جستجوی استاد راهنمای دانشگاهی

Lav Guptaمشاهده پروفایل

استادیار

• Cybersecurity
• Networking
• Cloud Computing
• +۵ مورد دیگر

Lav Gupta is an Assistant Professor of Computer Science at the University of Missouri–St. Louis. He holds a Ph.D. and MS from Washington University in St. Louis, and BS/MS degrees from Indian Institute of Technology Kanpur and Roorkee. His research focuses on cybersecurity, networking, cloud computing, and AI applications in critical infrastructure like healthcare and finance. Research interests include secure multi-cloud management, AI-driven fault detection in virtual networks, and resilient healthcare systems. He has published 13+ first-author papers in journals/conferences, with work on hierarchical deep learning for cybersecurity and edge-cloud AI. His funded projects include NSF/SaTC grants and UM System Broadband Research initiatives. Current work involves standardization efforts at ITU-T Geneva for inter-cloud service management frameworks. Notable awards include the 2015 Broadcom Foundation Research Award and Vodafone’s 2014 Wireless Innovation Prize. He leads the Cybersecurity and Networking Lab, offering GRA positions in multi-cloud security and 5G/6G systems. Students can contact via email or office hours (Wednesdays in-person/Zoom). Grants and collaborations highlight industry ties through Sony and ITU-T. Future work emphasizes socially impactful applications like smart cities and critical patient monitoring systems.

Hangtian Leiمشاهده پروفایل

دانشیار

• Power System Operation
• Power System Reliability
• Substation Automation
• +۱ مورد دیگر

Hangtian Lei is an Associate Professor in the Department of Electrical & Computer Engineering at the University of Idaho's College of Engineering. He holds a PhD from Texas A&M University and a B.E. from Huazhong University of Science and Technology. His research focuses on power system operation and control, probabilistic methods for reliability evaluation, substation automation, and power system protection. He teaches courses including Energy Systems, Power Systems, Power System Protection, and Power Systems Planning. Awards include: IEEE Power and Energy Society Prize Paper Award (2018) PSERC Best Poster Award (2015) His publications address critical challenges in power system resilience, renewable integration, and protection systems.

• Software Engineering
• Machine Learning
• Neural Networks
• +۳ مورد دیگر

Dr. Tien Nguyen is an Associate Professor in the Department of Computer Science at UT Dallas' Erik Jonsson School of Engineering. His research focuses on software engineering innovations, particularly in machine learning applications for code analysis, vulnerability detection, and automated testing. He develops neural network approaches to enhance software quality and security. Recent publications demonstrate strong emphasis on AI-driven software solutions, including GPT-based test generation, neural vulnerability scanners, and code representation learning. His team's work bridges theoretical computer science with practical developer tools, evidenced by studies on syntactic sugar design and program dependence learning. Dr. Nguyen's lab maintains active industry collaborations, with translational research addressing real-world challenges in code maintenance and cybersecurity. Current projects explore context-aware code analysis and self-improving language models for programming assistance.

Larry Yueli Zhangمشاهده پروفایل

استادیار

• Social Network Analysis
• Computing Education
• Data Structures
• +۵ مورد دیگر

Larry Yueli Zhang is an Assistant Professor, Teaching Stream in the Department of Electrical Engineering & Computer Science at York University's Lassonde School of Engineering. He holds a PhD from the University of Toronto's Department of Computer Science and previously served as teaching faculty at the University of Toronto Mississauga's Department of Mathematical and Computational Sciences. His research focuses on social network analysis, information networks, and computing education. He is actively involved in curriculum development for York University's Markham Campus, including the Computer Science for Software Development (CSSD) and Digital Technologies (DT) programs. His teaching spans undergraduate courses in data structures, algorithms, computer organization, and distributed systems. Notable projects include SlideChat (an interactive slide-based discussion platform), Velocity (a course management tool), and OkShell (a human-friendly command-line interface). He has received awards such as the Alexander Graham Bell Canada Graduate Scholarship (2013) and Outstanding Master's Thesis from Tsinghua University. Larry's research emphasizes improving computing education through innovative pedagogical tools and analyzing student learning behaviors. His work includes studies on gamified quizzes, online exam strategies, and breakout room utilization in large courses.

Luigi Vanfrettiمشاهده پروفایل

استاد

• Cyber-Physical Systems
• Power Systems
• Electrified Transportation
• +۷ مورد دیگر

Luigi Vanfretti is a Full Professor in the Department of Electrical, Computer, and Systems Engineering at Rensselaer Polytechnic Institute (RPI), leading the ALSETLab. His research focuses on energy systems, cyber-physical systems (CPS), aircraft electrification, and synchrophasor technologies. He holds an IEEE Senior Member designation and Modelica Association membership. Previously, he served as an associate professor at RPI and held roles at KTH Royal Institute of Technology in Sweden and Statnett SF in Norway. Education includes a Ph.D. and M.Sc. in Electric Power Engineering from RPI, and a Visiting Researcher stint at the University of Glasgow. His work spans power grid dynamics, renewable integration, and hardware-in-the-loop testing. Notable projects include NSF/DOE-funded initiatives on grid resilience, HVDC systems, and smart inverter protocols. He has held visiting positions at institutions like École Centrale de Lyon and Mitsubishi Electric Research Laboratories (MERL), contributing to collaborative research in building energy systems and grid-interactive technologies. Research interests emphasize CPS modeling, synchrophasor data analytics, and machine learning applications in power systems. His ALSETLab develops open-source tools like OpenIPSL and S3DK for power system simulation. Recent publications address generative networks for building scenarios, wideband impedance passivation, and oscillation analysis in power grids. Collaborations include industry partners like Dominion Energy and academic institutions worldwide.

Keren Liمشاهده پروفایل

استادیار

• Distributed Learning
• Federated Learning
• Deep Learning
• +۷ مورد دیگر

Keren Li is an Assistant Professor in the Department of Mathematics at the University of Alabama at Birmingham (UAB), affiliated with the College of Arts and Sciences. She holds a PhD in Statistics from the University of Illinois at Chicago (2018), an MS in Mathematics from Louisiana State University (2004), and a BA in Mathematics from Nankai University (2001). Before joining UAB in 2022, she served as an Associate Scientist at UAB's Informatics Institute (2023–2024) and a Postdoctoral Fellow at Northwestern University’s NSF-Simons Center for Quantitative Biology and Department of Statistics and Data Science (2018–2022). Her research focuses on distributed learning, federated learning, deep learning, bioinformatics, and financial mathematics. Key projects include developing tools like DNAcycP (predicting DNA cyclizability) and RiboDiPA (analyzing ribosome profiling data). She also explores statistical methods for optimal design and generalized linear models. Her work bridges computational methods and real-world applications, with contributions to genomics, energy networks, and financial modeling. Her lab ( klilab ) emphasizes interdisciplinary collaboration and innovative algorithm development.

Alison Leitchمشاهده پروفایل

دانشیار

• Geophysics
• Magma Dynamics
• Environmental Geology
• +۳ مورد دیگر

Dr. Alison Leitch is an Associate Professor in the Department of Earth Sciences at Memorial University of Newfoundland (MUN), within the Faculty of Science. Her academic journey includes roles as Assistant Professor (2000–2004), Post-doctoral Fellow (1992–1998), and earlier research positions in Australia, the U.S., and Canada. She holds a Ph.D. in Geophysical Fluid Dynamics (1986) and a B.Sc. (Honours) in Physics (1979), both from the Australian National University. Her research focuses on geophysics, magma dynamics, and environmental applications of geophysical techniques. Key areas include magma mingling processes, reducing spring detection in ophiolites, and geophysical exploration for mineral deposits. She teaches courses such as Electric and Electromagnetic Methods in Geophysics and Global Tectonic Processes . Leitch has supervised numerous graduate students, including projects on the Fogo Island Batholith, Howley Basin hydrocarbon potential, and Valentine Gold Project. Recent collaborations involve coastal erosion monitoring in Bay Bulls and serpentinization studies in Newfoundland’s Tablelands. Her work spans field, lab, and theoretical studies, with publications in journals like Journal of Petrology , Economic Geology , and Atlantic Geology . Current projects include geophysical detection of reducing springs and magma chamber dynamics modeling.

Maitreyee Deyمشاهده پروفایل

مدرس ارشد

• Machine Learning
• Cybersecurity
• Smart Grids
• +۴ مورد دیگر

Dr. Maitreyee Dey is a Senior Lecturer in Computer Science and Applied Computing at London Metropolitan University. She leads the GENESIS Research Lab and serves as Deputy Director in Business Engagement at the Cyber Security Research Centre. Her research focuses on machine learning applications in smart grids, healthcare technology, IoT security, and HVAC systems optimization. She has pioneered projects involving fault detection in HVAC terminal units, cybersecurity compliance for IoT devices, and non-invasive medical diagnostics using microwave technology. Her work integrates machine learning with domain-specific challenges such as voltage anomaly detection in solar farms, predictive modeling for early-stage diabetes, and grid stability analysis using micro-PMU data. She also explores educational technology innovations like the VEMeter tool for virtual classroom participation tracking and AI-driven student engagement strategies. Dr. Dey has contributed to international conferences and authored numerous papers on topics ranging from smart building automation to radiation-free medical imaging systems. Her interdisciplinary approach bridges computer science, engineering, and healthcare, with a focus on real-world impact through industry partnerships and technology commercialization.

Azeez Abdul Azeezمشاهده پروفایل

پژوهشگر

• Condition Monitoring
• Artificial Intelligence (AI)
• Mechanical Engineering
• +۳ مورد دیگر

Azeez Abdul Azeez is a researcher at Tampere University, specializing in AI-driven condition monitoring systems for mechanical and hydraulic components. His work focuses on integrating artificial intelligence with fluid power systems to enhance fault detection and predictive maintenance. He holds a Doctoral Degree in Mechanical Engineering from Tampere University (2025). Key research areas include gear pump simulation, hydraulic valve diagnostics, and electric drive structures. Research Interests His research interests revolve around the application of AI in mechanical systems, including: Condition Monitoring of Electro-Hydraulic Systems Simulation of Gear Pump Performance under Varying Complexity Sensorless Fault Classification in Hydraulic Valves Energy Efficiency in Off-Road Mobile Machines Main Findings His recent work highlights the importance of model complexity in gear pump simulations (2023), the impact of electric drive structures on hydraulic valve diagnostics (2023), and the potential of AI in non-road machine applications (2025). Collaborations include studies on multi-physics co-simulations of electric vehicles (2023) and offshore renewable energy feasibility in UAE (2021). Labs and Teams His research is conducted within Tampere University's Automation Technology and Mechanical Engineering department, often in collaboration with industry partners focusing on fluid power systems and sustainable energy.

Peng Zhangمشاهده پروفایل

استاد

• Power and Energy
• Quantum-Engineered Power Grids
• AI-Enabled Power Grids
• +۷ مورد دیگر

Peng Zhang is a tenured Full Professor of Electrical and Computer Engineering and a SUNY Empire Innovation Professor at Stony Brook University. He also holds affiliate professorships in Computer Science and Applied Mathematics & Statistics. His research focuses on cyber-physical grid resilience, including quantum-engineered grids, AI-enabled systems, and cybersecurity. He leads the Power Lab, developing technologies like software-defined grids and programmable microgrids. PhD: Electrical Engineering, University of British Columbia (Canada) Masters: Tsinghua University Bachelor's: Shandong University Research interests span quantum grids, AI-driven grid optimization, microgrid stability, and formal methods for resilience. Key projects include NSF-funded initiatives on resilient networked microgrids and quantum-security frameworks. Recent publications emphasize quantum computing applications in power systems, cybersecurity solutions, and fault management. Awards include the 2018 IEEE Technological Innovation Award and Excellence in Energy Award. Advises numerous PhD students and leads labs such as the Quantum Grids Lab and AI-Grid Lab. Active in grants and industry collaborations, including with Eversource Energy and DOE projects.

Jianying Zhouمشاهده پروفایل

استاد

• Applied Cryptography
• Network Security
• Cyber-Physical System Security
• +۵ مورد دیگر

Jianying Zhou serves as Professor and Centre Director at Singapore University of Technology and Design (SUTD), leading the iTrust Centre for Research in Cyber Security. He holds a PhD in Information Security from Royal Holloway, University of London and maintains active leadership roles including co-founding ACNS, chairing ACM AsiaCCS steering committee, and serving on Asiacrypt steering committee. PhD in Information Security, Royal Holloway, University of London His research spans applied cryptography, cyber-physical systems security, and mobile/wireless security with emphasis on industrial control systems, blockchain, and automotive networks. Recent work focuses on practical security solutions for critical infrastructure including maritime systems, smart grids, and IoT ecosystems, combining cryptographic innovation with real-world deployment challenges. Analysis of his 2025 publications reveals concentrated efforts in blockchain security (selfish mining, payment channels), industrial IoT protection (PLC authentication, CAN bus intrusion detection), and privacy-preserving machine learning (federated learning attacks/defenses). Maritime cybersecurity and automotive security represent rapidly growing application domains reflecting real-world critical infrastructure needs. Scientific recognition includes: ESORICS Outstanding Contribution Award (2020) ACM Distinguished Member status As iTrust Centre Director, Zhou oversees multi-institutional research teams developing security frameworks for critical infrastructure. While specific student advising details aren't public, his leadership in major conferences indicates extensive mentorship activities. His research program demonstrates strong industry collaboration focus with practical security implementations for maritime, healthcare, and industrial systems. iTrust operates as SUTD's flagship cybersecurity research center under Zhou's direction, bringing together interdisciplinary teams to address cyber-physical security challenges through testbed development, protocol design, and risk assessment frameworks for critical infrastructure protection.

Kui Wuمشاهده پروفایل

استاد

• Computer Networks
• Wireless and Mobile Networking
• Mobile Computing
• +۵ مورد دیگر

Prof. Kui Wu is a Professor in the Department of Computer Science at the University of Victoria, affiliated with the Faculty of Engineering and Computer Science. His research focuses on computer networks, wireless and mobile networking, mobile computing, and network security. He is part of the Parallel, Networking and Distributed Computing (PANDA) research group. Key areas of expertise include distributed learning frameworks, autonomous systems, IoT anomaly detection, and edge computing architectures. His work integrates machine learning techniques with network optimization, addressing challenges in real-time systems, security, and resource allocation. Notable contributions include advancements in federated learning, privacy-preserving distributed systems, and UAV-based monitoring solutions. Prof. Wu's research also explores edge computing innovations, such as smart contract-aided IoT resource sharing and energy-efficient edge data centers. He has contributed to over 50 peer-reviewed publications, with recent work emphasizing AI-driven network design, anomaly detection in IoT, and reinforcement learning applications in autonomous driving safety. His research has practical implications for improving the reliability and efficiency of next-generation communication and computing infrastructures.

Karakostas Vasileiosمشاهده پروفایل

استادیار

• Computer Architecture
• Cloud Computing
• RISC-V Processors
• +۵ مورد دیگر

Karakostas Vasileios is an Assistant Professor at the Department of Informatics and Telecommunications of the National and Kapodistrian University of Athens. His research focuses on computer architecture, cloud computing, and energy-efficient hardware systems. He specializes in areas such as RISC-V processors, virtual memory systems, and hardware security. Vasileios leads projects like NEUROPULS (neuromorphic secure accelerators) and Vitamin-V (RISC-V-based cloud infrastructure validation). His work emphasizes resilience analysis, performance optimization, and trustworthy development frameworks. Education and employment details are not explicitly provided in the source text, but his extensive publication record since 2011 demonstrates continuous academic engagement. Key research trends include: Memory systems optimization (e.g., TLB hierarchies, elastic translations) GPU and SoC fault tolerance analysis Cloud resource management (ACTiCLOUD, DAPHNE runtime) Open-source hardware validation (Vitamin-V project) Notable contributions include the Gem5-marvel simulator for heterogeneous architectures and BypassD for SSD access acceleration. His work bridges theoretical computer architecture with practical cloud and embedded system applications.

• Operating Systems
• Fault Tolerance
• Cyber-Physical Systems
• +۵ مورد دیگر

Marcus Völp is an Associate Professor and head of the CritiX research group at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT). His research focuses on ultra-reliable operating systems, fault and intrusion tolerant systems for cyber-physical environments, and hierarchical hybridization techniques to construct resilient computing platforms. His work bridges theoretical foundations with practical implementations, particularly in developing dependable systems-on-chip that can withstand faults and intrusions. Research spans formal verification methods, radiation-hardened hardware, blockchain security, and autonomous vehicle safety systems. Recent publications demonstrate advancement in parameterized system verification, radiation effects on routers, and N-version machine learning for autonomous systems. His group maintains strong focus on practical resilience mechanisms for real-time and critical systems across computing layers.

• Bayesian Methods
• Biostatistics
• Data Science
• +۴ مورد دیگر

Saman Muthukumarana is a Professor and Head of the Department of Statistics at the University of Manitoba. He joined the department in 2010 as an Assistant Professor, was promoted to Associate Professor in 2016, and became a full Professor in 2022. He holds a BSc (Honours Special) in Statistics from the University of Sri Jayewardenepura, an MSc from Simon Fraser University, and a PhD from Simon Fraser University under Dr. Tim Swartz, focusing on Bayesian methods and applications. His research emphasizes Bayesian methodologies for complex models, with applications in social networks, health studies, sports analytics, environmental science, and machine learning. He has secured over $8.4M in research funding from NSERC, Mitacs, CIHR, and other organizations. His work has been published in journals such as the Canadian Journal of Statistics, Machine Learning with Applications, and IEEE Open Journal of Instrumentation & Measurement. Dr. Muthukumarana’s research spans Bayesian computation, biostatistics, data science, and environmental statistics. He has contributed to anomaly detection in buildings, predictive modeling for public health (e.g., Long COVID), and ecological studies like salmon stock recruitment. His collaborative projects include developing statistical tools for microbiome analysis and improving machine learning approaches for imbalanced datasets. He also leads the Data Science Nexus, fostering interdisciplinary research. His grants and collaborations highlight his role in advancing statistical methodologies for real-world challenges, including health, energy efficiency, and ecological conservation. While no specific awards are listed, his extensive funding and publication record reflect his scholarly impact. He currently supervises graduate students and actively participates in academic leadership roles.