جست‌وجوی استاد و پژوهشگر

Mahmood Azimi-Sadjadiمشاهده پروفایل

استاد

• Digital Signal Processing
• Machine Learning
• Distributed Sensor Networks
• +۳ مورد دیگر

Dr. Mahmood Azimi-Sadjadi is a full Professor in the Department of Electrical and Computer Engineering at Colorado State University (CSU), affiliated with the Walter Scott, Jr. College of Engineering. He leads the Digital Signal/Image Processing Laboratory , focusing on advanced signal processing, machine learning, and underwater acoustics research. His work spans sonar systems, distributed sensor networks, and remote sensing applications. Educational Background: B.S. in Electrical Engineering, University of Tehran (1977) M.S. and Ph.D. in Electrical Engineering, Imperial College of Science and Technology, University of London (1978, 1982) Research Focus: His research emphasizes statistical signal/image processing, machine learning, and underwater target detection/classification using sonar. He has pioneered methods like manifold-based UXO classification and Bayesian occupancy grids. His lab develops both theoretical frameworks (e.g., canonical correlation analysis) and applied systems (e.g., acoustic tomography). Recent Publications Trends: Recent work includes adaptive machine learning for underwater UXO classification, wildfire prediction via satellite data, and autonomous systems navigation. His publications blend signal processing fundamentals with cutting-edge AI techniques. Awards & Affiliations: 1999 Abell Faculty Teaching Award (College of Engineering) Fellow of CIRA (Center for Information and Remote Sensing Research) Member of IEEE (Life Member) and IEEE Neural Network Society Advising & Labs: Directs the Digital Signal/Image Processing Lab, which collaborates on projects like acoustic source localization and sensor network optimization. His research has been supported by grants from agencies like SERDP (e.g., MR-2416 project).

Marta Ariasمشاهده پروفایل

دانشیار

• Machine Learning
• Data Mining
• Design and Analysis of Algorithms
• +۳ مورد دیگر

Marta Arias is an Associate Professor in the Computer Science Department at Universitat Politècnica de Catalunya (UPC), Barcelona, and a member of the LARCA research group. She has held academic positions since 2007, including roles at Columbia University and the University of Edinburgh. Her research focuses on Machine Learning, Data Mining, Algorithm Design, and Logic in Computer Science. She teaches advanced courses in Machine Learning, Information Retrieval, and Complex Networks at undergraduate and master's levels, including the Erasmus Mundus program in Data Mining and Knowledge Management. Educations: PhD in Computer Science from Tufts University (2000-2004), Postgraduate Studies at University of Edinburgh (1999-2000), B.Sc. in Computer Science from UPC (1992-1997). Professional experience includes software engineering and research roles in New York and Barcelona. Research highlights include developing algorithms for real-time ranking systems, Twitter-based financial forecasting, and causal network analysis. Notable contributions include the 'Best Paper Award' at AIPESW@ECAI 2020 and a 3rd place award in football performance research. Her work spans theoretical foundations (e.g., Horn clause learning) and applied domains like cybersecurity, healthcare analytics, and energy systems. Teaching responsibilities include labs and lectures on Machine Learning, Information Retrieval, and Programming, with active involvement in curriculum design and pedagogical innovation. Ongoing projects include enterprise risk analysis, synthetic data generation, and network modeling.

• Economic Model Predictive Control
• Stability of Nonlinear Systems
• Chemical Reaction Networks Theory
• +۵ مورد دیگر

David Angeli is a Professor of Nonlinear Network Dynamics in the Department of Electrical and Electronic Engineering at Imperial College London's Faculty of Engineering. Affiliations: Control and Power Research Group Energy Futures Lab His research focuses on Economic Model Predictive Control, Stability of Nonlinear Systems, Chemical Reaction Networks Theory, Systems Biology, and Control of Smart Grids. He develops theoretical frameworks for networked systems with applications in energy infrastructure and biological processes, emphasizing robustness and scalability in distributed settings. Recent publications (2023-2025) highlight work on distributed control algorithms, Lyapunov-based stability certification, and small-gain theorems for interconnected systems. His research bridges control theory, game theory, and machine learning to solve problems in cyber-physical systems, particularly in resilient consensus protocols and economic optimization for heterogeneous networks. As a core member of the Control and Power Research Group and Energy Futures Lab, he contributes to sustainable energy solutions and advanced control methodologies for complex networked systems.

Bikash Palمشاهده پروفایل

استاد

• Power System Stability
• Power System Control
• Dynamic State Estimation
• +۵ مورد دیگر

Bikash Pal is a Professor of Power Systems at Imperial College London’s Department of Electrical and Electronic Engineering, within the Faculty of Engineering. He specializes in power system stability, control, and computation, with research supported by EPSRC, National Grid, GE, and Siemens. His work includes leading large-scale international consortia, such as the six-university UK-China ROSES project (2020–2023), and developing tools like fast power flow and volt-var control for Siemens’ Spectrum Power. He has graduated 30 PhD students and published over 160 papers in IEEE and IET journals, co-authoring four books and award-winning IEEE reports. Education: B.Eng. (First Class Honours, Jadavpur University, 1990), M.Eng. (First Class, IISc Bangalore, 1992), PhD (Best Thesis, Imperial College London, 1999). Research Interests: Power system stability, control, dynamic state estimation, renewable energy integration, and smart grid technologies. His work addresses challenges posed by high renewable penetration, inverter-based resources, and grid resilience. Key Achievements: 2025 IEEE PES Kundur Award, Fellow of IEEE and The Royal Academy of Engineering, 2016 President’s Award for Outstanding Research. He has held visiting professorships at DTU (Denmark), University of Duisburg-Essen (Germany), and Chinese institutions. Professional Roles: Former Vice President of IEEE PES Publications (2019–2023), Editor-in-Chief of IEEE Transactions on Sustainable Energy, and IEEE Distinguished Lecturer. He advises UN agencies and utilities worldwide, contributing to grid stability solutions and training programs. Grants and Collaborations: Major projects with GE, Siemens, UK Power Networks, and international consortia. His research impacts global grid management, including implementations in Columbia, Norway, and Azerbaijan.

Yousef Al-Gumaeiمشاهده پروفایل

استادیار

• Wireless Communications
• Cybersecurity
• Machine Learning
• +۵ مورد دیگر

Yousef Al-Gumaei is an Assistant Professor and Course Leader of Computing at the Global College, Heriot-Watt University in Edinburgh, Scotland. Previously, he held roles including Lecturer in Electrical Engineering at Liverpool John Moores University (2021–2022), Postdoctoral Research Fellow at Northumbria University, and Senior Lecturer at Al-Madinah International University (2016–2019). He earned a Ph.D. in Electrical Engineering from the University of Malaya (2017), an M.Eng.Sc. (2010), and a B.Sc. in Electrical Engineering from IBB University, Yemen (2003). His research focuses on wireless communication systems, cybersecurity, machine learning applications, IoT networks, and 5G/6G technologies. Key areas include power control algorithms, DDoS attack detection, social media analytics for public health, and distributed data mining. He has contributed to advancements in sensor network optimization, metamaterial antennas for THz applications, and energy-efficient EV charging infrastructure. Al-Gumaei has authored or co-authored over 25 publications, including books and journal articles. His work aligns with UN Sustainable Development Goals, particularly in innovation and infrastructure (SDG 9) and industry, innovation, and infrastructure (SDG 9). He teaches courses in Computing and Physics at Heriot-Watt University.

Oleksiy Klymenkoمشاهده پروفایل

مدرس ارشد

• Model-Based Process Design
• Mathematical Modelling in Natural Sciences
• Uncertainty Quantification
• +۳ مورد دیگر

Dr. Oleksiy Klymenko is a Senior Lecturer in Chemical Process Engineering at the University of Surrey, affiliated with the School of Chemistry and Chemical Engineering and the Institute for Sustainability. He holds a DPhil and specializes in model-based process design, mathematical modeling, and uncertainty quantification. Research Interests: Model-based design and optimization of process systems Mathematical modeling in natural and life sciences Uncertainty quantification, particularly global sensitivity analysis Teaching: Module leader for three M-level modules: ENGM071 Process and Energy Integration (MSc) ENGM214 Process Modelling and Simulation (MSc/Year 4 MEng) ENGM256 Technology, Business and Research Seminars (MSc/Year 4 MEng) Contributes to a Year 2 BEng/MEng module. Research Trends: Publications focus on antimicrobial technologies, energy systems optimization, and electrochemical simulations. Recent work includes 3D modeling of microbial dynamics, sustainable energy design, and the development of tools like KISSA software for electrochemical analysis. Advising & Grants: No explicit student advisees or grant details provided in texts. Research collaborations likely underpin his work in interdisciplinary areas like food safety and energy systems. Labs/Teams: Part of the Institute for Sustainability at Surrey, collaborating on projects aligning with sustainable development goals, particularly in energy and food systems.

Dennice F. Gaymeمشاهده پروفایل

دانشیار

• Wall-Bounded Turbulent Flow
• Wind Farm Modeling and Control
• Grid Integration of Renewable Energy
• +۳ مورد دیگر

Roles and Affiliations: Dennice F. Gayme is an Associate Professor in the Department of Mechanical Engineering at Johns Hopkins University's Whiting School of Engineering. She holds secondary appointments in Electrical and Computer Engineering and Environmental Health Engineering. She serves as a member of the Ralph O’Connor Sustainable Energy Institute (ROSEI) leadership council and is the faculty advisor for the Society of Women Engineers (SWE) and Hopkins Students Wind Energy Team (HSWET). Education: Bachelor’s in Mechanical Engineering and Society, McMaster University (1997) MS in Mechanical Engineering, UC Berkeley (1998) PhD in Control and Dynamical Systems, Caltech (2010) Postdoctoral Fellow in Computing and Mathematical Sciences, Caltech (2010–2012) Research Interests: Her work focuses on modeling, analysis, and control of large-scale networked systems in applications such as wall-bounded turbulent flows, wind farms, and power grids. Key areas include: Control systems for renewable energy integration Wake dynamics and wind farm optimization Fluid-structure interactions and turbulence Networked dynamical systems and distributed control Her lab employs computational methods from fluid mechanics, applied mathematics, and optimization. Recent Research Trends: Articles emphasize interdisciplinary approaches combining turbulence modeling, wind energy systems, and control theory. Key themes include wake steering optimization, offshore wind farm dynamics, and turbulence control using riblet surfaces. Recent work also explores climate resilience in energy systems and market mechanisms for renewable integration. Awards and Recognition: NSF CAREER Award (2017) ONR Young Investigator Program Award (2017) JHU Discovery Awards (2019, 2022, 2024) IEEE Senior Member and SIAM/APS/ASME Fellow Advising and Grants: Advised over 10 PhD students, including Carl Shapiro, Ismail Hameduddin, and Genevieve Starke. Secured grants from NSF, ONR, and JHU. Her team developed the JHTDB-wind database for wind farm research. Labs and Collaborations: Leads the Networked and Spatially Distributed Systems Research Group. Collaborates with institutions like Portland State University on offshore wind potential. Serves on editorial boards for Physical Review Fluids and Annual Review of Fluid Mechanics .

Ming Xiaoمشاهده پروفایل

دانشیار

• Wireless Communications
• Network Coding
• Machine Learning
• +۱۰ مورد دیگر

Ming Xiao is an Associate Professor in the Division of Information Science and Engineering at KTH Royal Institute of Technology's School of Electrical Engineering and Computer Science (EECS). He is affiliated with the Digital Futures Faculty and leads research in wireless communications, machine learning, and network coding. His work focuses on 6G networks, distributed learning, and secure communications. Affiliations: KTH EECS, Digital Futures, Swedish Research Council, EU Horizon Europe projects Roles: Editor for IEEE Transactions on Wireless Communications, TPC Co-Chair for VTC Fall Research Interests: Dr. Xiao's expertise spans wireless communication systems (e.g., mmWave, NOMA), network coding, machine learning applications in communications, and energy-efficient distributed systems. He has pioneered work on intelligent reconfigurable surfaces (RIS), federated learning in edge computing, and integrated sensing-communications (ISAC). Projects: Ongoing EU-funded projects include ASCENT (autonomous vehicular networks) and COVER (unmanned aerial vehicles for emergency response). Past projects include 6G channel coding and intelligent energy management in smart communities. Grants: Over 12 active grants from VR, EU Horizon Europe, FORMAS, STINT, and VINNOVA Awards: IEEE Vehicular Technologies Society Best Paper Award (2023), World Top 2% Researcher (2020–2023), Highly Cited Researcher in Computer Science/Engineering. Labs/Teams: Leads the KTH Digital Futures initiative, collaborates with RISE Research Institutes, and manages a team of 12 PhD students/postdocs focusing on 6G, distributed ML, and secure IoT.

Amy Babayمشاهده پروفایل

استادیار

• Distributed Systems
• Networking
• Resilient Systems
• +۳ مورد دیگر

Dr. Amy Babay is an Assistant Professor at the University of Pittsburgh’s School of Computing and Information, with joint appointments in the Department of Informatics and Networked Systems and the Department of Computer Science. She holds a PhD (2018) and MSE (2014) in Computer Science from Johns Hopkins University, along with a BA in Cognitive Science (2012). Her research focuses on distributed systems and networking, emphasizing resilient critical infrastructure and next-generation internet services. Notable projects include the Spire intrusion-tolerant SCADA system for power grids and structured overlay networks for low-latency applications. Her work has been recognized with awards, including the Best Paper at IEEE ICDCS 2017. Babay’s research also explores technology’s role in community resilience and cybersecurity challenges in smart cities. She teaches advanced distributed systems, networks, and programming courses. Key contributions include the Spines overlay platform and Prime replication engine. Her lab, RSSLab, actively develops solutions for resilient infrastructure and cybersecurity threats. Publications span topics like intrusion-tolerant systems, epidemic modeling, and network resilience. She collaborates with institutions like Sandia National Labs and Hawaiian Electric Company. Contact: babay@pitt.edu, located at 701B Information Sciences Building.

• Energy Efficiency
• Demand Side Management
• Industrial Energy Systems
• +۳ مورد دیگر

Dominic O'Sullivan is a Senior Lecturer in the Department of Civil & Environmental Engineering at University College Cork (UCC), appointed since 2008. He leads the Intelligent Efficiency Research Group (IERG), focusing on energy efficiency technologies and IT-driven solutions for industrial and building systems. His research integrates smart analytics, renewable energy systems, and HVAC optimization to advance sustainable engineering practices. Education includes a BEng in Civil Engineering (1998), MEngSc in Building Appraisal (2000), and PhD in Building Performance (2005), all from UCC. He has held roles in energy consultancy before academia. Research interests span energy efficiency retrofitting, demand-side management, and Industry 4.0 applications. Notable projects include the Carbon Neutral Building Project, I2E2 initiatives, and EU-funded projects like BIM4EEB and DENIM. Over €4.5M in research funding secured, with 50+ journal publications and top citations in Intelligent Efficiency. Awards include UCC ICT Invention of the Year (2012) and SEAI Energy Team of the Year (2022). He advises on national energy standards and collaborates with industries like Intel and DePuy. Academic roles include roles in UCC committees, editorial board memberships, and supervision of 15+ PhD/MSc students. Teaching focuses on energy systems, building services, and data analytics for engineers. Current projects emphasize carbon neutrality, proactive maintenance frameworks, and smart manufacturing solutions.

• Power Electronics
• DC-DC Converters
• Photovoltaic Systems
• +۷ مورد دیگر

Clara Marina Sanz Garcia is an Associate Professor in the Electronic Technology Department at Charles III University of Madrid (UC3M). She is a member of the Electronic Power Systems Group (GSEP) and teaches courses in Electronics, Mechanical Engineering, and Telecommunications. Her research focuses on power electronics with applications in photovoltaic systems, electric vehicles, and aerospace power systems. Dr. Sanz Garcia's research spans multiple critical areas of power electronics including DC-DC converters, photovoltaic systems integration, solid-state power controllers, and impedance modeling. Her work demonstrates particular expertise in converter topologies for renewable energy applications, with numerous publications on specialized converter designs like the AFZ converter, autotransformer forward-flyback converter, and Buck-Boost Modified Series Forward converter. She also has significant contributions in hardware-in-the-loop simulation techniques and digital control implementations using FPGAs. Her recent publications reveal a strong trend toward practical implementation of power electronic systems with a focus on stability analysis, control strategies, and system integration. The research consistently bridges theoretical modeling with practical applications, particularly in renewable energy systems and transportation electrification. Many of her papers address the challenges of integrating power electronic converters into larger systems, with special attention to stability issues that arise in cascaded converter architectures. Convertidor CC-CC reductor y elevador, método de conversión CC-CC, y planta fotovoltaica que incorpora dicho convertidor (2019) Active control procedures for the connection of very capacitive loads using SSPCs (2017) Active control procedures for the connection of very capacitive loads using SSPCs (2014) Método y dispositivo de transformación de corriente continua en corriente alterna (2014) Método y sistema de alimentación de una carga constituida por una pluralidad de cargas elementales, en particular de LED (2013) Dr. Sanz Garcia has supervised at least one doctoral thesis on novel converter families for photovoltaic applications and has been principal investigator on multiple research projects including 'Estrategias de modelado y control para la estabilización de la InterCONEXión de convertidos electrónicos de POTencia' (2018-2021) and 'SMARTMOD-Habilitación de funciones inteligentes en convertidores de potencia modulares para la movilidad eléctrica' (2022-2025). She has secured funding from diverse sources including the Ministry of Economy, European Commission, and industry partners like Siemens Healthcare. She leads research within the Electronic Power Systems Group (GSEP), focusing on power converter design, stability analysis, and applications in renewable energy systems and transportation electrification. Her team works on both theoretical modeling and practical implementation, with strong connections to industry applications in aerospace, railway systems, and medical equipment.

• Database Systems
• Mobile and Pervasive Data Management
• Distributed Computing
• +۵ مورد دیگر

Panos K. Chrysanthis is a Professor of Computer Science at the University of Pittsburgh and an adjunct Professor at Carnegie-Mellon University and the University of Cyprus. He holds a BS in Physics with a Computer Science concentration from the University of Athens, Greece, and MS and PhD degrees in Computer and Information Sciences from the University of Massachusetts Amherst. He has been affiliated with the University of Pittsburgh since 1991, serving as Director of the Advanced Data Management Technologies (ADMT) Lab. His research focuses on database systems, mobile and pervasive data management, distributed computing, and real-time systems, with recent emphasis on data streams and energy-efficient data management for IoT and sensor networks. Chrysanthis has authored over 100 peer-reviewed publications, including a book on transaction processing and consistency in distributed databases. He has received the NSF CAREER Award (1995) and the University of Pittsburgh's Provost Award for Excellence in Mentoring (2015). He has held editorial roles at the VLDB Journal, IEEE TKDE, and DAPD, and has organized major conferences like ICDE and MDM. His work bridges theoretical database research with practical applications in urban informatics, healthcare, and sustainability. Chrysanthis has advised numerous students, contributed to grants focused on big data and healthcare analytics, and co-developed tools like the ADMT Lab's experimental platforms for urban mobility and congestion. He is a Senior Member of IEEE and an ACM Distinguished Scientist.

• Machine Learning
• Stochastic Optimization
• Networked Systems
• +۴ مورد دیگر

Juan Bazerque Giusto is a Visiting Assistant Professor at the Department of Electrical and Computer Engineering, University of Pittsburgh, within the Swanson School of Engineering. He holds a B.Sc. in Electrical Engineering from Universidad de la República (Uruguay), and M.Sc. and Ph.D. degrees from the University of Minnesota. His research focuses on machine learning, stochastic optimization, and networked systems, with emphasis on reinforcement learning, swarm robotics, and power systems optimization. Education: B.Sc., Electrical Engineering, Universidad de la República, 2003 M.Sc., Electrical and Computer Engineering, University of Minnesota, 2010 Ph.D., Electrical and Computer Engineering, University of Minnesota, 2013 His work bridges theoretical advancements in optimization and signal processing with practical applications in robotics, energy systems, and wireless networks. Notable contributions include multiagent systems for mobile infrastructure, safe reinforcement learning algorithms, and sparse kernel-based methods for signal recovery. Publications: Over 15 peer-reviewed articles in IEEE Transactions and top conferences, emphasizing interdisciplinary research in reinforcement learning, distributed optimization, and cognitive networks. Recent work explores networked robotics and energy-efficient datacenter management. Awards: University of Minnesota Master Thesis Award (2009-2010) Best Paper Award at ICCRON 2007 Professional Experience: Previously served as Assistant Professor at Universidad de la República (Uruguay) before relocating to the U.S. in 2022.

Siris Vasiliosمشاهده پروفایل

استاد

• Resource Management in Networks
• Distributed Ledger Technologies (DLTs)
• Blockchains and IoT Security
• +۳ مورد دیگر

Professor Siris Vasilios holds the position of full Professor at the Department of Informatics, Athens University of Economics and Business (AUEB). Previously, he served as Assistant and Associate Professor at AUEB (2009–2020) and the University of Crete (2002–2009). His expertise spans resource management in networks, blockchain-based IoT security, and future communication systems. He has published over 150 papers in top venues like IEEE INFOCOM and ACM Mobicom, and holds three patents in wireless resource management. Education: Diploma in Physics (1990), National and Kapodistrian University of Athens M.S. in Computer Science (1992), Northeastern University, Boston, USA Ph.D. in Computer Science (1998), University of Crete Research Interests: His work focuses on trusted communication in IoT , leveraging blockchain technologies for secure systems. Key areas include distributed ledger applications, energy-efficient network protocols, and satellite-terrestrial integration. He emphasizes combining theoretical methods with practical system implementations. Awards & Recognition: He has coordinated EU-funded projects (e.g., SOFIE) and served as Technical Program Chair for IEEE WoWMoM 2018 and IQ2S 2015. His research has been recognized through grants from Greek governmental and industry partners. Grants & Projects: Principal Investigator for multiple EU research projects Lead on Greek national and industry-funded initiatives Contributed to the SOFIE project addressing IoT security via interledger technologies Labs & Teams: Active in the Department of Informatics' research groups, focusing on experimental systems like Dedalus for wireless maritime networking and blockchain-based IoT prototypes.

Arshad Salemaمشاهده پروفایل

دانشیار

• Clean Energy Technologies
• Biomass Gasification
• Microwave Processing
• +۷ مورد دیگر

Dr. Arshad Salema is an Associate Professor and Course Director (Master of Applied Engineering) in the Mechanical Engineering Department at Monash University's School of Engineering. His research focuses on clean energy technologies, biomass gasification, microwave processing, and advanced materials like MXene. He has led projects such as 'Microwave Sterilization of Palm Fresh Fruits' and 'Biomass Gasification for Syngas Production.' Dr. Salema holds a PhD from Universiti Teknologi Malaysia (UTM) and completed a postdoc at the University of New Brunswick, Canada. His expertise spans renewable energy systems, energy efficiency, and sustainable materials. Awards include the 2023 PVC’s Excellence in Research Engagement and the School of Engineering Research Award 2023. He teaches courses like Energy Efficiency and Sustainable Engineering, and advises students on graduate research. Dr. Salema collaborates with industry and government, advancing sustainable engineering solutions through initiatives like solar PV installations and waste-to-energy projects. Key projects include the development of MXene-biochar composites and integrating microwave technology for biomass processing. His work aligns with UN SDGs, emphasizing sustainability and clean energy innovation.