer-reviewed conferences, with notable recognitions such as Best Paper Awards at NOCS’2015 and EU HiPEAC, and a Featured Paper in IEEE Transactions on Computers (2020). He serves as Associate Editor for ACM Transactions on Architecture and Code Optimization (TACO) and has chaired major conferences like HiPEAC’2017 and NOCS’2018. His research group’s recent work includes integrating AI into hardware acceleration, fault-tolerant neural networks, and RUL estimation for power electronics using recurrent neural networks. Lu has secured grants from the Swedish Research Council and Intel Corporation and developed courses like IL2230 (Hardware Architectures for Deep Learning) and IL2233 (Embedded Intelligence), pioneering embedded AI education at KTH. Education: BSc (Beijing Normal University), MSc/PhD (KTH), MBA (University of Turku) Awards: Best Paper Awards (NOCS, EU HiPEAC), Swedish Research Council Grants, Intel Research Gifts Labs/Teams: Research Group on In-Network Processing and Embedded Intelligence

Adrian Lewمشاهده پروفایل

استاد

• Computational Solid Mechanics
• Numerical Algorithms
• Hydraulic Fracturing Simulation
• +۳ مورد دیگر

Adrian Lew is a Professor of Mechanical Engineering at Stanford University, specializing in computational solid mechanics and numerical algorithms. His research focuses on hydraulic fracturing simulation, embedded boundary methods, and material model design. He holds a PhD in Mechanical Engineering from Caltech (2003). His work bridges advanced numerical techniques with real-world applications in geophysics, material science, and structural engineering. Education: PhD, Mechanical Engineering, California Institute of Technology, 2003 Research Interests: Lew's group develops algorithms for time-integration embedded boundary methods and hydraulic fracturing simulations. Key areas include curvilinear crack propagation, universal meshing for complex geometries, and high-fidelity fracture mechanics. His work on variational integrators and discontinuous Galerkin methods has advanced computational efficiency in nonlinear elasticity and thermodynamics. Publications: Recent articles emphasize mesh optimization (DVRlib), fracture path instabilities, and magma chamber dynamics. His methodologies address challenges in 3D crack modeling, fluid-structure interaction, and high-order approximations in domains with singularities. Advising & Grants: Lew's research is supported by projects in computational geophysics and material science. Though no advisees are listed, his work involves collaborative teams focused on algorithmic innovation and high-performance computing.

• Poisson Geometry
• Contact Geometry
• Jacobi Geometry
• +۴ مورد دیگر

Alfonso Giuseppe Tortorella is a Tenure Track Assistant Professor in the Department of Mathematics at the University of Salerno since October 31, 2022. Previously, he held research positions at CMUC (Center of Mathematics of the University of Coimbra), CMUP (Center of Mathematics of the University of Porto), and KU Leuven. He received his PhD in Mathematics from the University of Florence in 2017 under the supervision of Luca Vitagliano and Paolo de Bartolomeis. His educational background includes an MSc in Mathematics from the University of Salerno (2013) with honors, where he completed his thesis titled "Geometric methods of Hamiltonian mechanics" under Luca Vitagliano's guidance. Tortorella's research focuses on Poisson geometry in the broadest sense, with particular emphasis on deformation theory of coisotropic submanifolds in Jacobi manifolds, multiplicative structures on Lie groupoids, and VB-groupoids. His work explores the intersection of differential geometry, mathematical physics, and algebraic structures, developing sophisticated theoretical frameworks to understand geometric structures and their deformations. He has made significant contributions to understanding symplectic foliations, contact dual pairs, and the algebraic structures underlying Jacobi geometry. His most recent publications (2023-2025) demonstrate a consistent focus on deformation problems in Poisson and related geometries, with particular attention to coisotropic submanifolds in contact geometry, symplectic foliations, and the application of L∞ algebras to geometric deformation problems. His work shows increasing sophistication in handling higher structures and their applications to geometric problems. Abilitazione Scientifica Nazionale for Professore Associato in Geometria e Algebra (01/A2 - II Fascia) (May 24, 2021 - May 24, 2030) Qualification aux fonctions de Maître de conférences, section 25 - Mathématiques (December 31, 2018 - December 31, 2022) PhD internship at IM PAN awarded by WCMCS (December 2014) PhD scholarship from INdAM (October 2013) Scholarship from SMI (June 2013) Tortorella has advised multiple PhD, MSc, and BSc students, including Vanessa Oliveira (PhD, University of Porto), Antonio Maglio (PhD, University of Salerno), and Rodrigo de Oliveira Baptista (MSc, University of Porto). He has served on examination committees and as a reviewer for numerous prestigious mathematics journals. His collaborative work extends across international boundaries, with research stays at institutions in Italy, Portugal, Belgium, Poland, France, Germany, and Brazil. He is an active organizer of conferences and workshops, particularly in the field of Poisson geometry, serving on the organizing committees for events like Poisson 2024 and the INdAM Intensive Period on Poisson Geometry & Mathematical Physics.

Claudia R. Binderمشاهده پروفایل

استاد

• Urban Sustainability
• Transition Research
• Urban Metabolism
• +۵ مورد دیگر

Claudia R. Binder is Full Professor at EPFL's School of Architecture, Civil and Environmental Engineering, leading the Laboratory for Human-Environment Relations in Urban Systems (HERUS) since 2016. Previously, she held professorships at the University of Munich (2011-2016), University of Graz (2009-2011), and University of Zurich (2006-2009). She served as Dean of EPFL's ENAC School from 2020-2023 and holds advisory roles with Swiss federal institutions including the Mercator Foundation since 2024. Her academic foundation includes a Biochemistry degree and PhD in Environmental Sciences from ETH Zurich, followed by postdoctoral research at the University of Maryland. This interdisciplinary background underpins her research approach spanning natural and social sciences. Professor Binder's work centers on urban sustainability transitions, examining urban metabolism dynamics through systems science frameworks. She investigates energy-food-transport interdependencies in cities using transdisciplinary methods that integrate material flow analysis, spatial modeling, and socio-technical assessments. Her research particularly emphasizes regulatory mechanisms and transformation drivers in human-environment systems, with case studies across Swiss and global urban contexts. Recent publications reveal evolving focus from foundational urban metabolism studies toward actionable transition strategies. Her 2024-2025 work increasingly addresses social tipping dynamics, circular decarbonization, and spatially explicit waste management, demonstrating methodological innovation through geo-referenced material flow analysis and participatory backcasting frameworks. Key thematic clusters include energy innovation diffusion, plastic waste governance, and demand-side flexibility in residential systems. She actively mentors 7 current PhD candidates while supervising 11 graduates since 2018, with research spanning urban metabolism modeling, sustainability assessment, and transition governance. Her leadership extends to Swiss National Science Foundation committees and National Research Program 71 on energy consumption management. At EPFL, she directs the HERUS laboratory which develops the Sustainability Solution Space methodology for urban assessment. The lab operates at the intersection of data science, environmental engineering, and social theory, maintaining strong field connections in Switzerland, Indonesia, and Germany for empirical validation of transition models.

• Medical Informatics
• Artificial Intelligence in Healthcare
• Healthcare Data Integration
• +۷ مورد دیگر

Prof. Martin Boeker is a Professor of Medical Informatics at the Technical University of Munich (TUM), affiliated with the TUM School of Medicine and Health. His work focuses on advancing healthcare through AI-driven solutions, interoperability frameworks, and precision medicine initiatives. Key projects include the German Medical Text Corpus (GeMTeX) and the MIRACUM DIFUTURE Alignment Hub. Expertise: Medical Informatics, AI in Healthcare, Federated Learning, Health Data Integration Key Contributions: FHIR-based systems, clinical decision support, patient-centered outcomes research Leadership: Director of the Institute for AI and Informatics in Medicine at TUM Hospital Right of the Isar Research emphasizes bridging clinical practice and data science through projects like modular health crawlers, automated guideline adherence monitoring, and cross-institutional medical NLP solutions. His work spans oncology informatics, rare disease management, and pandemic response data ecosystems. Recent articles highlight innovations in digital twins for precision oncology, federated analysis in oncology, and German-language medical NLP challenges. He collaborates internationally on EHR standardization and healthcare interoperability, contributing to the Medical Informatics Initiative (MII) and pandemic evidence ecosystems. Grants and collaborations involve the German Federal Ministry of Education and Research, European initiatives, and industry partnerships. Educational efforts focus on training future medical informatics professionals through MII competency programs.

• Defects in Semiconductors
• Porous AlGaN Materials
• Cathodoluminescence Spectroscopy
• +۴ مورد دیگر

Gunnar Kusch is a Senior Research Associate at the Department of Materials Science & Metallurgy, University of Cambridge. His research focuses on defects in semiconductors, porous AlGaN materials, and advanced characterization techniques like cathodoluminescence (CL) and atom probe tomography (APT). He holds a PhD from the University of Strathclyde and leads projects on UV-B LED optimization, nanoscale defect behavior analysis, and semiconductor device design. His work bridges materials synthesis, characterization, and device performance, with applications in energy-efficient lighting and solar cell technology. Key research areas include: Defect engineering in III-nitride semiconductors Porous AlGaN templates for high-efficiency UV emitters Correlative microscopy techniques (CL, EBSD, APT) Composition-structure-property relationships in photovoltaic materials Notable contributions include developing CL-based methods for nanoscale defect analysis and demonstrating improved Cu(In,Ga)S₂ solar cell efficiencies through compositional engineering. His laboratory focuses on translating microscopic insights into macroscopic device improvements.

Duminda Wijesekeraمشاهده پروفایل

استاد

• Cybersecurity
• Cyber-Physical Systems
• Digital Forensics
• +۵ مورد دیگر

Duminda Wijesekera serves as Professor in the Department of Cyber Security Engineering and Department of Computer Science at George Mason University, where he was inaugural chairman of the Cyber Security Engineering Department until December 2022. He concurrently held the position of visiting research scientist at the National Institute of Standards and Technology (NIST) from 2007-2022 and maintains status as a fellow at the Potomac Institute of Policy Studies. He leads the Mason Innovation Laboratory at Mason Square, driving translational research in cyber-physical security. His educational foundation includes: PhD in Computer Science, University of Minnesota (1997) PhD in Mathematical Logic, Cornell University (1990) BSc in Mathematics, University of Colombo Professor Wijesekera's research centers on cyber-physical system security , with pioneering work in Intelligent Transportation Systems spanning trains, aircraft, and connected vehicles. His digital forensics innovations establish frameworks for evidence-based scenario reconstruction and error management, while his formal methods research provides mathematical guarantees for safety-critical systems. Current projects address Next G-based edge services, digital twin vulnerability detection, and healthcare security architectures, consistently bridging theoretical rigor with real-world infrastructure protection. Analysis of his 2022-2025 publications reveals intense focus on autonomous vehicle security (38% of recent output), including traffic signal control optimization, ramming attack countermeasures, and CARLA-based scenario validation. Digital forensics using AI (20%) and secure manufacturing/edge computing (27%) constitute other major thrusts, demonstrating how formal verification and machine learning converge to solve complex cyber-physical security challenges across transportation, energy, and healthcare domains. His scientific recognition includes: CCI Impact Award (2022) for groundbreaking cyber-physical security contributions Fellowship at the Potomac Institute of Policy Studies for cybersecurity policy leadership Professor Wijesekera has secured substantial research funding through: NIST grants for health record security frameworks (2014-2015) US Department of Transportation projects on wireless frequency mapping for high-speed rail (2013-2014) Cyber Security Research Alliance funding for trust architectures in cyber-physical systems (2014) Commonwealth Cyber Initiative awards for autonomous vehicle security and energy-efficient manufacturing His industry partnerships with Honeywell and NIST ensure practical impact of theoretical research. The Mason Innovation Laboratory under his direction serves as an interdisciplinary hub for cyber-physical security, integrating researchers from computer science, electrical engineering, and policy studies to develop deployable solutions for transportation networks, power grids, and critical infrastructure protection.

Petteri Nurmiمشاهده پروفایل

استاد

• Environmental Monitoring
• Internet of Things (IoT)
• Artificial Intelligence (AI)
• +۷ مورد دیگر

Petteri Nurmi is a Professor of Computer Science at the University of Helsinki, affiliated with the Department of Computer Science and the Helsinki Institute of Sustainability Science (HELSUS). His research focuses on IoT systems, environmental monitoring, AI-driven solutions, and sustainable computing. He leads projects such as the NordForsk-funded initiative (2024-2028) and the Team Finland Knowledge programme (2024-2026), emphasizing large-scale IoT deployments and quantum computing integration. Key research interests include drone-based air quality monitoring, low-cost sensor networks, and AI applications in environmental science. Nurmi has published extensively in top venues like IEEE IoT Journal and ACM workshops. His work bridges technical innovation with societal challenges, such as urban pollution reduction and sustainable resource management. He supervises doctoral students in the Computer Science program and collaborates internationally on projects like underwater plastic detection (SEAGULL) and smart city infrastructure. Nurmi’s contributions to edge computing and pervasive sensing have been recognized through grants totaling over €2M. His lab develops tools for data-intensive systems, including thermal imaging for energy efficiency analysis and AI-driven sensor fusion frameworks.

Benjamin Busamمشاهده پروفایل

پژوهشگر

• 3D Computer Vision
• Multi-Modal Sensor Fusion
• Collaborative Robotics
• +۶ مورد دیگر

Dr. Benjamin Busam is a Senior Research Scientist at the Technical University of Munich , affiliated with the Chair for Computer Science Applications in Medicine under Prof. Nassir Navab. Starting September 2025, he will hold the Professorship for Photogrammetry and Remote Sensing at TUM. His career includes leadership roles at FRAMOS Imaging Systems and Huawei Research in London. Education: Mathematics (TUM), Mathematics and Physics (ParisTech, University of Melbourne), PhD in Mathematics (TUM, 2014) His research focuses on 3D computer vision , multi-modal sensor fusion , and their applications in collaborative robotics and augmented reality . He specializes in projective geometry , 6D pose estimation , and neural radiance fields , with a particular emphasis on photometrically challenging environments. Recent publications highlight advancements in 3D scene understanding , neural rendering , and medical imaging , often leveraging machine learning and vision-language models . His work has been recognized through awards like the EMVA Young Professional Award (2015) and Innovation Pioneer of the Year (2019) , along with multiple Outstanding Reviewer distinctions at leading conferences. Dr. Busam has supervised numerous PhD and MSc students on topics including 6D pose estimation , medical augmented reality , and robotic ultrasound , collaborating with institutions like MIT , École Polytechnique , and University of Padova .

Maximilian Hilgerمشاهده پروفایل

پژوهشگر

• Radar Perception
• SLAM (Simultaneous Localization and Mapping)
• Autonomous Systems
• +۳ مورد دیگر

Maximilian Hilger is a doctoral researcher at the Chair of Perception for Intelligent Systems, part of the Munich Institute of Robotics and Machine Intelligence at Technische Universität München (TUM). He joined the chair in 2024 and specializes in radar perception for autonomous systems. M.Sc. in Automation Engineering (RWTH Aachen, 2023) Doctoral studies previously at AASS, Örebro University, Sweden His research focuses on radar-based localization, mapping, and introspection in challenging environments, with publications addressing 4D imaging radar SLAM, loop closure techniques, and sensor fusion methodologies. Recent work includes evaluating radar odometry algorithms and developing robust mapping systems using intensity-augmented normal distributions transform. Key research themes: Radar perception for autonomous systems SLAM robustness and introspection Occlusion-resistant localization Sensor fusion in dynamic environments He collaborates with team members including Prof. Achim Lilienthal, Valeria Salazar, and Thomas Wiedemann at TUM's Siemens Technology Center campus in Garching, Germany.

• Climate Change Attribution
• Extreme Weather Events
• Agricultural Impacts of Climate Change
• +۳ مورد دیگر

Mariam Zachariah serves as a Research Fellow at the Centre for Environmental Policy within the Faculty of Natural Sciences at Imperial College London. She is a core contributor to World Weather Attribution (WWA), an international scientific collaboration conducting rapid climate change attribution analyses for extreme weather events globally. Her work bridges climate science, vulnerability assessment, and policy-relevant research. Her educational foundation includes a PhD from the Indian Institute of Technology Bombay (IITB), where she investigated climate impacts on Indian agriculture. This research focused on drought and extreme temperature effects on crop yields in major agrarian regions, recognizing agriculture's critical role in India's climate-vulnerable economy. Zachariah's research centers on near-real-time attribution of extreme events to quantify human-induced climate change influences. Her expertise spans climate modeling, statistical analysis of extreme weather, and integrating vulnerability frameworks to assess compound impacts on communities. She examines how climate change interacts with socioeconomic factors to exacerbate disasters, particularly in agricultural systems and flood-prone regions worldwide. Analysis of her recent publications reveals a dominant focus on rapid attribution of droughts, floods, and heatwaves across diverse global contexts - from the Horn of Africa to Central Europe and South America. These studies consistently demonstrate climate change as a significant amplifier of event severity, while emphasizing how pre-existing vulnerabilities determine actual impacts. Her work increasingly addresses compound hazards and the intersection of climate change with infrastructure failures and land management. As a key member of the World Weather Attribution initiative, Zachariah collaborates with climate scientists, social scientists, and vulnerability experts in a unique operational framework that delivers scientific assessments within days of extreme events. This work directly informs policymakers, media, and affected communities about climate change's role in contemporary disasters.

• Battery simulation
• Cyber physical system
• Design simulation
• +۱۲ مورد دیگر

Sara Vinco is an Associate Professor at the Department of Control and Computer Engineering (DAUIN), Politecnico di Torino, Italy. She specializes in battery simulation, digital twins, and energy-efficient design automation for heterogeneous embedded systems, aligning with Industrial and Information Engineering (Area 0009) and ERC sectors including Computer Architecture and Machine Learning . Her research focuses on advancing cyber-physical systems through simulation frameworks like SystemC-AMS, enabling holistic modeling of analog, digital, and thermal domains. Key projects include data-driven digital twins for EV batteries and low-area digital circuits in industrial/medical applications, supported by commercial contracts such as C-based virtual prototyping. Her recent publications (2022-2023) emphasize machine learning for battery SOH/SOC estimation , energy monitoring in production lines , and multi-domain fault modeling . These works span journals like IEEE Transactions and conferences including DATE and ISLPED. Awarded the FFABR 2017 grant and IEEE FDL Best Paper Award 2011 , she also chairs editorial boards for IEEE Transactions on CAD and DATE Conference. She supervises PhD students Giovanni Pollo (Digital Circuits) and Khaled Alamin (EV Battery Twins), reflecting her leadership in smart systems design.

• Earthquake Engineering
• Structural Dynamics
• Seismic Risk Assessment
• +۳ مورد دیگر

Prof. Dr. Hakkı Polat Gülkan is a Professor at Başkent University's Civil Engineering Department. With a PhD (1971) and Master's (1968) from the University of Illinois in Civil Engineering and a Bachelor's (1966) from METU, his career spans over five decades in earthquake engineering, structural dynamics, and disaster management. PhD: University of Illinois, Civil Engineering (1971) Master's: University of Illinois, Civil Engineering (1968) Bachelor's: Middle East Technical University, Civil Engineering (1966) His research focuses on seismic risk assessment, structural behavior under extreme loads, and disaster mitigation strategies. Key contributions include earthquake simulator development, ground motion analysis, and retrofitting techniques for masonry and reinforced concrete structures. He has published extensively on deformation limits, response spectra, and historical building preservation. Recent work includes 15+ articles from 2024-2012 analyzing Istanbul's seismic hazards, Marmara region dynamics, and post-earthquake structural integrity. Conference papers address Turkey's endemic building vulnerabilities and deformation thresholds for seismic isolation systems. Scientific Achievements: Elected to U.S. National Academy of Engineering (2023) As an active journal reviewer for 13+ publications (2023-2024), he contributes to advancing earthquake engineering discourse. His teaching portfolio includes advanced structural analysis, concrete mechanics, and seismic design courses.