جست‌وجوی استاد و پژوهشگر

Carlos Rubio-Medranoمشاهده پروفایل

استادیار

• Cybersecurity
• Access Control
• Authorization Systems
• +۷ مورد دیگر

Carlos Rubio-Medrano is an Assistant Professor of Computer Science specializing in Cybersecurity at Texas A&M University-Corpus Christi's College of Science and Engineering. He leads the Cybersecurity Research and Innovation Laboratory (CSRIL) and has established himself as a prominent researcher in access control, authorization systems, and cyber-physical security. Dr. Rubio-Medrano earned his Ph.D. in Computer Science from Arizona State University (2016), following an MS from The University of Texas at El Paso (2008) and BS from Instituto Tecnologico de Chihuahua II (2005). His research focuses on the intersection of cybersecurity and software specification, verification, and validation, with particular expertise in access control models and their implementation at the source-code level. His work spans multiple domains including mobile security, industrial control systems, drone security, and energy delivery systems. He has secured substantial research funding including a $500,000 site award as part of the $10 million CYBER-CARE Transportation Cybersecurity Center and multiple NSF grants totaling over $2 million for projects related to zero-trust access management, drone security, and high-performance computing infrastructure. His recent publications demonstrate a strong trajectory in top-tier security venues including IEEE Security & Privacy (S&P), USENIX Security, and ACM conferences. His research shows an evolving focus from traditional access control systems to emerging challenges in cyber-physical systems, reflecting the expanding scope of cybersecurity threats in interconnected environments. Cybersecurity Fellow by the Computing Alliance of Hispanic Serving Institutions (CAHSI), December 2024 Dr. Rubio-Medrano actively mentors students, with multiple current PhD candidates and numerous past MS and BS students who have completed their degrees under his supervision. His teaching portfolio includes graduate courses in Advanced Software Engineering, Computer Forensics, and Advanced Information Assurance. He has been featured in TAMU-CC's 'Why I Teach' series and has received positive student evaluations highlighting his teaching excellence. His laboratory, CSRIL, focuses on innovative approaches to cybersecurity challenges, particularly in authorization frameworks for emerging technologies and mission-critical cyber-infrastructures.

• Computer Science
• Robotics
• Emergency Response Technology
• +۵ مورد دیگر

Dr. Alexander Ferworn is an Adjunct Professor in the Faculty of Computing and Software at McMaster University, specializing in computer science applications for public safety and emergency response systems. His work bridges robotics, human-computer interaction, and blockchain technology to address challenges in urban search and rescue, disaster relief, and medical data processing. His research focuses on integrating drones, haptic navigation systems, and virtual reality simulators to enhance emergency responder capabilities. Key contributions include frameworks for IED neutralization training ( Universal Simulation Platform ), blockchain-based aid delivery systems, and haptic feedback mechanisms for hazardous environments. He has extensively collaborated on projects involving canine-assisted technology and 3D disaster scene reconstruction. Dr. Ferworn’s scholarly activity spans 25 years with 126 publications in venues like IEEE International Conference on Safety, Security, and Rescue Robotics, IEEE GEM Conference, and Simulation & Gaming . His work has been referenced in patents and adopted by institutions like the Health Information Systems Research Centre . While specific teaching details remain unmentioned, his research portfolio demonstrates sustained engagement with disaster response systems since 1999.

• Marine Sciences and Technology
• Oceanography
• Geotechnical Engineering
• +۳ مورد دیگر

Cem GAZİOĞLU is a Professor at Istanbul University , affiliated with both the Institute of Marine Sciences and Management and the Faculty of Architecture (Department of Architecture). His academic career spans over two decades, with prior appointments at Istanbul Kültür University (2005-2013) and technical institutions. He holds a Doctorate in Marine Environment-Coastal Engineering (2001) and postgraduate degrees in Geomatics Engineering (1995, 1993). Research areas include Marine Sciences , Oceanography , Remote Sensing , and Environmental Pollution . Doctorate: Istanbul University , Institute of Marine Sciences and Management, Department of Marine Environment-Coastal Engineering (2001) Postgraduate: Istanbul Technical University , Geodesy and Photogrammetry Engineering Program (1995) Undergraduate: Istanbul Technical University , Geodesy and Photogrammetry Engineering (1993) His work focuses on coastal vulnerability , marine pollution , ship emissions , and climate change impacts on coastal zones. He employs remote sensing , GIS , and deep learning for coastal monitoring and environmental risk assessment. Recent studies include pharmaceutical residues in Arctic waters , antifouling paint biocides in the Sea of Marmara , and coastal inundation modeling . Publications highlight trends in satellite-derived bathymetry , coastal risk assessment , and maritime transport emissions . He has advised 38 graduate theses on topics like decarbonization in shipping , deep learning for coastal analysis , and marine environmental policy . His managerial roles include Director of the Institute and Member of the Senate at Istanbul University.

• Emergency cartography
• Geographic data
• Digital photogrammetry
• +۷ مورد دیگر

Dr. Fabio Giulio Tonolo is an Associate Professor at the Politecnico di Torino , Department of Architecture and Design (DAD), specializing in geomatics and remote sensing for urban and environmental applications. His work bridges emergency cartography , UAV photogrammetry , and climate change monitoring through advanced geospatial techniques. Academic Roles : Teaching Satellite Remote Sensing and GIS and Advanced Geospatial Data Management at various cycles of the PhD in Urban and Regional Development Research Leadership : Scientific Director for projects like MOHYCAM (hydrogeological hazards) and EMERITUS (environmental crimes), with collaborations on glacier monitoring and cultural heritage preservation Scientific Affiliations : Secretary of AIT - Italian Remote Sensing Association (2019-2026), former President of IWG-SEM, and active member of ISPRS working groups Key Research Themes : Multi-source geospatial data integration, 3D modeling for heritage conservation, satellite-based climate impact analysis, and emergency mapping protocols His 15 most recent publications focus on remote sensing , glacier monitoring , and cultural heritage digitization , with methodologies spanning from UAV LiDAR to AI-based image segmentation . Dr. Tonolo has received ASITA Federation Best Poster Awards and contributes to editorial boards like ISPRS International Journal . He supervises PhD students in Urban and Regional Development, leads commercial projects such as 3D metric surveys in Assisi, and participates in international conferences including GISTAM and Gi4DM. His work aligns with SDG 11 (Sustainable Cities) and ERC PE10_14 (Earth Observations).

Anu Bourgeoisمشاهده پروفایل

دانشیار

• Health Informatics
• Security and Privacy
• Wireless Networks
• +۲ مورد دیگر

Anu Bourgeois is an Associate Professor in the Department of Computer Science at Georgia State University. She holds a Ph.D. in Electrical and Computer Engineering from Louisiana State University. Her research spans health informatics, security and privacy, wireless and sensor networks, and computer science education. Dr. Bourgeois has served as general co-chair for the IEEE International Parallel and Distributed Processing Symposium (2020, 2023) and program co-chair for the IEEE International Conference on Internet of Things (2019). Her technical contributions include developing energy-efficient MAC protocols for sensor networks, privacy protection frameworks for context-aware services, and mobile health interventions for opioid use disorder. In computer science education, she explores bridge programs for underrepresented groups, TA training methods, and visualization of career pathways. Current projects include cosmic ray detection systems, natural language-controlled UAVs, and animation workflow innovations.

Tim Taltyمشاهده پروفایل

استاد

• Wireless Communications
• Communication Systems
• Signal Processing
• +۴ مورد دیگر

Tim Talty is a Collegiate Professor and Director of Admissions for the Master of Engineering Program at Virginia Tech's Bradley Department of Electrical and Computer Engineering. He holds a Ph.D. from the University of Toledo (1996) and a B.S. from Trine University (1987). His research focuses on wireless communications, signal processing, and intra-vehicle sensor networks, with particular emphasis on physical layer security and mobile communications. Key research areas include lidar systems, vehicular antennas, and software-defined radio architectures. He has contributed to innovations in automotive communication networks, including UWB localization and transparent antenna fabrication. His work bridges theoretical advancements with practical applications in autonomous vehicles and telematics. Notable awards include the General Motors ‘Boss Kettering’ Award for Innovation (2019) and the Commander's Award for Civilian Service from the U.S. Army. He has served as an ABET program evaluator and actively participates in industry collaborations, including leadership roles in IEEE conferences and automotive R&D initiatives. Recent publications emphasize energy-efficient computing for ADAS, lidar miniaturization, and 5G vehicle connectivity. His research trends highlight interdisciplinary approaches to solving challenges in vehicular communication, sensor fusion, and autonomous systems.

Xiaowei Wuمشاهده پروفایل

استادیار

• Statistical Genetics
• Bioinformatics
• Bayesian Statistics
• +۳ مورد دیگر

Xiaowei Wu is an Assistant Professor in the Department of Statistics at Virginia Polytechnic Institute and State University, part of the College of Science. He holds a Ph.D. in Statistics from Rice University (2010), and M.S. and B.S. degrees in Electrical Engineering from Wuhan University, China (2003 and 1997, respectively). His research focuses on statistical genetics, bioinformatics, Bayesian methods, and stochastic population dynamics. Key areas include mutation rate estimation, epigenetic analysis, and computational tools for genomic data. Teaching includes courses like Advanced Statistical Genomics and Probability & Statistics for Electrical Engineers. His work bridges theoretical statistics with applications in genetics, neurology, and environmental health. Notable contributions include developing simulation frameworks (e.g., SimuBP) and methodologies for analyzing genetic and epigenetic data. Current projects address antimicrobial resistance, neurological disorder genetics, and machine learning in clinical prediction. Publications span journals in stochastic analysis, genetics, and bioinformatics, with emphasis on branching processes, mutation dynamics, and genomic variant detection. He collaborates across disciplines to advance quantitative methods in life sciences and healthcare.

Kirti Rajagopalanمشاهده پروفایل

استادیار

• Environmental Engineering
• Agricultural Resource Management
• Water Resource Management
• +۳ مورد دیگر

Kirti Rajagopalan is an Assistant Professor in the Department of Biological Systems Engineering at Washington State University (WSU), part of the College of Agricultural, Human, and Natural Resource Sciences. Her research focuses on transdisciplinary approaches to address water and agricultural resource challenges through systems modeling, integrating engineering, economics, and environmental science. She leads the Agricultural, Natural and Human Systems Modeling Group, which develops tools for climate adaptation, water resource management, and crop resilience. Her work emphasizes leveraging satellite imagery, machine learning, and data-driven methods to solve real-world problems in precision agriculture and environmental sustainability. Key research interests include climate change impacts on crop water demand, precision agriculture technologies (e.g., SoilScan mobile app), and sustainable water management strategies. Dr. Rajagopalan collaborates widely with experts in entomology, statistics, and agronomy to ensure interdisciplinary problem-solving. Her contributions include advancing snow-water equivalent prediction models, evaluating seasonal forecast utility for agricultural decisions, and assessing vulnerabilities in the Columbia River Basin under climate change scenarios. Her recent projects highlight innovative applications of AI, such as the IGraSS framework for infrastructure network identification via satellite imagery, and UAV-based digital trait analysis for wheat yield prediction. She also investigates legal frameworks like water right forfeiture and the economic implications of agricultural water trading. Dr. Rajagopalan’s research has been supported by high-profile initiatives, including WSU’s leadership in a $20M NSF-funded AI institute for agriculture. Notably, her work bridges science and practice through public engagement, policy analysis, and stakeholder dialogues focused on the food-energy-water nexus. She emphasizes actionable solutions for resilient agricultural systems in the face of climate uncertainty, leveraging both technical and institutional innovations.

Ben Clarkمشاهده پروفایل

مدرس

• Digital Electronics
• Embedded Systems
• Signal Processing
• +۵ مورد دیگر

Ben Clark is a Lecturer in Digital Electronics at Loughborough University , part of the Wolfson School of Mechanical, Electrical and Manufacturing Engineering. He holds an MEng in Electronic and Electrical Engineering (2014) and a PhD in two-dimensional direction of arrival estimation with time modulated arrays (2019), both from Loughborough University. Previously, he worked as a Research Associate developing embedded sensor technologies and data acquisition systems. His teaching focuses on microcontrollers and software for embedded systems, with a commitment to innovative pedagogy. He received the Fellow Higher Education Academy (FHEA) in 2020 and the STEMLab Teaching Innovation Award (2021) for transforming lab equipment for blended learning. His research spans IoT systems, acoustic monitoring, UAV applications, and environmental sensing, with recent work on autonomous hydrophone deployment and flood forecasting in Colima, Mexico. Ben’s work integrates engineering solutions with real-world challenges, emphasizing interdisciplinary approaches. He collaborates with institutions globally and has contributed to projects like the RiverCore IoT device for water level monitoring.

• Remote Sensing
• Environmental Sciences
• Geomatic Engineering
• +۷ مورد دیگر

Dr. Yuting Zhou is an Associate Professor in the Department of Geography at Oklahoma State University. Her research focuses on understanding the impacts of climate and human activities on ecosystems using remote sensing, ecological models, and machine learning. She holds a PhD in Ecology from the University of Oklahoma (2017). Her work integrates satellite data (e.g., MODIS, Landsat), UAS imagery, and field observations to address challenges in land use change, drought monitoring, and sustainable food-energy-water systems. Key research areas include: Remote sensing applications for agricultural monitoring Flash drought detection and early warning Alfalfa and peanut crop management using UAVs Climate-vegetation interactions in grasslands Sustainable development goals (SDGs 2, 6, 13, 15) Currently leads projects funded by NSF EPSCoR, OklahomaView, and USDA collaborations. She actively collaborates with researchers at the University of Oklahoma and USDA ARS labs. Courses taught include GIS fundamentals, environmental problem-solving tools, and advanced remote sensing applications. Notable achievements include developing novel drought indices using LSWI, optimizing crop yield prediction with deep learning, and advancing UAS-based agricultural monitoring techniques. Her work bridges geospatial technologies with real-world sustainability challenges.

Jarosław Bosyمشاهده پروفایل

استاد

• Geodesy
• GNSS Meteorology
• Remote Sensing
• +۴ مورد دیگر

Jarosław Bosy is a Full Professor at the Institute of Geodesy and Geoinformatics at Wrocław University of Environmental and Life Sciences (WUELS), Poland. He served as Vice-Rector for Research and International Relations (2016–2020) and Rector (2020–2024). Since June 2024, he chairs the Committee on Geodesy of the Polish Academy of Sciences. He holds a PhD in Geodesy and Cartography (1996) and habilitation from AGH University of Science and Technology, Kraków. Awarded the Professor title in Technical Sciences by the Polish President in 2014. His research focuses on three core areas: GNSS-based reference frame realization at global/regional scales, GNSS meteorology (atmospheric state analysis via satellite signals), and GNSS applications in geodynamics. Key contributions include real-time troposphere delay models, integration of GNSS and numerical weather prediction (NWP), and development of the ASG-EUPOS positioning system in Poland. Bosy has authored 286 publications, supervised 23 PhD theses, and led 7 projects. His work bridges geodesy, meteorology, and geodynamics, with applications in climate monitoring, real-time positioning, and Earth system observation. He collaborates internationally, contributing to initiatives like GGOS and EPOS. His lab, GNSS&Meteo, develops services like real-time ZTD estimation and MSTID mitigation for precise positioning.

Yufei Liمشاهده پروفایل

استاد

• Database Systems
• Software Engineering
• Machine Learning
• +۳ مورد دیگر

Yufei Li is a Professor at Xi'an Jiaotong University's School of Computer Science and Technology, Department of Computer Science. With an extensive publication record spanning from 2007 to 2025, Dr. Li has established himself as a prominent researcher in database systems, software engineering, and machine learning applications. His work demonstrates strong interdisciplinary connections between computer science and electrical engineering, particularly in power systems applications. Dr. Li's research interests span multiple domains of computer science and engineering. His primary focus is on database systems, where he has pioneered work in LLM-based database tuning systems like GPTuner. He also has significant contributions in software configuration and performance optimization, as evidenced by his CSAT framework. His research extends to computer vision applications for security screening and medical diagnostics, as well as electrical engineering applications in power systems and UAV control. This diverse portfolio demonstrates his ability to bridge theoretical computer science with practical engineering applications across multiple domains. Analysis of Dr. Li's recent publications (2023-2025) reveals a strong trend toward integrating large language models with traditional computer science domains. His work on GPTuner represents a significant advancement in applying LLMs to database tuning, while his research on QUITE demonstrates innovative approaches to query rewriting using LLM agents. There's also a clear pattern of applying advanced machine learning techniques to solve domain-specific problems across electrical engineering, medical diagnostics, and industrial quality control. The interdisciplinary nature of his work positions him at the forefront of AI integration across multiple engineering disciplines. Dr. Li has established a productive research group with numerous doctoral students and collaborators, particularly Jiale Lao, Yibo Wang, and Jianguo Wang who frequently appear as co-authors on his recent publications. His research has been consistently funded, as evidenced by the steady stream of publications across multiple high-impact venues including IEEE Access, Journal of Systems and Software, and CVPR. His work demonstrates strong industry relevance with applications in database management, software configuration, security screening, and power systems. Dr. Li leads a research team focused on database systems and AI integration, with strong connections to both computer science and electrical engineering domains. His group appears to specialize in applying cutting-edge machine learning techniques, particularly large language models, to solve longstanding problems in database management and software engineering. The team maintains active collaborations with researchers across multiple institutions, as evidenced by the diverse author lists on his publications.

Jin-Hee Choمشاهده پروفایل

دانشیار

• Cybersecurity
• Artificial Intelligence
• Trust Management
• +۷ مورد دیگر

Jin-Hee Cho is an Associate Professor at the Department of Computer Science, Virginia Tech. Affiliations include the National Security Institute and the Northern Virginia Center. She holds the Stephen and Cherye Tyndall Moore Computer Science Junior Faculty Fellowship and is a Faculty Fellow of the College of Engineering. Education: Ph.D. (2008) and M.S. (2004) in Computer Science from Virginia Tech. Research Interests: Focus on cybersecurity, AI-driven defense mechanisms, and human factors. Key areas include trust management, moving target defense, uncertainty reasoning, and federated learning. Her work addresses challenges in autonomous systems, smart agriculture, and social network analysis, with a focus on interdisciplinary solutions for critical infrastructure protection and online safety. Recent Research Trends: Recent publications emphasize AI safety, privacy-preserving federated learning frameworks, and resilience against adversarial attacks. Themes include decision-theoretic approaches to influence maximization, game-theoretic defense strategies, and cybersecurity for autonomous vehicles and IoT systems. Awards: Stephen and Cherye Tyndall Moore Computer Science Junior Faculty Fellow Faculty Fellow, College of Engineering (Virginia Tech) Advising & Grants: While no student names are listed, her research involves collaborative projects on cyber deception, resilient networks, and AI ethics. Her work is supported by grants addressing topics like cybergrooming prevention and federated learning security. Labs & Teams: Engaged in interdisciplinary collaborations across the National Security Institute and Northern Virginia Center, focusing on cybersecurity, AI, and societal resilience.

Kanad Ghoseمشاهده پروفایل

استاد

• Computer Architecture
• Power-Aware Systems
• High-Performance Computing
• +۶ مورد دیگر

Kanad Ghose is a Distinguished Professor and Director of the Center for Energy-Smart Electronic Systems (ES2) at SUNY Binghamton's School of Computing. His research focuses on computer architecture, power-aware systems, high-performance computing, and cybersecurity. He leads projects in data center energy management, secure processor design, and flexible electronics for wearable health monitoring. Education: BTech/M.Tech from University of Calcutta; MS/PhD from Iowa State University Awards: SUNY Chancellor's Award, IBM Faculty Award, National Science Talent Search Research interests include energy-efficient microarchitectures, cybersecurity at the hardware level, and autonomous systems. Notable projects involve data center cooling optimization, secure execution validation, and wearable ECG sensors. His lab collaborates with industry partners like Intel, Lockheed Martin, and UC Berkeley's Arias group. Current projects include DC-powered data centers, FPGA accelerators, and flexible electronics for clinical-grade health monitoring. Past work includes the MARSSx86 simulator and ARINC-compliant avionics systems.

• Massive MIMO
• Cognitive Radio Networks
• Smart Grids
• +۶ مورد دیگر

Professor Sangarapillai Lambotharan is a Professor of Digital Communications and Head of the Signal Processing and Networks Research Group at Loughborough University's Wolfson School of Mechanical, Electrical and Manufacturing Engineering. He holds qualifications including BEng, PhD, DIC, PGCAP, and is a Senior Member of IEEE, Fellow of IET, and Fellow of the Higher Education Academy. His research focuses on advanced wireless communication technologies such as Massive MIMO, Cognitive Radio Networks, and Smart Grids, alongside Machine Learning, Data Mining, and Cyber Security. He has authored over 200 publications in top-tier journals and conferences. His work integrates machine learning with signal processing to address challenges in adversarial attacks, federated learning, and network optimization. Recent research emphasizes intelligent reflecting surfaces (RIS), OTFS satellite communications, and federated learning defenses against model poisoning. Prof. Lambotharan's contributions span theory development, algorithm design, and practical implementations in 5G/6G systems, UAV networks, and edge computing environments. He leads collaborative projects on secure communications, distributed intelligence, and blockchain-based network security mechanisms. Prof. Lambotharan's academic leadership includes editorial roles at IET Signal Processing and teaching Digital Signal Processing and Information Theory. His lab explores cutting-edge topics like RIS-aided systems, anomaly detection in IoT, and context-aware caching strategies for heterogeneous networks. Key achievements include pioneering work on Kalman filtering for channel estimation and game-theoretic solutions for resource allocation in cognitive radio networks.