جست‌وجوی استاد و پژوهشگر

• Cyber-physical system security
• Smart Grid security
• Networked systems algorithms
• +۳ مورد دیگر

Binbin Chen is an Associate Professor in Information Systems Technology and Design at Singapore University of Technology and Design (SUTD). His research focuses on enhancing the security and efficiency of interconnected systems like cyber-physical systems and IoT networks. Prior to his current position, he earned a PhD from National University of Singapore (NUS) and a Bachelor's from Peking University, both in Computer Science. Key research areas include smart grid security, networked systems algorithms, and safety-security co-analysis. Notable contributions include work on RFID protocols, fault-tolerant distributed systems, and secure substation control mechanisms. His research has been funded by Singapore's Energy Market Authority (EMA), A*STAR, and the Singapore Cybersecurity Consortium. Publications highlight advancements in secure substation command delaying, privacy-preserving electricity data sharing, and fault-tolerant aggregate function computation. He leads development of tools like CyberSAGE for cyber-physical system security assessment and SoftGrid for substation cybersecurity testing. Received Best Paper Award at ACM SIGCOMM 2010 Contributed to over 30 peer-reviewed journal/conference publications Active in professional service including journal reviewing and conference organization Current research emphasizes integrating security and safety engineering principles in critical infrastructure systems, with particular focus on railway and smart grid resilience.

Kirill Morozovمشاهده پروفایل

دانشیار

• Cryptography
• Cybersecurity
• Post-quantum Cryptography
• +۹ مورد دیگر

Kirill Morozov is an Associate Professor at the University of North Texas within the College of Engineering and the Department of Computer Science and Engineering . His research focuses on Cryptography and Cybersecurity , particularly on code-based protocols, post-quantum cryptography, and information-theoretic methods. Research interests include cryptographic protocols from coding and correlated randomness, covering post-quantum cryptography, zero-knowledge systems, secret sharing, and physical-layer key agreement. He has taught courses like Introduction to Computer Security and Applications of Cryptography at UNT since 2018, and previously at Tokyo Institute of Technology (2017) and Kyushu University (2011–2015). His work spans code-based encryption , unconditionally secure protocols , and cloud storage applications , with contributions to zero-knowledge proofs, cheater-identifiable systems, and oblivious transfer over noisy channels. Contact: Kirill.Morozov@unt.edu . No scientific awards explicitly listed. His publications emphasize code-based cryptography , secure computation , and quantum-resistant protocols .

• Porous Media Flow
• Geological Carbon Sequestration
• Subsurface Energy Systems
• +۲ مورد دیگر

Dr. Cheng Chen is Associate Professor and Nariman Farvardin Professor in the Department of Civil, Environmental and Ocean Engineering at Stevens Institute of Technology. He directs the Subsurface Energy, Water and Environmental Systems (SEWES) Lab, focusing on porous media transport phenomena through combined computational and experimental approaches. His NSF and DOE-funded research addresses multiphase flow in geological formations for carbon sequestration, shale energy recovery, and nuclear waste disposal. Recent work integrates machine learning for scale-bridging data assimilation and distributional reinforcement learning for autonomous marine systems. Chen's methodological innovations include lattice Boltzmann simulations for pore-scale analysis and Gaussian process models for uncertainty quantification. Scholarly outputs demonstrate consistent focus on energy-geoscience interfaces, with recent expansion into privacy-preserving federated learning applications for IoT systems. His 2023-2024 publications increasingly address security challenges in distributed computing and adversarial machine learning. Major Recognition: Stanford Top 2% Most Cited Scientist (2023) Nariman Farvardin Endowed Professorship Chen teaches numerical methods in environmental engineering and subsurface flow modeling, maintaining industrial partnerships with Schlumberger, SeaRobotics, and Consolidated Edison. He holds editorial roles for SPE Journal and has authored over 60 peer-reviewed publications.

Alexander Kosovichevمشاهده پروفایل

استاد

• Solar Physics
• Helioseismology
• Solar Activity
• +۴ مورد دیگر

Alexander Kosovichev is a Distinguished Professor of Physics at New Jersey Institute of Technology. He earned his D.Sc. in Astrophysics from St. Petersburg University and specializes in solar physics and helioseismology. His research focuses on solar interior structure, convection zone dynamics, solar-stellar connections, and space weather prediction using advanced helioseismic techniques and computational modeling. He has developed innovative methods for studying solar differential rotation and convection patterns. Professor Kosovichev's recent publications demonstrate extensive work in helioseismology applications, solar convection modeling, and machine learning approaches for space weather forecasting. His research consistently bridges theoretical astrophysics with practical prediction systems. He received the Wempe Prize in Astrophysics (2005) for significant contributions to the field. His laboratory develops computational tools for simulating solar convection and analyzing helioseismic data from space missions like SDO and Kepler.

Shaoquan Jiangمشاهده پروفایل

استادیار

• Network Security
• Blockchain
• Cryptographic Protocols
• +۳ مورد دیگر

Dr. Shaoquan Jiang is an Assistant Professor at the University of Windsor's School of Computer Science. He holds a Ph.D. in Electrical & Computer Engineering from the University of Waterloo (2005). Research interests: His work spans network security architectures, cryptographic protocol design, blockchain implementations, quantum-resistant cryptography, and security education frameworks. Current projects focus on post-quantum security and authentication systems. Teaching: He instructs courses in cryptography, network security, and cyber security fundamentals at undergraduate and graduate levels.

Roman Belavkinمشاهده پروفایل

دانشیار

• Information Theory
• Optimization
• Machine Learning
• +۳ مورد دیگر

Dr. Roman Belavkin is an Associate Professor in Informatics at the Department of Computer Science, Middlesex University, affiliated with the School of Science and Technology. He holds a PhD in Computer Science from the University of Nottingham (1998-2002) and an MSc in Physics from Moscow State University (1988-1994). His research focuses on information theory, optimization, and their applications to machine learning, evolutionary algorithms, and computational biology. He is an affiliated faculty member of the Center for Applied Optimization at the University of Florida and serves on the editorial board of Optimization Letters. His work spans theoretical foundations of information dynamics, mutation rate control in evolutionary systems, and applications to finance and cognitive architectures. Notable contributions include studies on entropy computation, value of information analysis, and neural modeling. He has presented at international conferences such as the Advanced Course on Data Science & Machine Learning (Siena, 2018) and published extensively in top-tier journals. Collaborations include interdisciplinary projects linking information theory with biology, finance, and artificial intelligence. Dr. Belavkin teaches courses in computer science and informatics at both undergraduate and postgraduate levels. His research interests also extend to cybersecurity, including detection of application layer DDoS attacks using clustering and Bayesian methods. He maintains an active personal website detailing his publications, software tools, and academic activities.

Anna Tzanakakiمشاهده پروفایل

دانشیار

• Optical Networking
• 5G/6G Systems
• Cloud-RAN
• +۲ مورد دیگر

Anna Tzanakaki is an Associate Professor at the National and Kapodistrian University of Athens (Physics Department) and Visiting Research Fellow at the University of Bristol. Her research focuses on optical networks supporting 5G/6G systems, converged infrastructures, and network slicing. Key research areas include: Optical-wireless convergence for 5G/6G transport Intent-based network management using AI/ML Techno-economic analysis of network deployments Her extensive publication record (200+ papers) shows consistent focus on optical network design, cloud-RAN architectures, and multi-access edge computing, with recent work emphasizing AI-driven network optimization and integrated sensing-communication systems. As technical coordinator of the EU 5G-PPP project 5G-VICTORI, she drives innovation in railway communications and vertical industry applications.

Myoungkyu Leeمشاهده پروفایل

استادیار

• High-Performance Computing
• Turbulent Flows
• Multiphysics Simulations
• +۳ مورد دیگر

Dr. Myoungkyu Lee is an Assistant Professor in the Department of Mechanical and Aerospace Engineering at the University of Houston (2023–current). Previously, he served as an Assistant Professor at the University of Alabama (2022–2023) and held postdoctoral positions at Sandia National Laboratories (2018–2021) and the Oden Institute of Computational Science and Engineering (2016–2018). His research focuses on high-performance computing, thermal/chemical nonequilibrium flows, and direct numerical simulations of multiphysics turbulent flows. He earned his Ph.D. in Mechanical Engineering from the University of Texas at Austin (2015) and B.S. from Hanyang University (2008). Dr. Lee’s research integrates computational fluid dynamics, turbulence modeling, and high-performance computing to study wall-bounded flows, magnetohydrodynamic effects, and nonequilibrium phenomena. His work emphasizes spectral analysis, data-driven modeling, and advanced numerical methods for resolving complex fluid behaviors. Notable contributions include studies on Reynolds stress scaling, wall-pressure correlations, and stochastic forcing in turbulent flows. His awards include the Early Career Presenter Fellowship (2021) and a Best Student Paper Finalist at SuperComputing SC13 (2013). He has published extensively in journals like Journal of Fluid Mechanics and Physical Review Fluids , with over 30 peer-reviewed articles. His teaching includes courses on fluid dynamics and computational methods. Dr. Lee’s academic trajectory reflects a strong dedication to advancing computational turbulence research and fostering interdisciplinary collaborations in engineering and applied mathematics.

Bo Zhaoمشاهده پروفایل

استادیار

• Distributed Systems
• Machine Learning Systems
• Large-Scale Data Processing
• +۲ مورد دیگر

Bo Zhao is an Assistant Professor in the Department of Computer Science at Aalto University, leading the Aalto Data-Intensive System group (ADIS). His research focuses on building efficient data-intensive systems across multiple layers, from scalable machine learning systems to distributed data management systems. Research Focus: Scalable machine learning systems Distributed data processing Hardware-software co-design Quantum computing systems High-performance computing Current Projects: AthenaRL (scalable RL systems), LARA (quantum ML algorithms), FlexMoE (efficient mixture-of-experts systems). His group develops systems enabling ML deployment across hardware from quantum computers to mobile devices. Education & Career: PhD from Humboldt-Universität zu Berlin. Previously at Queen Mary University of London, Imperial College London, and Amazon Web Services. Research published in SOSP, VLDB, USENIX ATC.

Khosro Shahbaziمشاهده پروفایل

دانشیار

• Computational Fluid Dynamics
• Multiphase Flows
• Nanoparticle Applications
• +۴ مورد دیگر

Dr. Khosro Shahbazi is a tenured Associate Professor of Mechanical Engineering at South Dakota Mines. His expertise includes computational fluid dynamics, multiphase flows, and nanophysics applications in energy and medicine. He completed his Ph.D. at the University of Toronto and held postdoctoral positions at Brown University and University of Wyoming. Research interests focus on novel numerical methods for compressible flows, nanoparticle optoacoustics for cancer therapy, and turbulence modeling. His work bridges theory, computation, and experimentation in renewable energy, inertial confinement fusion, and biomedical systems. Recent publications emphasize high-order finite difference methods, compressible multiphase flows, mining ventilation systems, and photoacoustic diagnostics. Teaching includes Thermodynamics, Fluid Mechanics, Heat Transfer, and specialized graduate courses in computational transport phenomena. Education: B.S. (Sharif University), M.A.S. (Toronto), Ph.D. (Toronto) Laboratory: Computational Transport Phenomena Pedagogy: Emphasizes constructivism and rigorous challenge with support

Rohit Negiمشاهده پروفایل

استاد

• Wireless communications
• Networking
• Signal processing
• +۷ مورد دیگر

Rohit Negi is a Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University (CMU), affiliated with the College of Engineering. He holds a Ph.D. (2000) and M.S. (1996) in Electrical Engineering from Stanford University, and a B.Tech. from the Indian Institute of Technology Bombay (1995). His research focuses on wireless communications, networking, information theory, and cyberphysical systems, with emphasis on ad hoc networks, sensor networks, and power systems. Key roles include leading research on capacity of ultra-wideband (UWB) networks and joint optimization frameworks for physical/MAC/network layers. He has advised numerous Ph.D. and M.S. students, with notable alumni in industry (e.g., Qualcomm, Samsung) and academia (e.g., University of Florida). Research sponsors include NSF (including a Career Award), Texas Instruments, and industry partnerships. He has published extensively in IEEE journals/conferences, focusing on scheduling algorithms, secure communication, and power systems optimization. Notable awards include a 2012 IEEE Smart GridComm Best Paper Award and the President of India Gold Medal (1995). Teaching contributions include developing courses like 18-450 (Digital Wireless Communications) and co-designing the Intel Instructional Wireless Lab. His professional activities include editorial roles for IEEE Transactions and NSF review panels. Current research explores cyberphysical systems, smart grid state estimation, and reconfigurable RF-FPGA systems. Collaborations span disciplines like machine learning and network science, reflecting his holistic approach to engineering challenges.

• IoT
• Machine Learning
• Wireless Sensor Networks
• +۳ مورد دیگر

Qi Ang is a Postdoctoral Researcher in the Department of Economics, focusing on interdisciplinary research at the intersection of IoT, machine learning, and cybersecurity. Their work emphasizes practical applications such as smart irrigation, flood prediction systems, and secure wireless communication protocols. Key contributions include enhancing IoT device authentication, developing AI-driven environmental monitoring frameworks, and advancing physical layer security techniques. Research interests span IoT infrastructure, machine learning for environmental data analysis, wireless sensor networks, and cybersecurity solutions for constrained environments. Recent efforts include designing lightweight security protocols for IoT devices and integrating local sensor data with third-party forecasts for precision agriculture and disaster management. Publications highlight trends in sensor network modeling, anomaly detection, and energy-efficient routing. Notable projects include a smart sewage management system and a flooding alert system for municipal use. Qi Ang has also contributed to educational methodologies, as seen in their work on thesis quality assurance in academic settings.

Jie Zhangمشاهده پروفایل

استاد

• Wireless Communications
• 5G/6G Networks
• Machine Learning
• +۳ مورد دیگر

Professor Jie Zhang holds the Chair in Wireless Systems at the University of Sheffield's Department of Electronic and Electrical Engineering since 2011. He previously held roles at Imperial College London, Oxford University, and the University of Bedfordshire, becoming a Professor in 2006. With a PhD and MEng in Industrial Automation from East China University of Science and Technology, his research focuses on 5G/6G radio access, AI-driven network optimization, millimeter-wave communications, and smart environments. He pioneered femtocell/small cell and HetNet research, authoring influential papers and books like Femtocells: Technologies and Deployment . As a co-founder of RANPLAN (NASDAQ-listed) and Cambridge AI+ Ltd, he commercializes network design tools used globally. Since 2005, he secured over £10M in grants from EPSRC, Innovate UK, and EU programs, advancing femtocell/HetNet technologies. His work includes groundbreaking studies on interference coordination, spatial modulation, and IRS-based systems. Current research emphasizes AI in virtualized 5G RAN, proactive network optimization, and terahertz communications. Education: PhD in Industrial Automation, East China University of Science and Technology (1995) MEng in Industrial Automation, East China University of Science and Technology (1992) Research Interests: Dr. Zhang explores cutting-edge topics such as AI-enhanced 5G RAN, millimeter-wave small cells in built environments, and modeling smart environments. His work bridges theory and practice, addressing challenges like heterogeneous network optimization and OAM-based multiplexing. Recent efforts include IRS-enabled integrated sensing/communication systems and blockchain-fog computing optimizations. Grants & Awards: Over £10M in grants from EPSRC, EU FP6/FP7/H2020, and Innovate UK. Notable projects include early femtocell/HetNet research and AI-driven network planning models. His Google Scholar citations exceed 5700 (H-index 30). Advising & Labs: Leads a team advancing 6G and AI-driven wireless innovations. Collaborates with industry partners like RANPLAN to deploy tools like Ranplan Professional. His work impacts telecom operators and manufacturers globally.

Claude D'Amoursمشاهده پروفایل

استاد

• Wireless Communications
• MIMO Systems
• CDMA
• +۷ مورد دیگر

Claude D'Amours is a Professor at the University of Ottawa's School of Electrical Engineering and Computer Science, serving as Vice Dean of Academic Affairs since 2007. He holds a B.A.Sc., M.A.Sc., and Ph.D. in Electrical Engineering from the University of Ottawa (1990–1995). His career includes roles at the Communications Research Centre (CRC) and the Royal Military College (RMC). Research interests focus on advanced wireless communication systems, including MIMO, CDMA, OFDM/SC-FDMA, and error control coding. Notable innovations include the parity bit selected spreading technique and permutation spreading for MIMO-CDMA systems. He has pioneered work in UAV-to-ground channel modeling, mmWave MIMO precoding, and physical-layer security against jamming attacks. Recent publications emphasize 5G/6G technologies, secure network design, and channel optimization in challenging environments. His work addresses critical challenges in network reliability, interference management, and spectrum efficiency. Teaching awards: 2006 John V Marsh Award and 2007 University Excellence in Teaching Award Leadership roles: Vice Dean overseeing academic affairs in the Faculty of Engineering His research spans theoretical advancements and practical implementations, with contributions to cognitive radio systems, RF fingerprinting, and underwater sonar-based activity detection. Current projects include AI-driven 3D drone deployment frameworks and low-complexity detection algorithms for overloaded CDMA systems.

• Machine Learning
• Computer Vision
• Autonomous Robotics
• +۹ مورد دیگر

Yann LeCun is a Silver Professor at New York University (NYU) and Chief AI Scientist at Meta. He holds the Jacob T. Schwartz Chair in Computer Science at NYU's Courant Institute of Mathematical Sciences, and has affiliations with the Center for Data Science, Center for Neural Science, and the Tandon School of Engineering (Electrical and Computer Engineering). LeCun is a leading figure in artificial intelligence, known for pioneering work in deep learning, convolutional neural networks (e.g., LeNet), and self-supervised learning. His research focuses on machine learning, computer vision, autonomous robotics, and computational neuroscience. Education: Ph.D., Computer Science, Université Pierre et Marie Curie, France, 1987. DEA, Artificial Intelligence and Pattern Recognition, Université Pierre et Marie Curie, France, 1984. Diplôme d'Ingénieur, Electrical Engineering, École Supérieure d'Ingénieurs en Électrotechnique et Électronique, France, 1983. Research Interests: Machine learning, computer vision, robotics, computational neuroscience, and foundational AI research. He emphasizes the importance of self-supervised learning, world models for autonomous intelligence, and open-source AI development. His work bridges theoretical advancements with practical applications in healthcare, climate modeling, and robotics. Awards & Honors: ACM Turing Award (2018, shared with Geoffrey Hinton and Yoshua Bengio). Queen Elizabeth Prize for Engineering (2025). Member of the National Academy of Sciences and National Academy of Engineering. Multiple honorary doctorates and fellowships from institutions worldwide. Advising & Grants: LeCun has advised numerous PhD students and postdocs, many of whom have gone on to leadership roles in academia and industry. His research is supported by grants from Meta FAIR, NYU, and collaborations with institutions globally. He emphasizes mentorship and fostering interdisciplinary teams. Labs & Teams: Leads the CILVR Lab (Computational Intelligence, Learning, Vision, Robotics) at NYU and collaborates with Meta's FAIR (Fundamental AI Research). These groups focus on advancing AI through projects like JEPA (Joint Embedding Predictive Architecture) and World Models .