جست‌وجوی استاد و پژوهشگر

• Systems Theory
• Machine Learning
• Artificial Intelligence
• +۴ مورد دیگر

Tyler Cody is an Associate Professor of Data Science at the University of Virginia School of Data Science and a member of the National Security Data and Policy Institute. His research bridges systems engineering and artificial intelligence through abstract systems theory. Education: Ph.D. in Systems Engineering, University of Virginia B.S. in Systems Engineering, University of Virginia (minors: Computer Science, Applied Mathematics) Dr. Cody's research centers on systems theory as a meta-theory for learning, with applications in machine prognostics, telecommunications, computer networks, fraud detection, and computer vision. He investigates phenomena in learning processes, focusing on change and reuse, lifecycles, and iterated games. His recent publications (2024-2025) reveal a strong trend in applying systems theory to machine learning assurance and cyber security. Key areas include reinforcement learning for cyber operations, combinatorial methods for testing ML systems, and outcome-based engineering for AI. His work also addresses ethical implications and architectural design of learning systems. Scientific Awards: No awards listed in the provided information. No details were provided regarding student advising or research grants. Dr. Cody contributes to the National Security Data and Policy Institute, where his expertise supports data-driven approaches to national security challenges through systems-theoretic frameworks.

Mike Barthمشاهده پروفایل

استاد

• Automation Technology
• Control Systems
• Cyber-Physical Systems (CPS)
• +۵ مورد دیگر

Prof. Mike Barth is a Professor for Networked Secure Automation Technology at the Karlsruhe Institute of Technology (KIT), affiliated with the Department of Electrical Engineering and Information Technology (ETIT) and the Institute for Control Systems (IRS). His academic background includes a doctorate from Helmut Schmidt University (2011) and a master's degree from Pforzheim University (2008). He previously held roles as a researcher at ABB and as a professor at Pforzheim University, focusing on blended learning and Industry 4.0 integration. Education: PhD in Automation Technology, Helmut Schmidt University (2011) M.Sc. in Product Development, Pforzheim University (2008) Diploma in Mechanical Engineering, Pforzheim University (2006) Research Interests: Automation technology, control systems, Industry 4.0, cyber-physical systems, digital twin engineering, cybersecurity, and IoT protocols. Teaching: Courses include System Modeling, Cyber Physical Production Systems, and Digital Twin Engineering. His research emphasizes secure automation architectures, decentralized systems, and model-based engineering. He chairs multiple committees including IFAC TC3.1 and the VDI/VDE Society for Measurement and Automation. Over 50+ publications span topics like simulation models, industrial security, and robotic integration. Labs/Teams: Leads the IRS Automation Technology team, focusing on innovation in control systems and digital twin applications.

Ting-Chung Poonمشاهده پروفایل

استاد

• Optical Scanning Holography
• Digital Holography
• 3D Imaging
• +۳ مورد دیگر

Ting-Chung Poon is a Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. His research focuses on optical scanning holography (OSH), digital holography, and 3D imaging applications. He leads the Optical Scanning-Holographic Imaging Group (OSIG), which explores OSH for 3D imaging, processing, and display, emphasizing 2D optical heterodyne scanning techniques. Education: Ph.D., University of Iowa, 1982 M.S.E.E., University of Iowa, 1979 B.A., University of Iowa, 1977 Research Interests: Optical Scanning Holography (OSH) and its applications in 3D imaging Computer-Generated Holography (CGH) Quantitative Phase Imaging Optical Cryptography Efficient Hologram Algorithms His work spans theoretical advancements and practical implementations, including encryption systems, noise reduction techniques, and high-resolution 3D reconstruction. Recent Research Trends: Focus on polygon-based CGH algorithms for faster rendering Integration of machine learning for speckle noise reduction and hologram classification Development of adaptive and compressive holography methods for industrial and biomedical applications Labs & Teams: Optical Scanning-Holographic Imaging Group (OSIG) at Virginia Tech Collaborations with institutions globally, including conferences on digital holography and photonics

Bradley Hayesمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Robotics
• Human-Robot Interaction
• +۵ مورد دیگر

Bradley Hayes is an Associate Professor in the Department of Computer Science at the University of Colorado Boulder, affiliated with the College of Engineering and Applied Science. He leads the Collaborative AI and Robotics (CAIRO) Lab, focusing on creating autonomous robots that collaborate effectively with humans through advances in explainable AI, machine learning, and human-robot interaction. His prior research includes foundational work at MIT's Interactive Robotics Group and Yale's Social Robotics Lab. Research interests span Explainable AI, Learning from Demonstration, Hierarchical Reinforcement Learning, Computer Vision, Natural Language Processing, and Cognitive Science. His work emphasizes making human-robot teams more efficient and safe through innovations like emotionally expressive robotic motion, socially aware navigation, and AR-based collaboration tools. Key contributions include techniques for robust robotic exploration, generative occupancy mapping, and systems for improving human trust through predictable robot behavior. His work has been applied to teleoperation training, surgical assistance, and space exploration scenarios. Grants and partnerships support development of assistive robotic canes and AR interfaces for collaborative tasks. Lab activities emphasize translating theoretical advancements into practical systems through close collaboration between researchers, engineers, and end-users. Education efforts include developing foundational robotics curricula addressing autonomy, perception, and control systems.

• Multibody dynamics
• Control of nonlinear systems
• Model predictive control

Michael Mühlebach is a Lecturer at the Department of Information Technology and Electrical Engineering at ETH Zurich, affiliated with the Max Planck Institute for Intelligent Systems in Tübingen, Germany. He received Bachelor (2010) and Master (2013) degrees from ETH Zurich, awarded the Outstanding D-MAVT Bachelor Award and Willi-Studer Prize for top performance. His research specializes in multibody dynamics , control of nonlinear systems , and model predictive control , with applications in robotics and aerospace systems. Publications demonstrate consistent focus on theoretical control frameworks validated through experimental platforms like ducted fans and reaction-wheel systems. Awards: Outstanding D-MAVT Bachelor Award Willi-Studer Prize (Best Master in Robotics, Systems, and Control)

Cameron Taylorمشاهده پروفایل

استادیار

• Rehabilitation Engineering
• Neuromuscular Sensing and Stimulation
• Electromagnetics
• +۳ مورد دیگر

Cameron Taylor is an Assistant Professor in the Lampe Joint Department of Biomedical Engineering at UNC Chapel Hill and NC State University . His research focuses on neuromuscular sensing and stimulation , electromagnetics , and computational science . He teaches BMME 385 - Bioinstrumentation and leads the Hi-PHI Lab , which develops transformative human interfacing technologies to restore ability in persons with movement disorders. His work integrates magnetoquasistatics , neural interfacing , and muscle physiology . Ph.D. in Media Arts and Sciences (Biomechatronics) MIT, 2020 M.S. in Media Arts and Sciences (Biomechatronics) MIT, 2016 B.S. in Electrical Engineering Brigham Young University, 2014 A.S. Mesa Community College, 2012 His research interests include novel electromagnetic strategies for sensing and imaging the human body, with applications in wearable technologies and clinical interventions. His lab’s innovations include magnetomicrometry —a first-of-its-kind technology for real-time muscle tissue tracking in humans. Awards : - 2023 Promising Investigator Award from the Rocky Mountain Muscle Symposium Lab and Team : The Hi-PHI Lab, launching Fall 2025, seeks graduate students and postdocs with expertise in electromagnetics , algorithm development , or signal processing . Current advisees include Mahavir Prasad (PhD candidate focused on affordable human interfacing technologies) and John Goebel (PhD candidate working on bioelectronic equipment for tissue measurements). His work has been featured in Physics World , MIT Technology Review , and Electronic Design .

Hafizul Asadمشاهده پروفایل

مدرس

• Formal Verification
• Hybrid Systems
• Intrusion Detection Systems
• +۵ مورد دیگر

Dr. Hafizul Asad serves as a Lecturer in Dependability at City St George's, University of London, leveraging his PhD in Electrical Engineering (City University of London, 2016) and MS in Aerospace Engineering (University of Belgrade, 2008) to advance cybersecurity and formal verification research. His expertise bridges critical infrastructure protection and cyber-physical systems security, with significant contributions to IoT/IIoT security frameworks. His educational journey includes: PhD in Electrical Engineering, City, University of London (2012-2016) MS in Aerospace Engineering, University of Belgrade, Serbia (2007-2008) BSc in Electrical and Electronics Engineering, University of Engineering and Technology Peshawar, Pakistan (1999-2003) Asad's research centers on formal verification of hybrid systems and verifiable intrusion detection mechanisms for interconnected environments. He pioneers provably robust security architectures for IoT/IIoT systems, emphasizing mathematical verification to ensure system resilience against cyber threats. His work integrates diversity principles to create defense-in-depth strategies for critical infrastructure, with recent focus on wind turbine cyber-safety and industrial control system protection. Analysis of his 15 most recent publications (2014-2025) reveals an evolution from aerospace applications and analog circuit verification toward cutting-edge cybersecurity for cyber-physical systems. His 2023-2025 work demonstrates increasing specialization in IoT security and formal methods, while maintaining foundational contributions to diversity-based security architectures established in his 2015-2018 research. No scientific awards or prizes are documented in the provided materials, though he maintains professional standing as a British Computer Society member and Higher Education Academy Associate Fellow. Details regarding doctoral student supervision or specific research grants are not disclosed in the source text. His professional trajectory indicates significant project involvement, including the D3S security project at City University of London (2015-2018) and Rolls-Royce-funded Future Systems Simulator development at Cranfield University (2018-2019), though current laboratory affiliations remain unspecified.

• Sports Biomechanics
• Exercise Physiology
• Rowing Performance
• +۴ مورد دیگر

Dr. Mathijs Hofmijster is an Assistant Professor affiliated with the Faculty of Behavioural and Movement Sciences, Physiology Department at Vrije Universiteit Amsterdam, as well as the Amsterdam Movement Sciences (AMS) and the Institute for Brain and Behavior Amsterdam (IBBA). His research focuses on biomechanics and physiology in sports performance, particularly in rowing and cycling. Key areas include power output measurement, neuromuscular adaptations, and training optimization. He teaches courses such as 'Moving Matters in Health' and supervises graduate research in elite athlete performance. Research Interests: Rowing biomechanics and power output analysis Neuromuscular fatigue and training adaptations Para-cycling performance and adapted physical activity Instrumentation for sports performance monitoring Recent work highlights include a 2024 scoping review on elite para-cycling performance and advancements in blade force measurement techniques (2019). His articles explore topics ranging from muscle morphology in Olympic rowers (2018) to real-time feedback systems improving training compliance (2017). He has supervised one PhD thesis and maintains active collaborations in sports science, contributing to UN Sustainable Development Goals related to health and well-being.

Oluwole O. Oniمشاهده پروفایل

مدرس

• Avian Health
• Veterinary Medicine
• Infectious Diseases
• +۹ مورد دیگر

Oluwole O. Oni is a Lecturer in Intensive Animal Health and Production at the University of Surrey's School of Veterinary Medicine. He holds academic qualifications including DVM, MVSc, and PhD. His research focuses on avian and poultry health, with a strong emphasis on infectious diseases, molecular diagnostics, zoonotic transmission, and biosecurity practices. Key studies include avian influenza seroprevalence in Benin, mycoplasma characterization in Nigerian poultry, and the impact of natural toxins like aflatoxin on poultry health. He has also contributed to understanding NDV and Marek's disease virus in Nigeria, and evaluates traditional herbal remedies on animal physiology. Research highlights include the design of efficient PCR primers for rotavirus detection and investigations into the epidemiology of avian pathogens across diverse farming systems. His work underscores the importance of gender-inclusive strategies in biosecurity for smallholder poultry farming in Benin, and he advocates for improved vaccination and diagnostic protocols in resource-limited settings. No scientific awards were explicitly mentioned in the text. His collaborative efforts span international teams, particularly in Nigeria and Ethiopia, and he emphasizes molecular approaches to disease control and poultry management. No specific grants or advisees are listed, but he has conducted studies on poultry vaccines, toxin mitigation, and haemoparasitic infections in livestock.

Yudong Chenمشاهده پروفایل

استادیار

• Changepoint Detection
• High-dimensional Statistics
• Robust Statistics
• +۴ مورد دیگر

Yudong Chen is an Assistant Professor in the Department of Statistics at the University of Warwick, starting September 2024. Previously, he was an LSE Fellow (2023–2024) and a postdoctoral researcher at the London School of Economics. He holds a PhD in Statistics from the University of Cambridge (2023), with a thesis on High-dimensional Online Changepoint Detection, supervised by Richard J. Samworth and Tengyao Wang. His research focuses on changepoint detection, high-dimensional statistics, robust methods, and machine learning. Education: PhD in Statistics, University of Cambridge (2023) MA & MMath in Mathematics, University of Cambridge (2018) BA in Mathematics, University of Cambridge (2018) Teaching: University of Warwick: Module leader for ST420 Statistical Learning and Big Data (2024/25) LSE: Taught ST202/6 Probability, ST447 Data Analysis, and ST449 Artificial Intelligence His research interests span statistical methodologies including online algorithms, robust statistics, and spatial models. He has published in top journals like the Journal of the American Statistical Association and presented at venues such as the IMS Annual Meeting. Awards include the LSE Class Teacher Award (2023) and the Smith–Knight Prize (2020). Grants: Worked on EPSRC-funded research on 'Change-point analysis in high dimensions' at LSE. Labs/Teams: Engaged in collaborative projects on online changepoint detection and statistical methodologies.

• Econometrics
• Agricultural Economics
• Resource Economics
• +۳ مورد دیگر

Zheng Li is an Assistant Professor in the Department of Agricultural and Resource Economics at North Carolina State University. His research focuses on econometric methodologies with applications in agricultural economics, resource management, and policy analysis. He holds expertise in nonparametric estimation, quantile regression, and structural econometric modeling. Key research interests include analyzing agricultural production risks, evaluating policy impacts on housing markets, and developing advanced statistical techniques for mixed data types. His work bridges econometric theory with practical applications in environmental, urban, and transportation sectors. Recent publications explore topics such as lung cancer detection via biomedical sensing technologies, ridesharing platform incentives, and pandemic effects on real estate markets. Methodologically, his contributions span kernel-based specification tests, bootstrap methods for heavy-tailed data, and monotonicity-constrained estimation techniques. No scientific awards or formal advisees are listed. His research often intersects with interdisciplinary challenges, reflecting a commitment to innovative solutions in applied economics and data science.

Damian Nale Dailisanمشاهده پروفایل

مدرس

• Computational Social Science
• Machine Learning
• Multi-Agent Systems
• +۳ مورد دیگر

Dr. Damian Nale Dailisan is a Lecturer in the Department of Humanities, Social and Political Sciences at ETH Zürich, affiliated with the Computational Social Science group. He holds a Ph.D. in Physics from the University of the Philippines, specializing in traffic modeling and machine learning applications. His research focuses on multi-agent systems, particularly in transportation and urban systems. He has held postdoctoral roles and contributed to projects like the ACCeSs@AIM lab. His work bridges computational methods with real-world challenges, including traffic control optimization, AI-driven decision-making, and smart city infrastructure. Notable projects include FAIRLANE for priority lane management and studies on democratizing traffic control systems. Dailisan’s publications span journals like Transportation Research Part C and IEEE Access, addressing topics such as reinforcement learning in traffic signals and ethical AI frameworks. He has presented at workshops like 'Back to the Future' at ETH Zurich and collaborates with interdisciplinary teams to enhance urban mobility solutions. His technical expertise includes Python, network analysis, and agent-based modeling, with contributions to open-source tools for earthquake networks and social systems analysis.

• Immersive Media
• Extended Reality (XR)
• Virtual Reality (VR)
• +۶ مورد دیگر

Prof. Jan-Niklas Voigt-Antons is a Professor of Applied Computer Science specializing in Immersive Media at Hamm-Lippstadt University of Applied Sciences. His work focuses on Extended Reality (XR), Virtual Reality (VR), Augmented Reality (AR), and their applications in healthcare, education, and human-machine interaction. He holds a Dr.-Ing (Engineering Doctorate) and has extensive industry experience with organizations like Daimler AG, Telekom Innovation Laboratories, and the German Research Center for Artificial Intelligence (DFKI). Research interests include user experience (UX) design, emotion analysis in virtual environments, and accessibility for aging populations. He has led projects on wearable health tech, AR/VR usability, and immersive training systems. Notable areas of impact include developing guidelines for inclusive XR interfaces and advancing telemedicine through immersive technologies. Prof. Voigt-Antons has collaborated with Charité – Universitätsmedizin Berlin on healthcare applications and has contributed to standardization efforts in telecommunications. His technical competencies include agile project management, statistical analysis, and mobile application development for iOS/Android. He advises on UX evaluations, usability testing, and physiological data analysis for industry partners. Key achievements include creating the Story Time Dataset for video quality research and developing the ColorTable system for flavor perception studies. His work emphasizes real-world deployment, with projects addressing mobility challenges for seniors in rural areas and improving dementia care through tablet-based interventions.

Luis Novoaمشاهده پروفایل

دانشیار

• Business Analysis
• Management Science
• Supply Chain Management
• +۳ مورد دیگر

Luis Novoa is an Associate Professor in the Department of Computer Information Systems and Business Analytics at James Madison University’s College of Business, where he also contributes to the MBA program. His academic journey includes a Ph.D. in Decision Sciences from The George Washington University (2016), an M.S. and B.S. in Industrial Engineering from Universidad de los Andes (2007 and 2005, respectively). He has held roles such as Assistant Professor at JMU since 2017, Visiting Assistant Professor at The George Washington University (2016–2017), and Instructor at Universidad de los Andes (2007–2011). His research focuses on business analysis, management science, and applied decision analysis under uncertainty, particularly in supply chain management, logistics, education, and healthcare. Notable work includes optimizing automated package sorting systems, developing educational tools like STRATA for operations research assessment, and Bayesian methods for academic motivation analysis in business analytics courses. Recent articles highlight contributions to bike-sharing system decision-making, supply chain curriculum alignment with industry practices, and stochastic optimization in energy systems. His awards include JMU College of Business Distinguished Teacher (2021–2022) and recognition for summer research excellence (2011). Dr. Novoa’s teaching and research emphasize practical applications of analytics, bridging academic theory with real-world challenges in business and public sectors. He has authored or co-authored over 15 peer-reviewed publications spanning operations research, education, and industry case studies.

Samer M. Khanafsehمشاهده پروفایل

استاد پژوهشی

• Navigation Systems
• Aerospace Engineering
• Sensor Integration
• +۵ مورد دیگر

Samer M. Khanafseh is a Research Associate Professor in the Department of Mechanical, Materials, and Aerospace Engineering at Illinois Institute of Technology (IIT), affiliated with the CARNATIONS research group. He holds a Ph.D. in Mechanical and Aerospace Engineering from IIT (2008), an M.S. from IIT (2002), and a B.S. in Mechanical Engineering from Jordan University of Science and Technology (2000). His research focuses on high-accuracy navigation algorithms, cycle ambiguity resolution, fault monitoring, and robust estimation techniques. Key areas include GNSS spoofing detection, integrity risk bounding, and sensor integration for aerospace applications. He is a member of the Institute of Navigation (ION) and the American Institute of Aeronautics and Astronautics (AIAA). His publications span navigation integrity, fault-tolerant systems, and GNSS applications, with notable work on Bayesian fault-tolerant estimators and GNSS spoofing attack detection using aircraft autopilot responses. His work bridges theoretical modeling with experimental validation, such as testing ground-based augmentation systems (GBAS). Awards: Best-of-Session Paper Award, Institute of Navigation (2006) Institute of Navigation 2011 Early Achievement Award Grants/Advising: Active involvement in CARNATIONS research initiatives, though no formal advisee list is provided. Labs/Teams: CARNATIONS (Context-Aware Navigation and Optimal Sensing) research group at IIT.