جستجوی استاد راهنمای دانشگاهی

Sijia Gengمشاهده پروفایل

استادیار

• Power Systems
• Control Theory
• Nonlinear Dynamical Systems
• +۴ مورد دیگر

Sijia Geng is an Assistant Professor in the Department of Electrical and Computer Engineering (ECE) at Johns Hopkins University (JHU) and a core researcher at the Ralph O’Connor Sustainable Energy Institute (ROSEI). She directs the Power and Energy Network Systems Analysis (PENSA) Laboratory and co-leads the NSF-funded Electric Power Innovation for a Carbon-free Society (EPICS) Center as co-PI. Her research focuses on integrating control theory, mathematical analysis, and optimization to enhance renewable energy utilization and grid resiliency. Education: Ph.D. and M.S. (ECE & Mathematics) from the University of Michigan-Ann Arbor (2016–2022), B.S. in Automation from Harbin Institute of Technology (2016). Postdoctoral work at MIT (2022) and visiting scholar roles at Purdue University (2015) and Pacific Northwest National Lab (2018). Research Interests: Dynamic analysis of inverter-based power systems, nonlinear control theory, data-driven decision-making, and multi-energy systems. Her work emphasizes achieving autonomous, resilient energy systems through advanced computational tools and theoretical frameworks. Awards: Best Paper Award at MIT/Harvard Applied Energy Symposium (2022), MIT Rising Stars in EECS (2021), Barbour Scholarship (2021), Towner Prize (2018), and Gerald and Esther Forrest Fellowship (2016). She is active in IEEE and INFORMS, organizing sessions at PES General Meeting and CISS conferences. Grants & Collaborations: Funded by NSF, DOE, MIT Energy Initiative, and industry. Leads global initiatives through EPICS, collaborating with UK, Australian, and international stakeholders. Co-leads ROSEI’s Grid pillar to advance fossil-free energy systems. Labs & Teams: Directs PENSA Lab, affiliated with JHU’s Data Science and AI Institute, Applied Mathematics & Statistics, and Computer Science departments.

Hatem Abou-Zeidمشاهده پروفایل

استادیار

• AI for 6G
• Wireless Sensing
• Extended Reality Networking
• +۵ مورد دیگر

Dr. Hatem Abou-Zeid is an Assistant Professor in the Department of Electrical and Software Engineering at the University of Calgary, directing the WAVES Research Group. He holds adjunct positions at Queen’s University, Carleton University, and Ontario Tech University. His research focuses on AI-driven 6G networks, wireless sensing, extended reality (XR), and brain-computer interfaces (BCI). Prior to academia, he spent 7 years in industry at Ericsson and Cisco, leading projects in 5G radio access and network intelligence, resulting in 20+ patents and $3.5M+ collaborative research projects. Education: PhD in Electrical and Computer Engineering (Queen’s University), M.Sc. and B.Sc. in Electronics and Communications Engineering (Arab Academy, Egypt). Research interests span trustworthy AI for 6G, joint sensing & communication systems, and AI for immersive networking. Notable work includes foundational models for 6G radios, self-supervised learning for spectrograms, and safe reinforcement learning for network slicing. His lab explores pediatric BCI, IoT edge computing, and low-power wireless prototyping. Publications highlight contributions to AI-driven resource allocation, 5G/6G slicing, and federated learning in tactical networks. Awards include the 2023 Early Research Excellence Award and 2023 Software Engineering Professor of the Year. Advising involves 15+ students and postdocs, with collaborations spanning academia (e.g., Hotchkiss Brain Institute) and industry (Ericsson, Telus). Current openings exist for PDF/PhD researchers in AI/6G wireless systems and pediatric BCI. Labs/Teams: Director of WAVES Lab; collaborates with Ericsson Canada, Alberta Innovates, and Canadian Space Agency on applied research projects. Teaching includes advanced networking, machine learning systems, and IoT courses.

Bayu Jayawardhanaمشاهده پروفایل

استاد

• Mechatronics
• Nonlinear Control Systems
• Robotics
• +۵ مورد دیگر

Prof. Bayu Jayawardhana is a Full Professor in Mechatronics and Control of Nonlinear Systems at the University of Groningen, affiliated with the Faculty of Science and Engineering. He leads the Jayawardhana Group focusing on opto-mechatronics and advanced nonlinear control theories. His roles include Director of Engineering and Scientific Director of the Engineering and Technology Institute Groningen. He holds editorial positions in journals like International Journal of Robust and Nonlinear Control and European Journal of Control . Education: PhD in Control and Power Group from Imperial College London (2006), M.Eng from Nanyang Technological University (2003), and B.Eng from Institut Teknologi Bandung (2000). Research interests span opto-mechatronics for high-tech systems, nonlinear control, and systems biology. Key projects include digital twins for energy optimization, control of ocean energy systems, and modeling of cryogenic actuators for telescopes. His work integrates AI and model-based methods for high-performance systems. Notable awards include the 2016 FSE Faculty Teacher of the Year Award and the Ben Feringa Impact Award (2020). He advises on ventures like Ocean Grazer B.V. and Sencilia B.V. Teaching includes graduate courses on nonlinear control, opto-mechatronics, and fitting dynamical models to data. His research labs include the Groningen Centre for Systems and Control and the Data Science and Systems Complexity Center.

Mehmet Öztürkمشاهده پروفایل

استاد

• Energy Harvesting
• Thermoelectrics
• Nanoelectronics
• +۵ مورد دیگر

Dr. Mehmet Öztürk is a Professor in the Department of Electrical and Computer Engineering at North Carolina State University. His research focuses on nanoelectronics, energy harvesting, and advanced materials for flexible electronics, particularly thermoelectric devices for body heat energy conversion. He holds a Ph.D. in Electrical Engineering from NC State, a Master’s from Michigan Technological University, and a Bachelor’s from Bogazici University. Dr. Öztürk’s research interests span Physical Electronics, Photonics, and Magnetics, with emphasis on novel materials and processes for thermoelectric generators and wearable technologies. His work includes developing flexible, high-efficiency thermoelectric systems using liquid metal interconnects and graphene-doped elastomers. Recent projects involve aerosol spray deposition techniques for stretchable electronics and optimizing materials for body heat harvesting systems. Key scientific contributions include analytical models for thermoelectric energy extraction, high thermal conductivity composites, and microporous CNT nanocomposites. His work bridges fundamental material science with applied engineering solutions for energy-efficient wearable devices. Awards: 2020 William F. Lane Outstanding Teaching Award 2009 IEEE Fellow for contributions to Si/SiGe epitaxy 2006 IEEE Undergraduate Teaching Award Lab Affiliations: Center for Advanced Self-Powered Systems of Integrated Sensors and Technologies (ASSIST)

Alan Sutherlandمشاهده پروفایل

استاد

• International Macroeconomics
• Monetary Economics
• International Finance
• +۳ مورد دیگر

Alan Sutherland is a Professor of Economics at the University of St Andrews' Business School. He specializes in international macroeconomics, monetary economics, and financial market integration. His research focuses on the macroeconomic implications of exchange rate policies, monetary policy regimes, and cross-country financial linkages. He leads projects funded by the Economic & Social Research Council, including 'The Macroeconomics of Financial Globalisation' (2011-2015) and 'Monetary Policy Welfare and International Financial Markets' (2006-2007). Research Interests: International macroeconomic policy design Exchange rate determination Financial market integration effects Numerical methods for macroeconomic modeling His recent work emphasizes the role of international financial flows in transmitting economic shocks between countries. He has developed influential solution methods for analyzing multi-country general equilibrium models. Key contributions include frameworks for understanding optimal monetary policy under incomplete financial markets and asymmetric information conditions. Scientific Recognition: 2013 Fellow of the Royal Society of Edinburgh Recipient of 2 ESRC-funded research grants

• Industrial Automation
• Control Systems
• Machine Learning Applications
• +۵ مورد دیگر

Valeriy Vyatkin is a Professor at the Department of Electrical Engineering and Automation, Aalto University. His research focuses on advancing industrial automation, control systems, and their integration with emerging technologies like machine learning and digital twins. He specializes in standards such as IEC 61499, addressing interoperability, formal verification, and performance optimization in distributed automation systems. Key research interests include: Physics-informed machine learning for industrial processes (e.g., steel rolling, reservoir engineering) Formal methods for control system validation and safety-critical applications Development of adaptive automation frameworks for Industry 5.0 challenges, including human-robot collaboration and energy systems Interoperability between legacy and modern industrial standards (OPAS, OPC UA) Recent work emphasizes real-time simulation, FPGA-based control prototyping, and AI-driven solutions for energy efficiency and sustainability in manufacturing, horticulture, and process industries. Publications span topics like robotic walker design, probabilistic model checking, and decentralized learning management systems. He collaborates on EU and industry-funded projects, focusing on digital twin implementation, edge computing, and virtual commissioning. His team develops tools for automated code generation, system migration, and anomaly detection in complex industrial settings.

• Autonomous Vehicles
• Intelligent Transportation Systems
• Robotics
• +۷ مورد دیگر

Miguel Ángel Sotelo Vázquez is a full Professor at the University of Alcalá, leading the INVETT Research Group (Intelligent Vehicles and Traffic Technologies). He holds the Department of Automatic Control and specializes in autonomous systems, particularly in path planning, sensor fusion, and human-vehicle interaction. His research integrates machine learning, robotics, and control theory to address challenges in intelligent transportation systems. He earned his Ph.D. in 2001 with a thesis on autonomous vehicle navigation in partially known environments. His work emphasizes real-world deployment, explainable AI, and safety-critical systems. Recent projects focus on lane change prediction, pedestrian behavior modeling, and cybersecurity for autonomous systems. Key contributions include neuro-symbolic frameworks for decision-making, real-time multi-physics field reconstruction, and cross-cultural studies of pedestrian interactions. He collaborates internationally on urban mobility resilience and hydrogen refueling infrastructure. Research Highlights : Development of knowledge graph-based prediction architectures Experimental validation of human-vehicle interaction in VR environments Creation of the SCOUT trajectory prediction framework

Hossein Valaviمشاهده پروفایل

مدرس

• In-Memory Computing
• Neural Networks
• Hardware Acceleration
• +۳ مورد دیگر

Hossein Valavi is a Lecturer and Assistant Director of Undergraduate Studies at Princeton University, contributing to advancements in computer architecture and hardware acceleration. His research focuses on in-memory computing, neural networks, and energy-efficient systems, with notable work in reconfigurable architectures and mixed-signal processing. He has received multiple teaching awards, including recognition for innovative pandemic-era Car Lab courses and collaborative work honored by the Edison Patent Award. His academic contributions span academic positions since 2018, emphasizing both research and pedagogical excellence. Key technical areas include scalable in-memory computing systems, analog neural network accelerators, and low-power matrix factorization algorithms. His work addresses critical challenges in data movement reduction and hardware-software co-design for modern computing systems. Awards: Teaching Excellence Awards (2021, 2023), Edison Patent Award (2023) Grants & Projects: Leading developments in in-memory computing accelerators and embedded microprocessor designs Research teams under his guidance have produced impactful IP in semiconductor layouts, CNN accelerators, and programmable architectures, aiming to bridge theoretical computer science with practical hardware implementations.

Tijani CHAHEDمشاهده پروفایل

استاد

• Network Optimization
• Edge Computing
• Machine Learning in Networks
• +۴ مورد دیگر

Prof. Tijani CHAHED is a Professor at Telecom SudParis, part of Université Paris-Saclay, affiliated with the SAMOVAR laboratory and the NeSS research group. His work focuses on network optimization, edge computing, machine learning applications in telecommunications, and game-theoretical frameworks for distributed systems. He holds a position in the Department of Computer Science and Telecommunications. His research spans resource allocation in 5G/6G networks, energy efficiency strategies for mobile infrastructure, reinforcement learning for dynamic systems, and coalitional game theory for multi-agent systems. Key contributions include optimization of cache allocation in edge computing, latency-critical traffic management (URLLC), and strategic investment models for distributed computing infrastructures. Selected articles highlight advances in edge computing resource management, metaverse data transport over 5G, and energy-efficient sleep mode control for base stations. His work often intersects with industrial applications in green networks and smart grid integration for mobile infrastructure. Collaborations involve institutions like École Polytechnique, INRIA, and industry partners in telecommunications. Current projects include 6G network architectures, metaverse-enabled edge services, and decentralized resource allocation frameworks. Labs/Teams: SAMOVAR Lab (Signal and Media Access Networks, Optical and Radio Networks), NeSS Group (Networked Systems and Services).

Khurram K. Afridiمشاهده پروفایل

استاد

• Wireless Power Transfer
• Power Electronics
• Electric Vehicle Charging Systems
• +۵ مورد دیگر

Khurram K. Afridi is a Professor in the Electrical and Computer Engineering Department at Cornell University's College of Engineering. With a BS from Caltech and SM/PhD from MIT, he leads the High-Frequency Power Electronics and Control (HFPEC) research group. His work focuses on high-frequency power electronics, wireless power transfer systems, and electric vehicle charging infrastructure. Dr. Afridi's research spans capacitive wireless power transfer systems for electric vehicles, high-frequency power converters , impedance control networks , and power density optimization . His team has developed innovative approaches for multi-MHz wireless power transfer, reduced-fringing-field systems, and high-efficiency power conversion architectures. Recent work emphasizes practical implementation challenges including thermal management, pavement-embedded systems, and dynamic charging applications. His publications reveal a strong focus on high-power-density systems , wireless charging technologies , and advanced power conversion techniques . The research spans both theoretical modeling and practical implementation, with numerous papers in top conferences like APEC, ECCE, and IEEE journals. Key themes include improving power transfer efficiency at multi-MHz frequencies, developing novel matching network designs, and creating practical systems for electric vehicle charging infrastructure. First Place Prize Paper Award, IEEE Journal of Emerging and Selected Topics in Power Electronics, 2023 First Place Best Contribution Award, IEEE WPTCE, 2023 Second Place Prize Paper Award, IEEE Transactions on Power Electronics, 2022 Distinguished Lecturer, IEEE Vehicular Technology Society, 2022 Cornell Engineering Research Excellence Award, 2021 NSF CAREER Award, 2016 Dr. Afridi has successfully advised numerous graduate students who have received multiple Outstanding Presentation Awards at major conferences. His research has been supported by significant funding including the NSF CAREER Award. The HFPEC group maintains strong industry connections and focuses on translating theoretical advances into practical power electronics solutions with real-world impact. Current research directions include electrified roadways, dynamic wireless charging systems, and high-power-density power conversion architectures for next-generation applications.

Pietro Bortolottiمشاهده پروفایل

پژوهشگر

• Multidisciplinary design, analysis and optimization (MDAO) of wind energy systems
• Wind turbine rotor design
• Aeroservoelasticity of wind turbines
• +۳ مورد دیگر

Pietro Bortolotti is a senior researcher at the National Wind Technology Center, focusing on wind energy systems. He leads U.S. Department of Energy-funded projects like Big Adaptive Rotor and Holistic Systems Engineering, advancing land-based wind turbine technology through multidisciplinary design and multi-fidelity optimization approaches. Education: Bachelor in Energy Engineering, Politecnico di Milano Master in Sustainable Energy Technology, Technical University of Delft PhD in Mechanical Engineering, Technical University of Munich His research spans MDAO of wind energy systems , rotor design , and aeroservoelasticity , with applications in turbine aerodynamics, noise reduction, and AI-driven environmental monitoring. Recent work includes comparing downwind/upwind turbine configurations, bat tracking systems, and large-scale turbine optimizations. Key trends in his 2024–2025 publications reflect advancements in rotor dynamics , multi-fidelity modeling , and AI integration for wildlife monitoring. Collaborations include institutions like DTU, TU Delft, and NREL, with tools like WISDEM, WEIS, and OpenFAST underpinning his research. His professional journey includes postdoctoral work at NREL (2018–2019), research roles at Technical University of Munich (2013–2018), and a research assistantship at Denmark Technical University (2012–2013). He contributes to projects improving numerical models for wind turbine analysis and optimization.

• Algorithms and Complexity
• Logic
• Database Theory
• +۲ مورد دیگر

Martin Grohe is a Professor at the School of Logic and Theory of Discrete Systems , part of the Department of Computer Science at RWTH Aachen University . His research spans Algorithms and Complexity , Logic , Database Theory , Graph Theory , and Machine Learning , with a focus on integrating logical frameworks into computational models. His recent work explores graph neural networks , Weisfeiler-Leman algorithms , and parameterized complexity , as seen in publications on isomorphism testing , database repairing , and probabilistic query evaluation . While no specific scientific awards are mentioned, his contributions to graph theory and machine learning are widely recognized through numerous peer-reviewed publications.

• Electromagnetic Interference (EMI)
• Filter Design
• Time-Domain Analysis
• +۷ مورد دیگر

Daria Nemashkalo is a researcher affiliated with the Digital Society Institute and Radio Systems at the University of Twente. Her work focuses on electromagnetic interference (EMI) filter design, time-domain analysis, and multichannel systems, particularly in power electronics and three-phase applications. Key Research Areas: EMI filter performance, mode decomposition, common mode choke saturation, and time-domain measurement techniques. Contributions: Published extensively on EMI mitigation strategies and filter optimization, including work on multichannel testing and real-world implementation challenges. Collaborations: Active in electromagnetic compatibility symposia, notably with peers like Peter Koch and Frank Leferink.

Lucy Chenمشاهده پروفایل

دانشیار

• Supply Chain Management
• Inventory Management
• Operations-Marketing Interface
• +۲ مورد دیگر

Associate Professor Lucy Chen is a faculty member at the NUS Business School , National University of Singapore, specializing in the Department of Analytics & Operations. With over 15 years at NUS, she bridges operations management and business analytics in her teaching and research. PhD and MSc in Operations Management from Cornell University Her research explores inventory management , supply chain dynamics , and the intersection of operations-marketing . Recent work investigates corporate behavior around quarterly targets, including publications like Supply Chain Performance with Target-Oriented Firms . She employs immersive teaching methods such as supply chain simulations and role-playing games to engage students. Lucy's Google Scholar profile reveals 15 years of contributions spanning: Strategic inventory optimization Behavioral aspects of supply chain decision-making Co-opetition models in service clusters Impact of financial turbulence on operations Cultural influences on inventory behavior Architectural innovations in balanced ordering systems In 2022, her research on target-oriented firms demonstrated how operational adjustments benefit trading partners more than focal companies. She actively mentors students in operations/supply chain management , emphasizing skill transferability to sectors like banking analytics and logistics consulting.

• Embedded Systems
• Hardware-Software Co-Design
• Invasive Computing
• +۷ مورد دیگر

Prof. Dr.-Ing. Jürgen Teich is a full Professor and Chair for Hardware-Software Co-Design at the Department of Computer Science, Friedrich Alexander University Erlangen-Nuremberg (FAU). He serves as Head of Department Computer Science and Vice Dean of the Technical Faculty since August 2024, and has been Speaker of the FAU Research Center Embedded System Initiative (FAU ESI) since 2023. His educational background includes: Diploma degree in Electrical Engineering, University of Kaiserslautern (1989) Dr.-Ing. degree in Electrical Engineering, University of Saarland (1993) Habilitation (PD Dr.-Ing.) entitled "Synthesis and Optimization of Digital Hardware/Software Systems" (1996) Prof. Teich's research focuses on Embedded Systems , Invasive Computing , Hardware-Software Co-Design , and Reconfigurable Computing . His work spans from theoretical foundations to practical implementations, with particular emphasis on resource-constrained systems, many-core architectures, and energy-efficient computing. He has pioneered research in invasive computing paradigms that enable more efficient use of many-core processors by allowing applications to dynamically claim resources. His recent publications reveal a strong trend toward energy-efficient AI deployment on embedded devices , security of embedded systems , and novel memory technologies . There's a clear focus on practical implementations of machine learning on microcontrollers (TinyML), hardware acceleration for data processing, and innovative approaches to power management in self-powered systems. Among his notable scientific awards are: IEEE Fellow (since 2018) Member of Academia Europaea, Section Informatics (since 2011) Member of the National Academy of Science and Engineering (acatech) (since 2018) Member of the German Society of Humboldtians (since 2021) Prof. Teich has been Principal Investigator for numerous DFG-funded projects including SFB/Transregio 89 "Invasive Computing" (2010-2022), SFB 694, and multiple priority programs. He has coordinated large collaborative research efforts across Germany and internationally, with significant funding from DFG and other sources. His research group has produced influential work in embedded systems design and co-design methodologies. He leads the Hardware-Software Co-Design research group at FAU, which focuses on innovative approaches to embedded system design, invasive computing architectures, and efficient implementation of machine learning on resource-constrained devices. The group maintains strong collaborations with industry partners including Intel, Xilinx, and automotive companies.