جست‌وجوی استاد و پژوهشگر

Gianluca Cerulloمشاهده پروفایل

پژوهشگر

• conservation science
• biodiversity
• climate change
• +۶ مورد دیگر

Gianluca Cerullo is a conservation scientist currently serving as a Visiting Researcher at the Department of Zoology, University of Cambridge, with additional affiliation to the Forest Animal Ecology Lab at Oregon State University. His research focuses on navigating trade-offs between biodiversity, climate, and economic objectives while meeting global wood demands through landscape-level modeling and field surveys. His primary research interests include conservation science, biodiversity preservation, climate change mitigation, forest restoration, and tropical ecosystem management. Cerullo combines detailed field surveys with ecological theory to develop approaches for reducing species extinction risk while addressing human needs for natural resources. His work spans multiple continents, with research conducted in Oregon, Borneo, Madagascar, the Colombian Andes, and Nigeria. Cerullo's scholarly output reveals a strong focus on practical conservation outcomes, with recent publications analyzing the complex relationship between tree plantations and ecosystem restoration, examining conservation strategies for endangered species like spider monkeys and pangolins, and exploring effective approaches to forest regeneration. His work consistently emphasizes the importance of evidence-based conservation decision-making and the need to move beyond simplistic solutions to complex ecological challenges. Among his notable contributions are analyses of how monoculture plantations can sometimes support restoration efforts when properly managed, investigations into the conservation value of naturally regenerating forests, and examinations of the challenges facing endangered species in fragmented habitats. His research often bridges academic theory with practical conservation applications. Cerullo is an active science communicator, contributing regularly to the international environmental journalism outlet Mongabay and maintaining his own blog focused on rainforest conservation. His writing emphasizes the importance of individual action in conservation, the need for thoughtful cause selection, and the value of evidence-based decision making in environmental protection efforts. His fieldwork experiences span multiple continents, where he has conducted research in diverse tropical ecosystems, from studying dung beetles in the Colombian Andes to tracking elephant populations in Nigeria's Yankari National Park. These experiences inform his practical approach to conservation science and his understanding of on-the-ground challenges facing biodiversity protection efforts worldwide.

Eva Naumannمشاهده پروفایل

استادیار

• Neurobiology
• Neuroscience
• Neural Circuits
• +۶ مورد دیگر

Eva Naumann is an Assistant Professor of Neurobiology, Psychology and Neuroscience, Biomedical Engineering, and Cell Biology at Duke University's School of Medicine. She investigates neural circuits across the zebrafish brain, focusing on how individuality emerges in brain architecture and behavior. Harvard University/Ludwig Maximillian University, Ph.D., Neurobiology University of Konstanz, MSc, Biology Her research spans whole-brain imaging, gut-brain axis communication, motivational states, and computational modeling. Using translucent zebrafish, she combines imaging, behavioral analysis, and machine learning to map brain-scale circuit models. Recent publications highlight work on visuomotor transformations, gigapixel microscopy, and neural decoding tools. Key trends include cross-scale imaging, behavioral idiosyncrasy, and brain-body interactions. 2020 Sloan Research Fellowship She advises graduate students and postdocs in her lab, which receives NIH and foundation funding for projects like brain-scale neural circuit development and adaptive imaging technologies.

Angelo Cenedeseمشاهده پروفایل

دانشیار

• Robotics
• Control Systems
• Multi-Agent Systems
• +۵ مورد دیگر

Angelo Cenedese is an Associate Professor at the Department of Information Engineering (DEI), University of Padova, and leads the SPARCS Lab (Flying Arena and Mobile Robotics Laboratory). He co-leads the NAVLAB (Autonomous Navigation Laboratory) and holds senior roles in IEEE societies, including the Control Systems Society (CSS) and Robotics and Automation Society (RAS). His academic activities span teaching, editorial work as Associate Editor for IEEE Transactions on Industrial Informatics, and leadership in research projects focusing on robotics, control systems, and multi-agent networks. His research interests include robotics , control systems , multi-agent coordination , computer vision , autonomous navigation , and industrial automation . His recent publications emphasize machine learning for industrial vision systems, adaptive control in aerospace robotics, distributed state estimation , and secure UAV navigation under GNSS spoofing. Key trends involve edge computing , collaborative robotics , and AI-driven optimization . Scientific Awards: Award for 'Most Innovative Application' at Quality Control by Artificial Vision Conference (QCAV 2019) His projects include AI in Manufacturing (AIMS5.0), Sustainable Mobility (PNRR-MOST), and 6G Networking (PREDICT-6G), often in collaboration with Italian and international institutions. Teaching roles cover Robotics and Control , Networked Control Systems , and Computer Vision courses at both undergraduate and graduate levels.

KHOO Boo Cheongمشاهده پروفایل

استاد

• Fluid Mechanics
• Computational Fluid Dynamics
• Numerical Methods
• +۷ مورد دیگر

Professor KHOO Boo Cheong is a faculty member in the Department of Mechanical Engineering at the National University of Singapore (NUS), affiliated with the College of Design and Engineering. He holds a BA (Hons.) from the University of Cambridge (1980), an MEng from NUS (1984), and a PhD from MIT (1989). His research focuses on Computational Fluid Dynamics (CFD) , Numerical Methods , and Fluid Mechanics , with applications to aerodynamics, turbulence, and fluid-structure interaction. Recent work emphasizes machine learning integration in CFD, bio-inspired UAV design, and icing mechanics for aerospace systems. Key research trends include advancing high-fidelity simulations for complex flows (e.g., turbulence modeling, cavitation suppression), optimizing fluid-structure systems (e.g., lightweight shells, train aerodynamics), and developing novel experimental techniques (e.g., light field PIV, wind spectra analysis). His contributions bridge theoretical CFD innovations with practical engineering challenges in transportation, renewable energy, and robotics. Professor Khoo collaborates on projects involving pressure gain combustion systems , ventilated supercavitating models , and quantum algorithms for fluid dynamics . His lab’s work often combines advanced numerical modeling with experimental validation, addressing real-world issues like wind effects on trains, ice accretion on airfoils, and autonomous navigation systems.

• Robotics
• Autonomous Vehicles
• Machine Learning
• +۴ مورد دیگر

Dr Charika De Alvis is a Research Fellow at the School of Computer Science , University of Sydney. Her work focuses on robotics and autonomous systems, integrating advanced machine learning and computer vision techniques. Research Interests : Robotics Autonomous Vehicles Machine Learning Computer Vision Sensor Fusion Data Science Her recent publications emphasize robust autonomy , scene segmentation using Lidar-constrained CRFs , sensor fusion for moving platforms, and uncertainty estimation in tracking systems. These studies highlight trends in autonomous vehicle perception , Lidar-camera integration , and probabilistic modeling . Grants : 2022: National Intelligence Postdoctoral Grant for "Extreme Class Imbalance Handling with Sample Characterized Margin Loss"

• Wireless Sensor Networks
• Mobile Computing
• Crowdsourcing Systems
• +۵ مورد دیگر

Qi Han is a Professor in the Department of Computer Science at Colorado School of Mines, with a distinguished research career spanning over two decades in wireless sensor networks, mobile computing, and distributed systems. Their work bridges theoretical foundations with practical applications in augmented reality, robotics, and smart city infrastructure. Research interests focus on three interconnected domains: 1) Networked robotic systems including UAV-UGV collaboration and swarm intelligence, 2) Mobile augmented reality with emphasis on real-time performance and spatial accuracy, and 3) Crowdsourced data systems for smart city applications. Recent work demonstrates sophisticated integration of these areas, particularly in energy-aware path planning, communication-resilient robot teams, and quality-aware AR systems. Analysis of recent publications (2022-2025) reveals a strategic shift toward integrating large language models with physical systems, developing more robust communication frameworks for drone networks, and creating comprehensive evaluation metrics for AR applications. The research trajectory shows increasingly complex system integration, moving from single-device solutions to coordinated multi-agent systems with sophisticated networking requirements. Principal Investigator for multiple NSF-funded projects on networked robotic systems Recipient of best paper awards at MobiQuitous and DCOSS conferences Senior member of IEEE Computer Society Organizing committee member for ACM MobiSys and IEEE PerCom conferences As a research advisor, Qi Han has mentored numerous graduate students who have gone on to publish in top-tier venues and secure positions in both academia and industry. Their lab maintains strong industry partnerships with companies developing AR/VR technologies and drone systems. Current research directions include energy-aware coordination of heterogeneous robot teams, privacy-preserving crowdsensing frameworks, and adaptive AR systems for industrial applications.

• Machine Learning
• Computer Vision
• Medical Imaging
• +۵ مورد دیگر

Wenwen Zhang is a Professor at the Department of Electronic Engineering, College of Information Science and Electronic Engineering, Zhejiang University. With an extensive publication record spanning from 2016 to 2025, Dr. Zhang has established herself as a prominent researcher in multiple interdisciplinary fields at the intersection of computer vision, machine learning, and sensor systems. Her work demonstrates significant contributions to medical imaging, sensor array systems, wireless communications, and AI-assisted applications. Dr. Zhang's research interests encompass a wide range of topics including medical image analysis, sensor array systems, wireless communications, and AI-assisted applications. Her work demonstrates particular expertise in developing innovative deep learning architectures for medical imaging tasks such as cardiac segmentation and nuclei detection, as well as creating sophisticated models for gas sensing and wireless communication systems. She has made significant contributions to the fields of one-shot object detection, medical image segmentation, and sensor fusion techniques, with her research often bridging theoretical advancements with practical applications in healthcare and engineering. Analysis of Dr. Zhang's recent publications reveals a strong focus on cutting-edge deep learning approaches applied to medical imaging and sensor systems. Her work shows increasing sophistication in model architectures, moving from traditional CNNs to more complex transformer-based and hybrid models. There's a clear trajectory toward more explainable and clinically relevant AI systems, particularly in medical applications. Her research also demonstrates growing interest in multimodal approaches, combining different types of data and sensors to improve system performance. Dr. Zhang maintains active collaborations with researchers at Zhejiang University, particularly with Yuanjin Zheng and Zhiping Lin in the field of electronic engineering and sensor systems. She also collaborates extensively with Fei-Yue Wang from the University of Chinese Academy of Sciences, evidenced by multiple publications on parallel vision frameworks. Her international collaborations include work with researchers from institutions in Canada on intelligent knee sleeves and other biomedical applications. Her publication record shows consistent productivity with 12 publications in 2025 (as of this writing), 25 in 2024, and 26 in 2023, indicating an active and growing research program across multiple high-impact journals and conferences.

• Computer Vision
• Human Mobility Modeling
• Infrastructure Monitoring
• +۴ مورد دیگر

Takehiro Kashiyama is an Assistant Professor at the Institute of Industrial Science, University of Tokyo, specializing in civil engineering with a focus on infrastructure monitoring and urban mobility systems. His work bridges computer vision, machine learning, and civil infrastructure applications. Dr. Kashiyama's research interests center around Computer Vision applications for infrastructure monitoring , Human Mobility Modeling , and Disaster Response Systems . His work develops innovative approaches for road damage detection using deep learning techniques, traffic flow reconstruction from moving camera systems, and human mobility modeling for urban planning and disaster scenarios. His research integrates cutting-edge computer vision techniques with practical civil engineering applications. His publication record shows a consistent focus on applying AI techniques to civil infrastructure problems, with a particular emphasis on road damage detection systems and human mobility modeling. His work often involves collaboration with Yoshihide Sekimoto and other researchers at the University of Tokyo. Dr. Kashiyama has made significant contributions to road damage detection challenges, human mobility modeling using agent-based approaches, and traffic flow analysis systems. His work has been published in journals such as Computer-Aided Civil and Infrastructure Engineering, Sensors, and IEEE conferences including Big Data and ITSC.

Robert Willeمشاهده پروفایل

استاد

• Design Automation
• Quantum Computing
• Computer Science
• +۷ مورد دیگر

Prof. Dr. Robert Wille is a Full Professor at the Technical University of Munich (TUM) in the School of Computation, Information and Technology and Chief Scientific Officer at the Software Competence Center Hagenberg GmbH . He leads the Chair for Design Automation , focusing on automatic methods for complex system design in conventional and future technologies. Studied Computer Science (Diploma) at the University of Bremen (2002-2006) Doctorate (summa cum laude) from the University of Bremen (2009) His research spans quantum computing , microfluidic biochips , field-coupled nanotechnologies , and reversible circuits , with applications in machine learning , artificial intelligence , and cyber-physical systems . Recent work includes quantum circuit verification, radar-camera fusion, and silicon dangling bond logic optimization. Robert Wille has received prestigious awards such as the ERC Consolidator Grant , Google Research Award , and Distinguished Professor appointment . He serves as Associate Editor for journals like IEEE TCAD and Springer LNCS, and has chaired conferences including DATE and ICCAD.

Davide Borelliمشاهده پروفایل

دانشیار

• Building Physics
• Acoustics
• Thermodynamics
• +۲ مورد دیگر

Davide Borelli is an Associate Professor in the Department of Mechanical, Energy, Management and Transport Engineering (DIME) at the University of Genoa, specializing in Environmental Technical Physics (SSD IIND-07/B). He serves on the Board of Directors of the Italian Center of Excellence for Logistics, Transport, and Infrastructure (CIELI), contributing to national infrastructure initiatives. His research spans Building Physics and Acoustics, with core expertise in ship propeller noise characterization, sound absorption materials, and building energy efficiency. Methodologically, he combines experimental acoustics with computational techniques including Lattice Boltzmann simulations for fluid-structure interactions. Recent publications (2024-2025) reveal a dual focus: marine acoustics (ship noise measurement in ports, cavitation tunnel analysis) and sustainable building systems (insulation optimization, perforated plate acoustics). This work directly addresses noise pollution control and energy conservation in infrastructure. Dr. Borelli teaches thermodynamics, building physics, and plant design across Industrial Technologies and Building Engineering programs. His active research collaborations through CIELI and co-authored publications indicate ongoing institutional support, though specific grants and student supervision details remain unpublicized.

Arif Tanju Erdemمشاهده پروفایل

استاد

• Digital Video Processing
• Computer Graphics
• Computer Vision
• +۲ مورد دیگر

Arif Tanju Erdem serves as Professor of Computer Science and Vice Rector for Academic Affairs at Ozyegin University, Istanbul. He joined the university in 2009 after 18 years at Eastman Kodak Research Laboratories and as CTO of Momentum, A.S., a digital media technologies company he co-founded. His leadership roles include Dean of the School of Engineering (2014-2018) and Head of Computer Science Department (2012-2014). His academic credentials feature: Ph.D. in Electrical Engineering, University of Rochester (1990) M.S. in Electrical Engineering, University of Rochester (1988) Dual B.S. degrees in Electrical & Electronics Engineering and Physics, Boğaziçi University (1986) Erdem's research centers on digital video processing and computer graphics with expanding applications in computer vision and machine learning. His foundational work in bispectrum analysis and video compression evolved into modern applications including face recognition systems, augmented reality tracking, and sensor fusion. Current investigations focus on overcoming data labeling challenges in biometric systems and developing robust motion tracking solutions for immersive technologies. Analysis of his recent publications (2012-2023) reveals three dominant research trajectories: (1) Advancements in face recognition using curriculum and semi-supervised learning techniques, (2) Precision sensor fusion for augmented reality through IMU-camera calibration and occlusion handling, and (3) Educational technology innovations through gamified learning systems. His work consistently bridges theoretical signal processing with practical implementations in medical monitoring, entertainment, and education. Professional service highlights include ISO-MPEG committee membership (1991-1998), IEEE Signal Processing Society leadership roles across Rochester, Turkey, and Region 8 chapters, and editorial contributions to Signal Processing: Image Communication. He has organized major conferences including the 3DTV Conference (2011) and IEEE Turkey Signal Processing Conference (2012).

• Advanced optical systems
• Light-sheet microscopy
• Mechanosensitive microscopy
• +۹ مورد دیگر

Dr Florian Ströhl is a Senior Researcher (equivalent to Research Professor) at the Department of Physics and Technology , UiT The Arctic University of Norway in Tromsø. He leads a highly interdisciplinary program that bridges optics, biology and medicine, acting as Principal Investigator on the ERC Starting Grant LiBriNa , the RCN FRIPRO SOLIS project, and the EU MSCA MitoQuant consortium. Education: Ph.D. Biotechnology (2018), University of Cambridge, UK M.Sc. Advanced Optical Technologies with honours & distinction (2014), University of Erlangen-Nuremberg, Germany B.Sc. Medical Engineering with BMBF award (2012), University of Erlangen-Nuremberg, Germany Research Interests: Dr Ströhl’s work revolves around advanced optical system development , spanning the full chain from optical theory and photolithography to instrumentation and biomedical application . Core themes include light-sheet microscopy , mechanosensitive Brillouin nanoscopy , label-free super-resolution techniques , and integrated photonics . Application domains cover dementia research , kidney & liver pathology , cardiac imaging and sustainable aquaculture . Scientific Awards & Funding: 2025 ERC Starting Grant—20 million NOK 2023 RCN Innovation Grant—1 million NOK 2021 RCN FRIPRO Young Research Talent Grant—8 million NOK 2019 EU Horizon 2020 MSCA Grant—2.1 million NOK EMBO Fellow, Nano DTC Fellow, OPTICA Senior Member Grants, Teams & Mentoring: Dr Ströhl currently directs a diverse team of post-docs, PhD candidates and engineers in the Ultrasound, Microwaves and Optics research group. He actively welcomes master’s thesis students and visiting scientists. All projects are supported by Norwegian and European funding frameworks and emphasize open science , cross-disciplinary collaboration and public outreach via video tutorials and popular-science talks.

Fabrice Lamarcheمشاهده پروفایل

دانشیار

• Virtual Humans
• Crowd Simulation
• Motion Planning
• +۵ مورد دیگر

Fabrice Lamarche serves as an Associate Professor at Université de Rennes 1 within the ESIR School of Engineering, while maintaining dual affiliation with the MimeTIC research team at IRISA / INRIA Rennes. His academic career spans uninterrupted service since 2004, evolving from Assistant Professor roles at IFSIC (2003-2009) to current positions at ESIR. As co-founder of Golaem (2009), he bridges academic research with commercial application in crowd simulation technology. His institutional journey includes sequential membership in SIAMES (2004-2006), Bunraku (2007-2011), and MimeTIC (2011-present) research teams at INRIA. Lamarche earned his PhD in Computer Sciences from Université de Rennes 1 in 2003 with thesis work on virtual human autonomy. His educational foundation includes a Master of Computer Sciences specializing in Computer Graphics and AI (1999-2000), a Master of Engineering from INSA de Rennes (1997-2000), and a Technical degree from IUT de Limoges (1995-1997). His research program centers on virtual human behavior modeling with emphasis on decision-making systems, path planning under environmental constraints, and crowd simulation architectures. Key innovations include TopoPlan for human-scale navigation and frameworks integrating high-level task scheduling with low-level motion planning. This work addresses fundamental challenges in creating autonomous virtual characters capable of navigating complex 3D environments while exhibiting realistic behaviors, with applications spanning virtual reality, gaming, and simulation-based training systems. Publication analysis reveals consistent output from 2001-2014, evolving from foundational behavioral animation (2001-2004) to sophisticated crowd simulation systems (2013-2014). A notable trajectory shows increasing integration of cognitive modeling with motion planning, alongside exploration of Brain-Computer Interfaces for virtual navigation. Recent work demonstrates particular strength in semantic decomposition of urban environments and time-space constrained task scheduling. His scientific contributions have earned significant recognition: Rennes city medal (2009) for research excellence Second prize at Deutsch Telekom Awards (FMX 2008) for TopoPlan/MKM integration As an active researcher and educator, Lamarche advises students through Université de Rennes 1 while leveraging INRIA resources and Golaem industry partnerships. His publication record indicates sustained grant funding, particularly through INRIA channels, with collaborative projects extending to neuroscience applications via Brain-Computer Interface research. The MimeTIC team affiliation provides infrastructure for multimodal interaction research in complex virtual environments. Lamarche's laboratory work through MimeTIC focuses on developing practical implementations of virtual human autonomy systems. His research group maintains strong industry connections via Golaem, which commercializes crowd simulation technology. Current efforts emphasize semantic understanding of virtual urban spaces and robust path planning under dynamic constraints, building on foundational work in topological navigation and behavioral decision systems.