جست‌وجوی استاد و پژوهشگر

• Wireless Communication
• Wireless Sensor Networks
• Network Coding
• +۳ مورد دیگر

Nadieh Moghadam is an Assistant Professor of Electrical Engineering at the University of San Diego (USD), affiliated with the College of Engineering. She holds a PhD from the University of Louisville (2017), an MS from Iran University of Science and Technology, and a BS from K.N. Toosi University of Technology. Her research focuses on wireless communication, network coding, sensor networks, and embedded systems. She has authored over 15 publications and served as a reviewer for IEEE Transactions journals since 2015. Education : PhD in Electrical Engineering, University of Louisville (2017) MS in Electrical Engineering, Iran University of Science and Technology BS in Electrical Engineering, K.N. Toosi University of Technology (Iran) Research Interests : Dr. Moghadam advances wireless communication systems through innovations in network coding, optimization algorithms, and embedded system design. Her work addresses challenges in multicast efficiency, queue stability, and energy conservation in IoT and sensor networks. She also explores blockchain applications in modern wireless standards like IEEE 802.11ax. Awards : Graduate Dean’s Citation Award (2017) University Fellowship (PhD period) Theobald Scholarship (PhD period) Industry Experience : She co-founded Ivani, a startup developing IoT wireless sensing systems using Bluetooth Low Energy (BLE) and Zigbee protocols. Her team designed low-power occupancy sensing solutions leveraging RF environments.

• Hardware-Software Systems
• Embedded Systems
• Intelligent Robotic Environments
• +۵ مورد دیگر

Dr. Alexandru Iovanovici is an Associate Professor at the Department of Computer Science, Faculty of Automatic Control and Computers, Politehnica University of Timisoara. His research focuses on hardware-software systems, embedded systems, intelligent robotic environments, and complex networks analysis with applications in urban traffic optimization and sensor networks. He holds a Dr. Eng. degree and has received Merit Diplomas in 2021 and 2023. His academic work combines theoretical network science with practical engineering solutions. Notable projects include the INCEPTION initiative exploring IoT and complex networks for COPD management, and TACTICS framework for adaptive traffic control systems. His research bridges computer science, transportation engineering, and biomedical informatics. Education: Dr. Eng. in Computer Science (degree institution unspecified) Key Skills: Network motif analysis, metaheuristic optimization, real-time traffic modeling Research trends show strong emphasis on applying complex networks theory to urban systems: 60% of recent publications (2019-2022) address traffic infrastructure optimization, while 30% explore biomedical applications like drug interaction networks. Recent work demonstrates cross-disciplinary innovation, combining machine learning with embedded systems for wearable healthcare monitoring. Awards: 2023 Merit Diploma for academic contributions, 2021 Merit Diploma Events Organized: 2024 Workshop on Secure Real-Time Data Systems, 2025 IEEE Symposium on Applied Computational Intelligence Active in both academic and applied research, Dr. Iovanovici leads projects involving EU economic dynamics modeling and pandemic-era mobility studies. His lab develops high-availability monitoring systems for sleep disorders and maintains a spatial analysis framework for traffic data integration.

• Operations Research
• Optimization
• Game Theory
• +۳ مورد دیگر

V.M. Timmermans is a Lecturer in Quantitative Economics at Maastricht University's School of Business and Economics, specializing in Operations Research. His work bridges optimization theory, game theory, and transportation systems. He holds a Doctoral Thesis from Maastricht University (2019) titled Uniqueness and computation of equilibria in resource allocation games . Research interests focus on equilibrium computation in resource allocation games, congestion game analysis, and optimization of transportation networks. His recent work explores collaborative strategies in inland waterway efficiency, emphasizing fuel optimization and skipper collaboration. Publications span journals like European Journal of Operational Research and conferences such as IPCO and MAPSP. His work integrates algorithmic design with real-world logistics challenges, demonstrating expertise in both theoretical and applied operations research.

Francis Yanمشاهده پروفایل

استادیار

• Networked Systems
• Computer Networks
• Machine Learning for Systems
• +۳ مورد دیگر

Francis Yan is an Assistant Professor of Computer Science at the University of Illinois Urbana-Champaign (UIUC), affiliated with the Siebel School of Computing and Data Science and the Electrical & Computer Engineering department. He leads the Illinois Networked Systems and AI (NSAI) Lab, focusing on integrating practical machine learning into networked systems. Previously, he was a Senior Researcher at Microsoft Research Redmond, working on systems and networking research. His work emphasizes deployable ML solutions, validated through large-scale platforms like Puffer and Pantheon. Education: Ph.D. in Computer Science (Stanford University, 2020); B.S. in Computer Science (Tsinghua University, 2015) and B.A. in Economics (Tsinghua University, 2015). Research Interests: Networked systems, machine learning for systems and networking, intelligent video systems, and cloud resource management. His lab develops frameworks like DeDe, Mowgli, and Autothrottle to enhance system performance and robustness. Awards: USENIX NSDI Outstanding Paper Award (2024), Applied Networking Research Prize (2021), and USENIX ATC Best Paper Award (2018). He serves on program committees for NSDI, SIGCOMM, and ACM workshops. Grants & Service: Co-chair of SIGCOMM 2024 Artifact Evaluation. Active in open-source projects and research platforms supporting reproducible networking experiments. Labs/Teams: Directs the NSAI Lab, collaborating on projects such as Puffer (400k-user video service), Teal (WAN optimization), and Genet (curriculum learning for networking).

Kristjon Cikoمشاهده پروفایل

پژوهشگر ارشد

• Network Architecture
• Distributed Systems
• Recursive InterNetwork Architecture (RINA)
• +۳ مورد دیگر

Kristjon Ciko is a Research Fellow at the University of Oslo's Faculty of Mathematics and Natural Sciences, affiliated with the Department of Informatics under the Networks and Distributed Systems group. His work focuses on advancing network architectures and distributed systems. Research Interests: Ciko's research spans network architecture, particularly Recursive InterNetwork Architecture (RINA), congestion control mechanisms, and energy-efficient computing. His studies address challenges in next-generation network design, throughput optimization, and sustainable computing systems. Publications: Recent work includes innovations in energy efficiency for throughput computing, software-based server energy management, and congestion control solutions for datacenter networks. His research bridges theoretical advancements with practical implementations.

Michael Caramanisمشاهده پروفایل

استاد

• Power Systems
• Smart Grid
• Energy Markets
• +۴ مورد دیگر

Michael Caramanis is a Professor of Mechanical Engineering and Systems Engineering at Boston University's College of Engineering. He holds affiliations with the Energy, Sustainability & Climate initiative. His research focuses on power markets, microgrid cyber capabilities, and stochastic production systems. Notably, he served on the Greek National Energy Council (1976-79), MIT Energy Laboratory (1979-82), and chaired Greece's Energy Regulatory Authority (2005-recently). His work emphasizes smart grid development, decision support algorithms, and integrating sustainable energy technologies like wind, storage, and EVs. Education: PhD in Engineering/Decision and Control from Harvard University. Additional affiliations include Mechanical Engineering and Systems Engineering departments at BU. Research Interests: Caramanis explores cyber-physical-energy systems, real-time market mechanisms, and load management. His recent work addresses distribution network retail markets, topology control algorithms (TCA), and the economic dispatch of distributed energy resources. Key areas include locational marginal pricing, demand response strategies, and grid resilience. Publications: Over 100 peer-reviewed articles and co-authorship of Spot Pricing of Electricity (1988). Recent trends focus on smart grid algorithms, market design innovations, and integrating renewable energy into power systems. His research bridges optimization theory with practical grid challenges. Grants & Projects: Funded by NSF, EPRI, NYSERDA, and industry. Projects include topology control for congestion mitigation, data center participation in markets, and distributed energy resource coordination. His work has been applied in PJM grid simulations and real-world distribution networks. Labs & Teams: Leads research teams advancing smart grid controls and market mechanisms. Collaborates on projects like the AitF: Collaborative Research initiative and ETEM-SG: Smart Energy Systems . Active in developing policy frameworks for competitive electricity markets.

• Computer Vision
• Networking Protocols
• Machine Learning
• +۳ مورد دیگر

Maria Ito is a Visiting Professor at Queen Mary University of London's School of Electronic Engineering and Computer Science, focusing on interdisciplinary research at the intersection of computer vision, networking protocols, and adaptive media streaming. Her work emphasizes video stabilization techniques, network performance optimization, and machine learning-driven solutions for real-time media delivery systems. Her research interests span video processing, deep learning applications in computer vision, and the design of efficient adaptive streaming protocols. Notable contributions include frameworks for distortion-free video stabilization and performance evaluations of QUIC vs. TCP protocols. Publications highlight trends in combining control theory with adaptive streaming systems and developing benchmark datasets for deep learning models. While no specific awards or grants are listed, her work demonstrates significant contributions to both theoretical and applied aspects of media streaming technologies. Advising and lab affiliations are not explicitly detailed in the provided materials.

Richard Harveyمشاهده پروفایل

استاد بالینی

• Rhinology
• Otolaryngology
• Skull Base Surgery
• +۳ مورد دیگر

Richard Harvey is a Clinical Professor at Macquarie University and the University of New South Wales (UNSW), holding the position of Program Head of Rhinology & Skull Base Surgery at UNSW's Applied Medical Research Center. He specializes in rhinology, endoscopic sinus and skull base surgery, and allergic rhinosinusitis management. With over 300 publications, he is a globally recognized leader in otolaryngology, ranked among Australia's top researchers in the field. His research focuses on chronic rhinosinusitis, nasal polyps, and endoscopic surgical techniques. He contributes to international journals as an editor and serves on the executive boards of societies like the Australian & New Zealand Skull Base Society. Harvey has received prestigious awards, including the ESR Hughes Award (2023) and the Society Medal for Distinguished Contribution (2018). He leads the Visualising Voice and Speech (VisVoiS) project, bridging experimental and clinical research. His clinical practice combines surgery with education, training surgeons globally and running annual courses in Sydney.

Johan Morrenمشاهده پروفایل

استادیار

• Distributed Generation
• Smart Grids
• Power System Protection
• +۲ مورد دیگر

Dr. Johan Morren is a part-time Assistant Professor in Electrical Energy Systems at Eindhoven University of Technology (TU/e), concurrently serving as Senior System Responsible at Enexis Netbeheer. His research focuses on smart grid technologies for distribution networks, including distributed generation integration and grid automation. Education: PhD and MSc in Electrical Power Engineering from Delft University of Technology. Research: Develops solutions for network planning, congestion management, and renewable integration using optimization methods and real-time control strategies. Current projects examine grid flexibility aggregation, power-to-gas coordination, and thermal rating of underground cables. Professional Experience: Combines academic research with practical grid operation expertise from Dutch distribution system operator Enexis, focusing on implementing smart grid solutions in real-world networks.

Rafael Bailoمشاهده پروفایل

استادیار

• Numerical Analysis
• Partial Differential Equations (PDEs)
• Computational Science
• +۳ مورد دیگر

Rafael Bailo is an Assistant Professor of Mathematics at the Eindhoven University of Technology , affiliated with the Centre for Analysis, Scientific Computing and Applications . His primary research focuses on the numerical analysis of kinetic equations and partial differential equations (PDEs), with additional interests in collective dynamics, self-organization, and agent-based modeling. He teaches courses such as Advanced Calculus I and Continuous Optimization . Department: Mathematics and Computer Science His research explores computational methods for complex systems, including uncertainty quantification in kinetic models, pedestrian dynamics with congestion effects, and consensus-based particle methods. Recent work emphasizes the development of numerical schemes for fractional diffusion, plasma physics simulations, and aggregation-diffusion equations. He collaborates internationally on topics like particle-in-cell methods and software tools for interacting particle systems (e.g., the CBX package). Key trends in his publications include advancing finite-volume schemes for nonlinear PDEs, analyzing structural properties of kinetic equations, and bridging theoretical analysis with computational implementation. His work often addresses challenges in preserving physical properties (e.g., positivity, energy dissipation) in numerical solutions. Bailo advises students on topics related to PDEs and computational methods but specific supervisee names are not listed. His contributions span applied mathematics, computational physics, and interdisciplinary modeling, with applications in plasma dynamics, crowd movement, and materials science.

Lin Wangمشاهده پروفایل

استادیار

• Networked Systems
• Edge Computing
• Cloud Computing
• +۵ مورد دیگر

Lin Wang is an Assistant Professor at the Department of Computer Science, Vrije Universiteit Amsterdam, and an Adjunct Professor at TU Darmstadt. His research focuses on networked systems, edge computing, cloud computing, and optimizing computer systems for applications like augmented reality. He holds a PhD from Chinese Academy of Sciences and has postdoctoral experience at SnT Luxembourg. His work contributes to UN Sustainable Development Goals related to innovation and infrastructure. Education: PhD in Computer Science (ICT, CAS), Postdoc at SnT Luxembourg Previous Roles: Head of Smart Urban Networks group at TU Darmstadt's TK Lab (2016-2018) Research interests include edge computing, in-network processing, novel network protocols, and energy efficiency. Recent work addresses latency in edge networks, IoT synchronization, and congestion mitigation in data centers. Supervised 2 PhD theses and collaborates internationally. Active in labs like the Telecooperation (TK) Lab. No ancillary activities declared.

• Control Theory
• Fault Detection
• State Estimation
• +۶ مورد دیگر

Tan Chee Pin is an Associate Professor and Head of the Mechatronics Engineering program at Monash University Malaysia. His research focuses on observer design for system state estimation, with applications in robotics, traffic management, and energy systems. He has published extensively in top journals like IEEE Transactions on Automation Science and Engineering, and secured RM1.5m in research funding. His teaching emphasizes student-centric approaches, earning him internal awards and a national educator award nomination. Research interests include model-based observer configurations for minimizing sensor usage, condition monitoring, and predictive maintenance. Applications span soft robotics, traffic congestion reduction, and energy optimization. He collaborates on projects like IoT-based predictive maintenance systems and solar technology for Orang Asli communities. Editorial roles include associate editorships at IEEE Transactions on Cybernetics and the Journal of the Franklin Institute. Awards include finalist status for the 2018 National Outstanding Educator’s Award. Advising includes supervising 7 PhD completions and 13 current students. Projects include smart drone trash monitoring and control systems for soft robots using few-shot learning.

Y. Richard Yangمشاهده پروفایل

استاد

• Computer Networks
• Wireless Networking
• Mobile Computing
• +۲ مورد دیگر

Y. Richard Yang is a Professor of Computer Science and Electrical Engineering at Yale University, where he leads research in computer networks, wireless systems, and distributed computing. He is a core member of Yale's Computer Systems Lab and has pioneered Internet standards like ALTO (RFCs 7285/9439/9569). His work on massive MIMO (Argos) laid foundations for 5G cellular networks. Education: Ph.D. in Computer Science, University of Texas at Austin (2001) M.S. in Computer Science, University of Texas at Austin (1998) B.E. in Computer Science, Tsinghua University (1993) Research Interests: Yang's work spans network architecture (ALTO/P4P), wireless innovations (beamforming, superposition coding), and network verification (Flash, Trident). His recent focus includes deep application-network integration and scalable data plane verification for cloud/CERN-scale systems. Publication Trends: Recent articles emphasize SDN programmability (Maple, Trident), Internet-scale optimization (ALTO extensions), and high-speed verification (Flash). His works consistently bridge theory (game-theoretic models) with practical deployment (RFCs, CERN integration). Awards: ACM SIGMobile Test of Time Award (2022) ACM SIGCOMM NAI Best Paper Award (2022) NSF CAREER Award Facebook/Google/Microsoft Faculty Research Awards Students & Funding: Advised recent graduates including Jackie Dong and Lily Zhou. Secured grants from U.S. NSF, Army, U.K. MoD, Facebook, Google, and Microsoft. Labs: Directs projects in the Computer Systems Lab at Yale , collaborating with CERN, Microsoft Research, and Tsinghua/Peking Universities.

Ehsan Naderiمشاهده پروفایل

استادیار

• Cybersecurity in Power Systems
• Renewable Energy Integration
• Optimization Methods in Power Systems
• +۳ مورد دیگر

Dr. Ehsan Naderi is an Assistant Professor of Electrical Engineering and Interim Director of the Department of Electrical Engineering at Arkansas State University (A-State), housed within the College of Engineering and Computer Science. He holds a Ph.D. in Electrical and Computer Engineering from Southern Illinois University (2023) and joined A-State in August 2023. His research focuses on enhancing smart grid security through advanced machine learning and optimization methods, particularly addressing cybersecurity threats in power systems integrating renewable energy and transportation infrastructures. He is an active member of multiple IEEE societies, including PES, IES, PELS, and IAS, and serves as an Associate Editor for Evolutionary Intelligence and Review Editor for Grid Efficiency . Education: Ph.D., Electrical and Computer Engineering, Southern Illinois University, Carbondale, IL, USA (2023) Research Interests: Applying optimization methods and fuzzy inference systems to modern power systems Cybersecurity of smart microgrids with renewable energy (e.g., wind and PV) Integration of clean energy and transportation systems into smart grids His work emphasizes experimental validation through lab-scale microgrid testing and hardware-in-the-loop systems. Publications: Over 30 peer-reviewed articles since 2021, focusing on cybersecurity in power systems, renewable integration, and smart grid resilience. Recent trends include addressing false data injection attacks targeting distribution systems, electric vehicles, and transformer vulnerabilities. Awards: 2025 A-State Faculty Excellence Award (Emerging Scholar) Multiple Best Paper Awards at IEEE conferences (2021–2024) Dissertation Research Fellowship (SIU, 2020–2023) Grants & Advising: While specific grants are not detailed, his research has been supported by experimental infrastructure development. He actively mentors students in cybersecurity and renewable energy projects. His editorial and reviewing roles reflect contributions to advancing peer-reviewed scholarship in energy systems. Labs & Teams: Leads the Electrical Engineering department’s research in smart grid security and collaborates with IEEE committees on cybersecurity standards and grid modernization.

• Information Acquisition
• Mechanism Design
• Stochastic Orders
• +۳ مورد دیگر

Xiaosheng Mu is an Associate Professor in the Department of Economics at Princeton University. He previously held positions as an Assistant Professor of Economics at Columbia University and a post-doctoral researcher at the Cowles Foundation at Yale University. He earned his Ph.D. in Economics from Harvard University, advised by Drew Fudenberg, Eric Maskin, and Tomasz Strzalecki. His research focuses on information acquisition, mechanism design, stochastic orders, and their applications to decision making. Key contributions include work on pricing strategies under informational robustness, privacy-preserving auctions, and market dynamics on global e-commerce platforms. His work bridges theoretical economics with practical applications in algorithm design, privacy mechanisms, and behavioral analysis. Xiaosheng has published in top journals such as Econometrica, the Quarterly Journal of Economics, and the Journal of Political Economy. Notable publications include 'Monotone Additive Statistics' (Econometrica, 2024) and 'Algorithmic Design: A Fairness-Accuracy Frontier' (Journal of Political Economy, 2024). His research often employs advanced mathematical techniques from probability theory, game theory, and optimization. He has collaborated extensively with scholars such as Annie Liang, Vasilis Syrgkanis, and Luciano Pomatto. Current research projects explore information friction in digital markets and the design of privacy-preserving economic mechanisms. His work consistently addresses foundational questions in economics while maintaining relevance to modern technological challenges.