Find Academic Supervisors

Alan SutherlandView profile

Professor

• International Macroeconomics
• Monetary Economics
• International Finance
• +3 more

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
• +5 more

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
• +7 more

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 ValaviView profile

Lecturer

• In-Memory Computing
• Neural Networks
• Hardware Acceleration
• +3 more

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 CHAHEDView profile

Professor

• Network Optimization
• Edge Computing
• Machine Learning in Networks
• +4 more

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. AfridiView profile

Professor

• Wireless Power Transfer
• Power Electronics
• Electric Vehicle Charging Systems
• +5 more

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 BortolottiView profile

Researcher

• Multidisciplinary design, analysis and optimization (MDAO) of wind energy systems
• Wind turbine rotor design
• Aeroservoelasticity of wind turbines
• +3 more

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
• +2 more

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
• +7 more

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 ChenView profile

Associate Professor

• Supply Chain Management
• Inventory Management
• Operations-Marketing Interface
• +2 more

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
• +7 more

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.

Renate EganView profile

Professor

• Techno-economic analysis
• Energy Data Analysis
• Machine Learning in Energy Systems
• +3 more

Renate Egan is a Professor and Deputy Head of School (Engagement) at the School of Photovoltaics and Renewable Energy Engineering , University of New South Wales (UNSW). She leads UNSW's activities in the Australian Centre for Advanced Photovoltaics , a national research consortium involving multiple Australian institutions. Her research focuses on: Techno-economic analysis of photovoltaic technologies Energy data analytics for decentralized systems Electricity market restructuring Technology transfer and commercialization Recent work examines machine learning applications in energy demand forecasting, thermal storage optimization, and bushfire resilience. She collaborates extensively across academia, industry, and government sectors. Key affiliations include: Co-Founder of Solar Analytics (Australia's largest independent energy monitoring provider) Executive Committee member of the IEA PV Power Systems program

• Robotics
• Unmanned Aerial Vehicles (UAVs)
• Mechatronics
• +7 more

Alexis Lussier Desbiens is an Associate Professor at the Université de Sherbrooke in the Department of Mechanical Engineering , Faculty of Engineering. He co-founded several research labs and initiatives including NSERC CREATE CoRoM (Collaborative Robotics in Manufacturing) and NSERC CREATE UTILI (Uninhabited Aircraft Systems Training). His work bridges robotics, mechanical design, and sports equipment innovation. PhD in Mechanical Engineering (Stanford University, 2012) BEng in Mechanical Engineering (Université de Sherbrooke, 2005) Postdoctoral Research (Harvard University, 2013) His research focuses on robotics and automation , particularly unmanned aerial vehicles (UAVs) with bioinspired design principles for mechanical intelligence. Key areas include: Autonomous UAV perching and climbing Hybrid locomotion systems Sports equipment dynamics (skis, hockey sticks) Magnetorheological actuator applications Conservation biology tools via aerial sampling Recent publications highlight interdisciplinary work in robotics , sports engineering , and ecological monitoring . His projects often integrate mechanical design with environmental or human-centric applications. Scientific recognition includes: Best Student Paper (IEEE SMC, 2021) Best Poster (ISEA, 2020) National Geographic Explorer (2020) CSME Gold Medal (2005) Current grants (2020-2023) include: $339,000 - High-performance UAV for power line interactions $1.65M - NSERC CREATE UTILI training program $120,000 - Intelligent hockey stick development He also leads the CREATEK Research Lab and maintains global collaborations with institutions like Harvard University, Stanford University, MIT, and EPFL.

James LacefieldView profile

Professor

• Biomedical Ultrasound Imaging
• Vascular Imaging
• Cancer Research Applications
• +5 more

James Lacefield is a Professor in both the Department of Electrical and Computer Engineering and the Department of Medical Biophysics at Western University. He serves as Director of the School of Biomedical Engineering and maintains his research laboratory in the Amit Chakma Engineering Building. His academic appointments span multiple disciplines, reflecting the interdisciplinary nature of his work in biomedical ultrasound imaging. Dr. Lacefield earned his Ph.D. and B.S.E. in Biomedical Engineering from Duke University. His educational background established the foundation for his current research program that bridges engineering principles with medical applications. His research focuses on the physical acoustics and signal processing aspects of ultrasound imaging, with particular emphasis on quantitative vascular imaging applications. Dr. Lacefield's laboratory develops novel methods for color Doppler, power Doppler, and contrast-enhanced ultrasound imaging, with primary applications in cancer research. Current projects include optimization of high-resolution ultrasound systems for tumor vascular characterization and development of methods to quantify spatial blood flow distribution in tumors. Analysis of his recent publications reveals a strong focus on quantitative ultrasound techniques for cancer applications, with particular attention to tumor perfusion assessment using contrast-enhanced ultrasound. His work demonstrates increasing sophistication in speckle analysis methods to improve the reliability of perfusion measurements in preclinical tumor models. Associate Editor, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control Member, Council of Chairs of Bioengineering and Biomedical Engineering Member, College of Reviewers, Canadian Institutes of Health Research Dr. Lacefield maintains active collaborations with multiple research groups including the Imaging Research Laboratories at Robarts Research Institute. His professional activities include editorial work for major ultrasound journals and participation in national review panels for biomedical research funding.

• Microfluidics
• BioMEMS
• Lab-on-a-Chip Technology
• +11 more

Prof. Kwang W. Oh is a tenured Professor at the Department of Electrical Engineering and Department of Biomedical Engineering within the School of Engineering and Applied Sciences at University at Buffalo (SUNY at Buffalo) . He serves as the Director of Graduate Studies in Electrical Engineering and Director of SMALL (Sensors and MicroActuators Learning Lab) . His academic journey includes PhD and MS in Electrical and Computer Engineering from University of Cincinnati (2001, 1997) and BS in Physics from Chonbuk National University (1995). Prof. Oh's research expertise lies at the intersection of microfluidics , BioMEMS , and lab-on-a-chip technologies. His lab has pioneered vacuum-driven microfluidic devices , PDMS-based systems , droplet manipulation , and chemical-free fabrication techniques . His work enables point-of-care diagnostics , single cell analysis , and wearable medical sensors , with significant contributions to sample-to-answer nanosystems and world-to-chip interfacing . The scientific awards section highlights his excellence in teaching and research: SUNY Chancellor's Award for Excellence in Teaching (2020) Meyerson Award for Undergraduate Teaching (2019) Qualcomm Faculty Award (2019) Senior Teacher of the Year (2017) Royal Society of Chemistry's Emerging Investigators (2013) Samsung Electronics' CEO Honor (2003) His lab has produced numerous PhD and MS students including Dr. Anyang Wang (2020), Dr. Nikhila Nyayapathi (2020), Mr. Liam Christie (2021), and Dr. Domin Koh (2019). As a conference chair , he has organized symposia at NanoTech (2012-2026) and served as editorial board member for Sensors , Micromachines , and Biomedical Engineering Letters .