جستجوی استاد راهنمای دانشگاهی

• Smart Grids
• Renewable Energy Integration
• Optimization of Power Systems
• +۴ مورد دیگر

Cuo Zhang is a Lecturer of Power Engineering and ARC DECRA Fellow at the University of Sydney's School of Electrical & Computer Engineering. He holds a B.E. (Hons.) from the University of Sydney (2014) and a Ph.D. in Electrical Engineering from UNSW (2018). His research focuses on smart grids, renewable energy integration, voltage control, and optimization of power systems. Key interests include distributed generation planning, energy storage systems, and demand response mechanisms. Dr. Zhang leads research on enhancing distribution network resilience through advanced control strategies and participates in the Net Zero Institute. He has secured grants such as the 2024 ARC DECRA project on renewables hosting capacity. Supervised students include Yunqing Zhang, working on robust renewables integration. His recent publications emphasize data-driven approaches, decentralized energy trading, and adaptive control for unbalanced networks. He explores machine learning applications in energy management and stochastic optimization under uncertainty. Awards include the University Medal for academic excellence. Awards: ARC DECRA Fellow Grants: 2024 Robust Renewables Hosting Capacity Enhancement Labs/Teams: Member of the Net Zero Institute

Ben Ali, Mahaمشاهده پروفایل

دانشیار

• Industrial Engineering
• Operations Management
• Supply Chain Optimization
• +۵ مورد دیگر

Maha Ben Ali is an Associate Professor at the Department of Mathematical and Industrial Engineering at Polytechnique Montréal. She is also an Adjunct Professor at Université Laval and a member of the Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT) and the Laboratoire Poly-Industries 4.0 . Education: Bachelor’s in Industrial Engineering, École Nationale des Ingénieurs de Tunis M.Sc. in Industrial Systems Engineering, École Nationale des Ingénieurs de Tunis M.Sc./Ph.D. in Mechanical Engineering (Industrial concentration), Université Laval Research Interests focus on Industrial Engineering , with emphasis on Demand Management , Supply Chain Optimization , Simulation Modeling , Industry 4.0 , and Data Valorization . Her work combines Operations Research with Machine Learning to solve complex production and logistics challenges, particularly in softwood lumber and bioethanol supply chains . Publications (34 total) include studies on reinforcement learning for demand-driven systems, hybrid recommendation systems in B2B contexts, and symbiotic bioethanol network design . She has presented at conferences like the Winter Simulation Conference and IISE Annual Conference . Scientific Awards: Best paper – CIGI-QUALITA-MOSIM 2023 David Martell Student Paper Prize in Forestry – CORS 2018 NSERC Alexander Graham Bell Canada Graduate Scholarship FRQNT Doctoral scholarship Fast-tracking scholarship Teaching includes courses like Production and Inventory Planning , Simulation of Production Systems , and Logistic Networks . She has supervised 9 completed Master’s theses on topics ranging from multi-project scheduling to CO₂ emission reduction in freight transportation .

Philip Brunnerمشاهده پروفایل

استاد

• Hydrogeology
• Surface Water-Groundwater Interactions
• Numerical Modeling
• +۳ مورد دیگر

Philip Brunner is a Professor of Hydrogeology at the University of Neuchâtel's Faculty of Science since 2012. He is based at the Center for Hydrogeology and Geothermics (CHYN), leading the Laboratory of Hydrogeological Processes. His work centers on sustainable water resource management through quantitative tools. He earned his PhD from ETH Zurich, focusing on sustainable salt and water management in Western China's agricultural basins. Post-PhD, he conducted three years of postdoctoral research in Australia, developing new approaches for simulating river-aquifer interactions. Brunner's research spans surface water-groundwater interactions, numerical modeling, and remote sensing. He integrates methods from numerical modeling, remote sensing, scientific computing, and isotopic chemistry. His interdisciplinary collaborations with mathematicians, biologists, and physicists address challenges in agriculture, ecohydrology, engineering, and sustainable resource management. Recent publications highlight innovative tracer techniques (noble gases, microbes), low-cost monitoring systems, and advanced numerical models. His work tackles climate change impacts on ecosystems, groundwater in conflict zones, and sustainable practices in diverse environments including mountains and agricultural regions. He teaches courses such as Introduction to Hydrological Processes (Master), Numerical Modeling (Master), Remote Sensing (Master), and Introduction to Soil Physics (Bachelor, in French). His laboratory serves as a center for experimental and computational hydrogeological research.

Luca Mottolaمشاهده پروفایل

استاد

• Battery-less IoT
• Mobile Space Robotics
• Smart Cities
• +۳ مورد دیگر

Luca Mottola is a Full Professor at Politecnico di Milano and Senior Researcher at RI.SE Sweden. He leads the Networked Embedded Software Lab (NESLab), focusing on next-generation IoT, battery-less systems, and mobile robotics. His work bridges embedded computing, wireless networks, and cyber-physical systems, with applications in smart cities and space robotics. Education: No explicit details provided in texts. Research interests include energy-harvesting IoT, drone communication, and real-time systems. Notable awards include the ACM SENSYS Test of Time Award (2022) and multiple Best Paper Awards at top conferences like MOBICOM and RTCSA. Grants/Projects: Overseen projects on battery-less IoT, drone localization, and energy-efficient systems. Editorial roles include IEEE Transactions on Mobile Computing and ACM Transactions on Sensor Networks. Labs/Teams: NESLab, FlyZone Testbed for aerial drones, and collaborations with NXP Technologies, TU Graz, and USC.

Brandon Luciaمشاهده پروفایل

استاد

• Intermittent Computing
• Energy-harvesting Systems
• Concurrency
• +۷ مورد دیگر

Brandon Lucia is a Full Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University's College of Engineering. He leads the abstract research group focusing on the intersection of computer architecture, systems, and programming languages. His work bridges theoretical foundations with practical implementations in energy-constrained environments. Lucia's research centers on intermittent computing systems and edge computing in extreme environments. His work on energy-harvesting systems has established fundamental principles for batteryless computing, while his orbital edge computing research pioneers computational intelligence for nanosatellite constellations. These research thrusts address critical challenges in reliability, efficiency, and programmability for systems operating under severe power constraints. His publication record shows a clear evolution from foundational work on intermittent computing models to sophisticated applications in space computing and edge intelligence. Recent publications demonstrate increasing integration of dataflow architectures with energy-harvesting constraints, particularly in satellite constellations where computational resources must be managed across distributed, power-constrained platforms operating in extreme environments. NSF CAREER Award (2017) IEEE TCCA Young Computer Architect Award (2019) Sloan Foundation Fellowship (2021) ASPLOS Best Paper Awards (2018, 2020) OOPSLA Distinguished Paper and Artifact Awards (2015) Lucia actively mentors numerous PhD students including Brad Denby, Zhuo Cheng, and Emily Ruppel, many of whom contribute significantly to his research program. His abstract research group maintains strong industry connections while pursuing fundamental advances in computing systems. The group has developed multiple open-source tools including Legerdemain for program analysis and MultiCacheSim for cache coherence simulation. His laboratory work spans from theoretical foundations of intermittent computing to practical implementations in space systems. Current projects include computational nanosatellite constellations, energy-minimal dataflow architectures, and secure edge computing systems that operate reliably despite frequent power failures.

Ryan K. Williamsمشاهده پروفایل

استادیار

• Real-Time Systems
• Robotics
• Multi-Agent Systems
• +۵ مورد دیگر

Ryan K. Williams is an Assistant Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. His research focuses on real-time systems optimization, multi-agent robotics, and computational frameworks for autonomous systems. He holds an NSF Career Award (2021) and has contributed to advancing algorithms for resilient and efficient multi-robot coordination. His work addresses challenges in distributed systems, including scheduling, fault tolerance, and resource allocation. Key areas include probabilistic security in multi-robot teams, topology control for stable coordination, and anticipatory planning for search and rescue operations. He also explores intersections with education, such as analyzing teacher professional learning impacts on student outcomes in STEM. Awards: NSF Career Award 2021 Grants: AF: Small grants (2024, 2021), CPS: Medium grant (2019) Labs/Teams: Collaborates on multi-robot systems and computational autonomy projects

Amneet Bhallaمشاهده پروفایل

دانشیار

• Fluid-Structure Interaction
• Multiphase Flows
• Aquatic Locomotion
• +۷ مورد دیگر

Dr. Amneet Bhalla serves as an Associate Professor in the Department of Mechanical Engineering within the College of Engineering at San Diego State University (SDSU). His primary contact email is asbhalla@sdsu.edu, with office located in Engineering Building Room 323-G, and phone number (619) 594-2043. Education: Ph.D., Mechanical Engineering, Northwestern University (2013) M.S., Mechanical Engineering, Indian Institute of Technology Kharagpur (2009) B.S., Mechanical Engineering, Indian Institute of Technology Kharagpur (2004-2008) Postdoctoral Training: University of North Carolina at Chapel Hill (Mathematics Department) and Lawrence Berkeley National Laboratory (Computational Research Division) Research Interests: Dr. Bhalla develops advanced numerical methods and high-performance computing techniques for computational fluid dynamics (CFD) and fluid-structure interaction (FSI) problems. His work spans aquatic locomotion, renewable energy device modeling, multiphase flows, vehicular aerodynamics, and bioengineering applications. He creates mathematical models to interrogate underlying flow physics for engineering design optimization, with emphasis on open-source software development through the IBAMR library. Publication Trends: Recent publications (2023-2025) focus on robust numerical frameworks for multiphase flows with phase change, acoustic streaming, and fluid-structure interaction. Key themes include mass conservation in level set methods, adaptive mesh refinement, and solvers for non-isothermal gas-liquid-solid systems. Applications range from aquatic locomotion and renewable energy devices to microfluidics and biomedical flows, demonstrating commitment to both theoretical advances and practical engineering solutions. Scientific Awards: No awards mentioned in the provided text Advising and Grants: Dr. Bhalla secured an NSF CAREER award (2023) for "Consistent Continuum Formulation and Robust Numerical Modeling of Non-Isothermal Phase Changing Multiphase Flows". As PI of the CFD Lab, he mentors graduate students in computational mechanics, leveraging prior industrial experience at ExxonMobil Upstream Research Company. His research integrates industrial practicality with academic rigor through collaborations with national laboratories. Laboratory and Team: The Computational Fluid Dynamics and Flow Physics Laboratory (CFD Lab) develops the open-source IBAMR software—a distributed-memory parallel implementation of the immersed boundary method with adaptive mesh refinement. The lab emphasizes transparency, community engagement, and reproducibility, establishing cross-institutional collaborations while advancing computational methods for complex flow phenomena in engineering and biological systems.

• Cryptography
• Cybersecurity
• Authentication Protocols
• +۵ مورد دیگر

Zheng Yang is a Professor at Tsinghua University's School of Software, with significant research contributions in cryptography, cybersecurity, and privacy-preserving systems. His work spans multiple institutions including collaborations with University of Helsinki's Secure System Group and Chongqing University of Technology. He maintains active research in both theoretical and applied security domains, with particular focus on industrial applications. Professor Yang's research interests center on cryptographic protocols, authentication mechanisms, and security for emerging technologies. His work addresses critical challenges in Cyber-Physical Systems security, Industrial Internet of Things protection, and privacy-preserving computation. He has made significant contributions to secure key exchange protocols, authentication systems, and defenses against sophisticated network attacks including DDoS mitigation strategies. His research bridges theoretical cryptography with practical implementations for resource-constrained environments. Analysis of Professor Yang's recent publications reveals a strong trend toward practical security solutions for industrial and embedded systems. His work increasingly focuses on balancing security with performance constraints in Cyber-Physical Systems and Industrial IoT environments. Key research themes include lightweight cryptography for resource-constrained devices, privacy-preserving location services, and novel authentication mechanisms that maintain security while minimizing computational overhead. His publications demonstrate consistent innovation in adapting cryptographic techniques to real-world security challenges. Professor Yang has established himself as a leading researcher through his extensive publication record in top security venues including IEEE Security & Privacy, USENIX Security, and ACM conferences. His work has been published consistently in high-impact journals and conferences, demonstrating sustained research productivity and influence in the security community. Professor Yang maintains active research collaborations with numerous institutions globally, evidenced by his extensive co-authorship network. His research has attracted significant funding for projects addressing critical security challenges in emerging technologies. His work on secure authentication protocols and privacy-preserving systems has practical applications across multiple industry sectors. Professor Yang leads research initiatives focused on secure Cyber-Physical Systems and Industrial IoT security. His laboratory work emphasizes practical implementations of cryptographic protocols for real-world systems, with particular attention to performance constraints in embedded environments. Current research directions include secure communication for programmable logic controllers, privacy-preserving location services, and adaptive defenses against sophisticated network attacks.

• Hydraulic Energy
• Hydroelectric Power
• CFD Simulation
• +۶ مورد دیگر

Cécile Münch-Alligné is a Professor in Hydraulic Energy at the University of Applied Sciences and Arts Western Switzerland (HES-SO) in Sion, where she serves as the Head of the Hydroelectricity Research Group and the Renewable Energy Program. She leads the Hydro Alps Lab, which conducts applied research in hydropower combining experimental and numerical approaches. Her work focuses on enhancing the flexibility of both small and large hydropower plants, with particular emphasis on adapting these systems to the evolving energy landscape and integration of renewable energy sources. Her educational background includes a BSc in Energy and Environmental Techniques, an MSc in Engineering, and a BSc in Industrial Systems, all from HES-SO Valais-Wallis. Her research spans multiple domains within hydraulic engineering and renewable energy systems, with particular expertise in CFD simulation, numerical methods, and hydraulic machine design. Münch-Alligné's research interests primarily center around improving hydropower flexibility through innovative approaches such as hydraulic short-circuit operating modes, variable speed operation, and energy recovery systems in water networks. She investigates both large-scale pumped storage power plants and micro-hydropower systems for urban water networks, with a strong focus on practical implementation and commercialization of research findings. Her work bridges theoretical modeling with experimental validation to address real-world challenges in the energy transition. Her research has been published extensively in leading journals, covering topics from Pelton turbine dynamics and Francis turbine vortex analysis to micro-turbine implementations in drinking water networks. The publications reveal a clear trend toward enhancing operational flexibility of hydropower systems to better integrate with intermittent renewable energy sources, with increasing emphasis on practical demonstration projects and commercial applications. As Principal Investigator, she has led multiple significant research projects including the SCCER 4 WP 3.2.0 2017-2020 (Supply of Electricity), Hydrolienne pour canaux artificiels Centrale de Lavey, and SOLUTION DE TRANSFERT D'ENERGIE PAR POMPAGE-TURBINAGE A PETITE ECHELLE. These projects, totaling over 2 million CHF in funding from sources including CTI, OFEN, and industrial partners, demonstrate her ability to secure substantial research funding and collaborate effectively with both academic and industry partners. Münch-Alligné leads the Hydro Alps Lab research team, which includes numerous researchers such as Steiner Amandus, Walpen Olivier, Vaccari Aldo, and others. Her collaborative approach extends to partnerships with institutions like Stahleinbau GmbH and The Ark Energy, facilitating the transfer of knowledge from research to industry application. The lab's work spans from fundamental fluid dynamics research to full-scale demonstration projects, creating a comprehensive pipeline from theory to practical implementation.

Ilia Polushinمشاهده پروفایل

دانشیار

• Robotics
• Teleoperation
• Control Systems
• +۱ مورد دیگر

Ilia Polushin is an Associate Professor at the Department of Electrical and Computer Engineering , Western University . His research focuses on Robotics, Teleoperation, Control Systems, and Biomedical Applications . Education : Ph.D. in Electrical Engineering (Carleton University), Cand. Sci. in Automatic Control (Saint-Petersburg Electrotechnical University) His work primarily addresses stability and control of teleoperation systems with communication delays, using scattering transformation techniques and projection-based force reflection algorithms . He has contributed to haptic systems, surgical robotics , and networked control applications , including drilling systems and cooperative teleoperation. Recent publications emphasize stabilization of conic systems , multi-agent synchronization , and nonlinear networked control . His research spans Robotics, Control Theory, Biomedical Engineering, and Industrial Automation . Scientific Awards : Best Conference Paper Award, IEEE International Conference on Mechatronics and Automation (2006) He has advised students and collaborated with researchers in Robotics , Control Systems , and Biomedical Applications . His laboratory focuses on teleoperation systems and haptic interfaces .

Peter Kazanzidesمشاهده پروفایل

استاد پژوهش

• Robotics
• Medical Robotics
• Augmented Reality
• +۴ مورد دیگر

Peter Kazanzides is a Research Professor in the Department of Computer Science at the Whiting School of Engineering, Johns Hopkins University, where he joined the faculty in 2002. His research focuses on robotics, medical robotics, augmented reality, and computer-assisted interventions with primary applications in computer-integrated surgery. His educational background includes multiple degrees from Brown University: ScB (1983) in Electrical Engineering AB (1983) in Computer Science ScM (1985) in Electrical Engineering ScM (1987) in Applied Mathematics PhD (1988) in Electrical Engineering Kazanzides is a member of the Robotics, Vision, and Graphics research group and directs the Sensing, Manipulation, and Real-Time Systems (SMARTS) laboratory. His work spans surgical robotics, mixed reality, and systems engineering, with emphasis on computer-assisted surgery in extreme environments including minimally invasive surgery, microsurgery, and space teleoperation. The SMARTS lab develops real-time sensing systems, augmented/mixed reality interfaces using head-mounted displays, high-performance motor control, and sensor fusion technologies, with strong focus on system integration and open-source platforms like the da Vinci Research Kit (dVRK). Analysis of his recent publications (2024-2025) reveals dominant trends in surgical robotics autonomy, augmented reality navigation, force estimation, and digital twin technologies. Key themes include AI-driven task automation, haptic feedback enhancement, real-time instrument segmentation, and simulation environments for surgical training, primarily leveraging the da Vinci Research Kit framework. As director of the SMARTS lab within the Laboratory for Computational Sensing and Robotics (LCSR), Kazanzides leads a collaborative ecosystem including the Computer Integrated Interventional Systems (CIIS) Lab, Advanced Medical Instrumentation and Robotics (AMIRO) Lab, Dynamical Systems and Controls Lab (DSCL), Computer Aided Medical Procedures (CAMP) Lab, Medical UltraSound Imaging & Intervention Collaboration (MUSiiC) Lab, and Photoacoustic & ULtrasonic Systems Engineering (PULSE) Lab. His lab maintains responsibility for the development and support of the open-source da Vinci Research Kit, a critical resource for surgical robotics research worldwide.

Venanzio Cichellaمشاهده پروفایل

استادیار

• Control Systems
• Robotics
• Autonomous Vehicles
• +۳ مورد دیگر

Venanzio Cichella serves as an Assistant Professor in the Department of Mechanical Engineering at the University of Iowa, specializing in advanced control systems and robotics research with applications spanning autonomous aerial vehicles, underwater systems, and soft robotics. His research portfolio prominently features Control Systems , Robotics , Autonomous Vehicles , Soft Robotics , Motion Planning , and Optimal Control . He develops theoretical frameworks for collision avoidance, coordinated path following, and motion planning, frequently employing Bernstein polynomials and Cosserat rod theory to address scalability challenges in multi-agent systems. His work on twisted and coiled artificial muscles (TCAMs) enables biomimetic soft robotic systems for underwater manipulation and rehabilitation applications. Analysis of his 2023-2025 publications reveals three dominant research threads: (1) Vision-based collision avoidance algorithms for intermittent measurement scenarios, (2) Physics-based modeling of TCAM-actuated soft robots using continuum mechanics, and (3) Bernstein polynomial-optimized trajectory generation for autonomous vehicles. These threads consistently bridge theoretical control innovations with practical implementations in UAV coordination, submarine maneuvering, and octopus-inspired robotics, demonstrating strong emphasis on environmental adaptation and computational efficiency.

• Forecasting
• Time Series Analysis
• Inventory Management
• +۵ مورد دیگر

Nikolaos Kourentzes is a Professor of Informatics at the University of Skövde , specializing in forecasting and operations research. His work bridges theoretical advancements in time series analysis with practical applications in supply chain management, tourism demand, and renewable energy forecasting. Academic Rank: Professor Department: Department of Information Technology Research Interests: His research focuses on hierarchical and temporal forecasting methodologies, integrating macroeconomic indicators into demand planning, inventory optimization, and machine learning applications. He explores forecast reconciliation, shrinkage estimators, and the role of expert judgment in predictive analytics. Recent Publications: Highlights include advances in hierarchical forecasting with leading indicators, probabilistic forecasts during crises like the pandemic, and complex smoothing techniques. His work spans journals such as Omega , International Journal of Forecasting , and European Journal of Operational Research . Collaborations: Kourentzes collaborates with researchers globally, including George Athanasopoulos, Rob Hyndman, and Robert Fildes, across domains like tourism analytics, tire industry forecasting, and public health modeling.

Dave Clarkeمشاهده پروفایل

استاد مدعو

• Quantitative Exercise Biology
• Exercise Physiology
• Sports Analytics
• +۳ مورد دیگر

Dr. Dave Clarke is an Adjunct Professor in the Department of Biomedical Physiology and Kinesiology at Simon Fraser University, leading the Clarke Laboratory for Quantitative Exercise Biology . His research focuses on Exercise-responsive cell signaling , Sports analytics using wearable sensors , Evidence-based exercise programming , and Clinical exercise physiology . The lab integrates mathematical modeling, clinical insights, and biomechanical approaches to address questions in athletic performance, metabolic disorders, and wearable technology applications. Dr. Clarke collaborates with institutions such as TRIUMF and the BC Cancer Research Centre. Publications highlight his work in critical power modeling , AMP-activated protein kinase dynamics , and mitochondrial disease treatments . His lab emphasizes interdisciplinary training, offering mentorship in experimental design, data analysis, and translational research. The Clarke Lab is affiliated with SFU’s Faculty of Health Sciences and maintains active outreach programs for public health education. Notable projects include developing hydraulic models for recovery kinetics prediction and validating chloride test strips for sodium excretion analysis. The lab’s work has been featured in journals like Frontiers in Sports and Active Living and Orphanet Journal of Rare Diseases . For real-time updates, follow the lab on Facebook .

Haibo Heمشاهده پروفایل

استاد

• Computational Intelligence
• Neural Networks
• Reinforcement Learning
• +۵ مورد دیگر

Dr. Haibo He is the Robert Haas Endowed Professor in the Department of Electrical, Computer, and Biomedical Engineering at the University of Rhode Island (URI). As an IEEE Fellow and NSF CAREER awardee, his research focuses on computational intelligence, neural networks, and reinforcement learning with applications to smart grids and microgrid systems. Ph.D. in Electrical Engineering, Ohio University, 2006 M.S. in Electrical Engineering, Huazhong University of Science and Technology, 2002 B.S. in Electrical Engineering, Huazhong University of Science and Technology, 1999 His research interests include: Computational Intelligence Adaptive Dynamic Programming Reinforcement Learning Deep Learning for Power Systems Distributed Control in Microgrids Imbalanced Data Learning Recent research trends from publications (2018-2025) show a focus on: Multi-agent reinforcement learning for energy systems Digital twin frameworks for grid security Event-triggered control mechanisms Finite-time convergence algorithms Cyber-attack resilient control systems Evolutionary computation in power networks Awards: IEEE Fellow (2018) NSF CAREER Award (2017) Dr. He leads the Computational Intelligence and Self-Adaptive Systems (CISA) Laboratory at URI, which conducts fundamental research on computational intelligence methods with applications to power systems, data mining, and neural networks.