جست‌وجوی استاد و پژوهشگر

Wang Li-Lianمشاهده پروفایل

استاد

• Applied Mathematics
• Numerical Analysis
• Spectral Methods
• +۵ مورد دیگر

Professor Wang Li-Lian is a faculty member in the Division of Mathematical Sciences at Nanyang Technological University (NTU), Singapore. He holds the rank of Professor of Applied Mathematics and has been affiliated with NTU since 2006, progressing through roles including Assistant and Associate Professor before his current position. His research focuses on spectral methods, computational acoustics/electromagnetics, and PDE-based image processing. He has supervised multiple PhD and Master's students, including Zhang Jing, Gu Ying, Yang Zhiguo, and others. Education and career highlights include a Postdoctoral Research Associate at Purdue University (2002-2003), followed by a Visiting Assistant Professorship (2003-2005). His academic work spans spectral element methods, fractional differential equations, and high-order numerical techniques for wave scattering problems. Notable contributions include advancements in spectral-Galerkin methods for nonlocal operators and exact nonreflecting boundary conditions for Maxwell's equations. Research interests emphasize high-accuracy numerical schemes, with applications to fractional PDEs, metamaterial simulations, and image processing. His publications (over 100+ articles) reflect expertise in spectral methods, computational physics, and mathematical modeling. Teaching responsibilities include courses on partial differential equations, numerical analysis, and scientific computing.

Ousmane Seidouمشاهده پروفایل

استاد

• Hydrological Modeling
• Climate Change Impacts
• Water Resources Management
• +۴ مورد دیگر

Dr. Ousmane Seidou is a Full Professor in the Department of Civil Engineering at the University of Ottawa, where he has served since 2007. He leads the Hydraulics Lab and holds affiliations with the Faculty of Engineering's Centre for Indigenous Community Infrastructure. His academic journey includes a PhD from École Polytechnique de Montréal (2002) and postdoctoral research at the Institut National de la Recherche Scientifique, Quebec. Dr. Seidou specializes in climate change impacts on water resources, hydrological modeling, and transboundary water management. Education: Ph.D. in Civil Engineering (Hydraulics), École Polytechnique de Montréal (2002) M.Sc. in Water Resources Engineering, École Polytechnique de Montréal (2002) Postgraduate Diploma in Hydroinformatics, École Inter-États des Ingénieurs de l'Équipement Rural (1998) Undergraduate Degree in Civil Engineering, École Mohammadia d'Ingénieurs (1996) Research Focus: Dr. Seidou’s work integrates hydrological modeling with climate adaptation strategies, emphasizing Africa’s water security. Key areas include: Climate change impacts on river basins (e.g., Niger, Congo) Development of flood early warning systems in West Africa Water-Energy-Food-Environment (WEFE) nexus frameworks Environmental flow estimation in wetland ecosystems He leads international projects involving multi-country collaborations and agencies like the United Nations Development Programme and the World Bank. Recent Projects: Principal Investigator for the Niger Basin Authority’s WEFE Nexus initiative Technical leadership in the Dutch-funded BAM-GIRE project (Mali/Guinea wetlands) Development of flood early warning systems for Niamey and Gaya (Niger) Teaching: Courses include Climate Change Impacts on Water Resources, Advanced Hydrological Modeling, and Water Resources Management. He mentors PhD students in hydrology and climate adaptation. Grants & Funding: Secured multi-million-dollar projects with organizations like Wetlands International and the UAE-BELEM Programme. Recent funding includes $135,000 for hydrological modeling tools in the Niger Basin. Labs/Teams: Director of the Hydraulics Lab at the University of Ottawa. Active in global initiatives like the Global Goal on Adaptation (GGA) indicator development under the Paris Agreement.

Randa Herzallahمشاهده پروفایل

دانشیار

• Control Systems
• Energy Systems
• Machine Learning
• +۲ مورد دیگر

Dr. Randa Herzallah is an Associate Professor at the University of Warwick with interdisciplinary expertise spanning control systems, quantum engineering, and machine learning. Her research develops probabilistic frameworks for complex systems control. Research interests focus on probabilistic control methods applied to energy grids, quantum systems, and biomedical applications. Recent work integrates machine learning with control theory for smart grid optimization and quantum system management. Publication analysis shows consistent focus on probabilistic control frameworks, with recent expansion into quantum applications and deep learning for industrial applications. Research funding includes EPSRC and Leverhulme Trust grants supporting quantum control and energy systems projects. Leads research in probabilistic control methodologies with industrial applications.

• Antennas
• Applied Electromagnetics
• Computational Electromagnetics
• +۲ مورد دیگر

Giuseppe Vecchi is a Full Professor at the Department of Electronics and Telecommunications (DET) of Politecnico di Torino , Italy. He leads the Applied Electromagnetics research group and contributes to projects in computational electromagnetics, metamaterials, and biomedical applications of electromagnetic fields. He has been a IEEE Fellow since 2010 and serves on PhD college committees for Electrical, Electronic, and Communications Engineering. Research Interests : Antennas, Applied and Computational Electromagnetics, Metamaterials, Microwave Imaging for medical applications, Nuclear Fusion Reactor Physics. Scientific Leadership : Principal Investigator for projects like METEOR, MTSA, and RESOLVED-K, focusing on terahertz generation, metasurface antennas, and real-time temperature mapping in hyperthermia. Awards : IEEE Fellow (2010), recognizing his contributions to electromagnetic simulations and antenna design. Students : Supervises PhD candidates in advanced antenna engineering, computational electromagnetics, and biomedical applications, including Owais Khan, Francesco Lattanzio, and Sara Paknezhad Panahi. Patents : Holds multiple patents in antenna diagnostics, encrypted metasurface antennas, and microwave soil disinfection systems.

• Computational Fluid Dynamics
• Discontinuous Galerkin Methods
• Finite Volume Methods
• +۶ مورد دیگر

Michael Dumbser is a Full Professor at the University of Trento's Department of Civil, Environmental and Mechanical Engineering. His research focuses on computational fluid dynamics, numerical methods for hyperbolic conservation laws, and high-performance computing. He specializes in developing structure-preserving numerical schemes such as discontinuous Galerkin and finite volume methods for continuum mechanics, relativistic fluid dynamics, and multiphase flows. Teaching responsibilities include courses like Calcolo numerico e programmazione , High-Performance Computing for Multi-Functional Metamaterials , and Metodi numerici per l'ambiente . His work emphasizes thermodynamically compatible formulations and adaptive numerical methods for complex physical systems. Recent research trends involve hyperbolic reformulations of classical models (e.g., Navier-Stokes-Korteweg, Einstein equations), staggered semi-implicit schemes for incompressible flows, and GPU-accelerated algorithms. His publications span topics from geophysical fluid dynamics to relativistic astrophysics, with a focus on maintaining physical conservation principles in numerical implementations. No scientific awards are explicitly listed in the provided information. His advising record is not detailed here, though his courses suggest involvement in student mentorship. Research collaborations include projects on metamaterials and computational geophysics. Current initiatives include developing unified models for earthquake rupture dynamics, non-Newtonian fluid simulations, and adaptive mesh refinement techniques. His lab work involves high-performance computing frameworks like ExaHyPE for large-scale wave propagation studies.

• Applied Mathematics
• Mathematical Physics
• Computational Science
• +۳ مورد دیگر

Ben Goddard is a Professor in the School of Mathematics at the University of Edinburgh. His work bridges applied mathematics with real-world scientific challenges, emphasizing interdisciplinary collaboration across engineering, biology, chemistry, and physics. He earned his PhD at the University of Warwick, later completing his final year at TU Munich following his advisor. His research focuses on mathematical modeling, numerical methods, and asymptotic analysis applied to problems such as quantum chemistry, fluid dynamics, and biological systems. Education: Bachelor’s degree in Mathematics (undergraduate details unspecified) PhD in Mathematical Quantum Chemistry (University of Warwick/TU Munich) Research interests include: Dynamic density functional theory (DFT) for complex fluids and nanoparticles Interfacial phenomena and contact line dynamics Numerical optimization and pseudospectral methods Biological systems modeling (e.g., RNA transcription mechanics) Recent work explores applications like ouzo phase behavior, aerosol droplet stability, and opinion dynamics in social networks. His collaborations span diverse fields, including experimental biology at the Welcome Centre for Cell Biology. He advocates for mathematicians’ role in interdisciplinary problem-solving, emphasizing clear communication and adaptability. Advising and grants: While specific grant details are not listed, his projects reflect significant funding and team-based research. He actively promotes STEM engagement through activities like designing math-themed escape rooms with his spouse, a statistician. Labs/Teams: Collaborates extensively with Edinburgh’s Schools of Engineering, Biology, and Informatics, though no specific lab names are mentioned.

James F. O'Brienمشاهده پروفایل

استاد

• Computer Graphics
• Computer Animation
• Physical Simulation
• +۷ مورد دیگر

Dr. James F. O'Brien is a Professor of Computer Science at the University of California, Berkeley, affiliated with research centers including the Berkeley Artificial Intelligence Research Lab (BAIR) and the Visual Computing Lab (VCL). His research focuses on computer graphics, animation, physical simulation, and image forensics, with applications in film, gaming, and virtual reality. O'Brien pioneered destruction modeling techniques used in over 200 films and games, earning an Academy Award in 2015. He holds leadership roles in tech companies like Juice Labs and Get Klothed, and has advised on patent litigation cases. Education: PhD in Computer Science (Georgia Tech, 2000), MS (Georgia Tech, 1997), BS (Florida International University, 1992). Research Interests: Computer Animation & Simulation Image/Video Forensics Human Perception of Motion VR/AR Privacy & Motion Data Machine Learning Applications Awards: Recipient of the 2015 Academy Award for Technical Achievement, ACM Distinguished Scientist (2009), and MIT TR-35 Innovator (2004). His work spans over 50,000+ VR user studies and groundbreaking contributions to cloth simulation and destruction modeling. Current Projects: Exploring ethical implications of extended reality (XR) motion data, developing privacy-preserving VR systems, and advancing AI-driven animation techniques.

Luca Sterponeمشاهده پروفایل

استاد

• Reconfigurable computing
• Computer-aided design algorithms
• Fault tolerance and reliability
• +۷ مورد دیگر

Luca Sterpone is a Full Professor at the Department of Control and Computer Science (DAUIN), Politecnico di Torino. He serves as Head of the Control and Computer Engineering Department (2023-2027), coordinates the Aerospace and Safety Computing Lab, and is a member of the Academic Senate and Power Electronics Innovation Center (PEIC). His research spans reconfigurable computing, fault tolerance, and radiation effects analysis in electronic systems. Professor since 2021 Department Head (DAUIN) since 2023 Coordinates international collaborations with ESA, AMD Xilinx, NVIDIA, and Thales Alenia Space Develops radiation-hardened FPGA tools (SETA, VERI-Place, PyXEL) 2007 EDAA Outstanding Dissertation Award and 2005 IEEE Best Paper Award Research Focus : Designing radiation-tolerant systems for aerospace, including fault-tolerant AI accelerators, FPGA reliability, and software-based error mitigation. He investigates soft error propagation in nanoscale circuits and develops tools for radiation sensitivity analysis in VLSI. His work integrates hardware-software co-design for mission-critical applications. Awards : EDAA Outstanding Dissertation Award (2007) IEEE European Test Symposium Best Paper (2005) SMACD Best EDA Tool Award (2018) ARC Best Paper candidate (2018) Teaching : He leads courses in Reconfigurable Computing (PhD level), GPU Programming , and Operating Systems . He has formal responsibility for teaching roles across 9 bachelor's and 7 master's years, and mentors multiple PhD students. Collaborations : Coordinates with the European Space Agency (ESA), University of Bielefeld, Universidad de Sevilla, and industrial partners like AMD Xilinx, NVIDIA, and General Motors. He leads projects such as RESCHIP4EU, VEGAS, and TERRAC for radiation-hardened computing solutions.

• Hydroinformatics
• Urban Hydrology
• Flood Modeling
• +۳ مورد دیگر

Jonathan L. Goodall is a Professor of Civil and Environmental Engineering and Director of the Link Lab at the University of Virginia. His research focuses on hydroinformatics, urban hydrology, and flood modeling, leveraging data science and cyber-physical systems to enhance resilience in coastal urban environments. He leads efforts in reproducible environmental modeling through integration of platforms like HydroShare, emphasizing open science and computational workflows. His work includes advancing machine learning techniques for real-time flood forecasting, integrating IoT and sensor networks for smart city applications, and assessing climate change impacts on coastal communities. Notable contributions involve developing surrogate models for flood prediction in Norfolk, VA, and studying compound flooding effects using hydrodynamic modeling paired with crowdsourced data. Collaborations span universities, national labs, and agencies like CUAHSI, focusing on environmental data interoperability and infrastructure resilience. Goodall’s research often addresses socio-technical challenges in urban flood management, combining engineering solutions with community engagement strategies. His lab explores reinforcement learning for real-time stormwater control, IoT education initiatives, and geospatial tools for flood vulnerability analysis. Projects frequently involve interdisciplinary teams and emphasize reproducibility through containerized environments and metadata standards.

Cheng Hanمشاهده پروفایل

استادیار

• Adaptable and Sustainable Intelligence
• Efficient Multimodality
• Parameter-Efficient Fine-Tuning
• +۷ مورد دیگر

Cheng Han is a tenure-track Assistant Professor in the School of Science and Engineering at the University of Missouri -- Kansas City (UMKC), where he conducts research in adaptable and sustainable intelligence, focusing on efficient AI systems and parameter-efficient fine-tuning methods for large-scale models. Ph.D., Rochester Institute of Technology (RIT) M.S., Pennsylvania State University (PSU) B.S., Tianjin University (TJU) His research interests center on creating energy-wise AI systems that empower communities and address environmental and social challenges. He focuses on multimodal and visual prompt tuning, transfer learning, and robust AI. His work bridges theoretical innovation with real-world deployment, particularly in efficient adaptation of vision and language models. His recent publications span top venues like NeurIPS, ICCV, CVPR, ICLR, EMNLP, and IEEE TPAMI. The research trends highlight a strong focus on parameter efficiency , prompt engineering , model robustness , and multimodal understanding . He investigates when and why prompt tuning outperforms full fine-tuning and develops novel frameworks like E^2VPT and M^2PT for efficient adaptation. Cheng Han actively contributes to the academic community as a reviewer and committee member. Program Committee, AAAI (2023–present) Program Committee, SIAM SDM (2024) Reviewer for NeurIPS, ICLR, CVPR, ICML, ICCV, TPAMI, TMLR, and others He advises Ph.D. students and teaches courses such as Deep Learning (COMP-SCI 5567). He has given invited talks at ICLR, ICCV, and seminars at NSF and Naval Research Laboratory. His research is supported by academic collaborations and likely grant funding, given his active publication and service profile. He leads a research group focused on sustainable and efficient AI, with code available on GitHub.

• Space Systems Engineering
• Computer Architecture
• Embedded Systems
• +۵ مورد دیگر

Pablo Parra Espada is an Associate Professor at the Department of Automática, University of Alcalá (Spain), affiliated with the Space Research Group (SRG-UAH). He holds a PhD from the University of Alcalá (2012) titled Integración de tecnologías de desarrollo y análisis basadas en componentes bajo un enfoque multi-plataforma , supervised by Dr. Sebastián Sánchez Prieto and Dr. Óscar Rodríguez Polo. His research focuses on space systems engineering , particularly in RISC-V processor design , embedded systems , and model-driven engineering . Key areas include hardware-software co-design for satellite systems, real-time computing, and fault-tolerant architectures. He has contributed to the Solar Orbiter mission through work on the Energetic Particle Detector (EPD) and its on-board software validation. His recent work emphasizes virtualization techniques for LEON processors, FPGA-based digital beamforming , and spaceborne phased array systems . He also explores model-driven approaches for automated configuration of ground support equipment. His interdisciplinary contributions bridge computer architecture with aerospace applications. Prof. Parra Espada has published extensively on topics such as hardware performance monitoring, memory management units for satellites, and system-level verification of space software. His work combines rigorous engineering methodologies with cutting-edge technologies to address challenges in space instrumentation and embedded systems.

David Daneyمشاهده پروفایل

استاد

• Robotics
• Cobotics
• Human-Robot Interaction
• +۱۴ مورد دیگر

David Daney is a Senior Researcher (Directeur de recherche) at Inria and HDR-qualified academic, currently serving as Head of Science for the Inria Center at the University of Bordeaux since July 2024. He is the team leader of the Auctus research group, focusing on robotics, cobotics, and human-robot interaction. He is affiliated with Inria and the École Nationale Supérieure de Cognitique (ENSC) at the University of Bordeaux, within the College of Engineering and the Department of Robotics. His research interests include Robotics, Cobotics, Human-Robot Interaction, Human Posture Analysis, Cable-driven Robots, Parameters Identification, Calibration, Interval Analysis, and Haptic Guidance. His work bridges theoretical robotics with industrial applications, particularly in aerospace, automotive, and sustainable agriculture. He has led and participated in numerous industrial collaborations with Airbus, Stellantis, Solvay, AKKA, and Farm3. His recent publications (2023–2025) demonstrate a strong focus on human-robot physical interaction, including real-time capacity estimation (Pycapacity), haptic guidance, model predictive control for dynamic environments, and musculoskeletal modeling for collaborative robotics. These works appear in top-tier journals such as IEEE Transactions on Robotics, Journal of Biomechanical Engineering, and Robotics and Autonomous Systems. HDR (Habilitation à Diriger des Recherches) Principal Investigator of ANR Pacbot Head of Science for Inria Center at University of Bordeaux Erdös number = 3 David Daney supervises multiple PhD students, including Alicia Barsacq, Ahmed-Manaf Dahmani, and Alexis Boulay. He has been principal investigator in several research projects such as LiChIE and ANR Pacbot, focusing on satellite production and human-robot collaboration. He also leads the SHAARE associate team with KAIST’s IRiS lab, advancing shared haptic control. His team develops tools for teleoperation, ergonomic analysis, and robot calibration, with applications in industrial and assistive robotics. He leads the Auctus team at Inria, which develops control and analysis techniques for human-robot physical interaction. The team collaborates with KAIST (SHAARE), ONERA, Pprime Institute, and industrial partners. The MOVER project studies human motor variability for ergonomics, and the Farm3 collaboration explores teleoperated vertical farming robotics.

Daniel Ventusمشاهده پروفایل

پژوهشگر

• Sexual Health
• Psychology
• Intervention Development
• +۳ مورد دیگر

Daniel Ventus is a Project Leader at Åbo Akademi University's Faculty of Education and Welfare Studies, specializing in interdisciplinary research across Psychology, Sexual Health, and Educational Technology. He leads the Experience Lab Health-related solutions and contributes to EU-funded projects like INTAKT and APOLLO2028 , focusing on academic procrastination interventions and healthcare worker resilience. Key research areas: Premature Ejaculation, High-Intensity Interval Training, Resilience Processes, Educational Robotics, and Mental Health interventions Recipient of the 2024 Best Poster Presentation Award at SWESrii for internet interventions His recent publications (2024-2025) examine: HIIT's impact on ejaculation control Real-time resilience assessment tools LLM-powered language learning systems for vulnerable children Physiological and psychological factors in sexual dysfunction As a peer reviewer for journals including Andrology and Scientific Reports , he contributes to multiple disciplines. Media visibility includes coverage in Finland-Swedish educational initiatives and sexual health research outreach (2018-2025).

Abolfazl Hashemiمشاهده پروفایل

استادیار

• Large-Scale Optimization
• Machine Learning
• Artificial Intelligence
• +۶ مورد دیگر

Abolfazl Hashemi is an Assistant Professor in the Elmore Family School of Electrical and Computer Engineering at Purdue University, directing the MINDS Group. He holds a B.Sc. from Sharif University of Technology (2014), and M.S.E. and Ph.D. degrees from The University of Texas at Austin (2016, 2020). His research focuses on Large-Scale Optimization for AI/ML, Learning at the Edge, and Decision-Making under Uncertainty, with applications in Federated Learning, Medical Image Analysis, and Cyber-Physical Systems. He leads the MINDS Group and collaborates with EnCORE and ICON centers. Key research areas include optimizing algorithms for machine learning, robustness in distributed systems, and adversarial learning. He has developed algorithms with mathematical guarantees for efficient deployment under resource constraints. Teaching includes Optimization for Deep Learning (graduate) and undergraduate courses like ECE 20001. He advises the Purdue RoboMaster robotics team and has mentored students through programs like SURF and Summer Stay Scholars. Outreach activities include fostering diversity through robotics competitions and research fellowships. His work bridges theoretical optimization with practical AI applications, emphasizing equitable and robust solutions in federated and decentralized learning.

Wendy M. Murrayمشاهده پروفایل

استاد

• Biomechanical Modeling
• Upper Limb Rehabilitation
• Prosthetics and Exoskeletons
• +۵ مورد دیگر

Wendy M. Murray is a Professor of Biomedical Engineering and Physical Medicine and Rehabilitation at Northwestern University's McCormick School of Engineering. She leads the ARMS Lab, focusing on biomechanical models of upper limb muscles to improve rehabilitation and prosthetic design. Her work addresses spinal cord injury, stroke, and orthopedic interventions. Education: Ph.D. and M.S. in Biomedical Engineering from Northwestern University, B.S. in Mathematics (summa cum laude) from University of Notre Dame. Research interests include musculoskeletal modeling, prosthetics control, and surgical simulations. Key contributions include widely cited anatomical databases and models for hand/wrist function. Current projects explore neuromuscular control, exoskeletons, and injury prevention in sports like baseball. Publications (selected 2024-2017) highlight advancements in motion capture, ultrasound imaging, and computational models for clinical applications. Her work bridges bioengineering with clinical practice to enhance functional recovery. Labs/Teams: Directs the ARMS Lab, collaborating with clinicians and engineers to translate biomechanical insights into real-world medical solutions.