جستجوی استاد راهنمای دانشگاهی

Ehsan Esfahaniمشاهده پروفایل

دانشیار

• Artificial Intelligence in Engineering
• Human-Machine Interaction
• Robotics
• +۴ مورد دیگر

Ehsan Esfahani is an Associate Professor and Director of Graduate Studies in the Department of Mechanical and Aerospace Engineering at the University at Buffalo's School of Engineering and Applied Sciences. He is affiliated with the Stephen Still Institute for Sustainable Transportation and Logistics. His research focuses on AI-driven robotics, human-machine interaction, and bio-mechatronics systems. Education: PhD in Mechanical Engineering, University of California, Riverside (2012) MS in Electrical Engineering, University of California, Riverside (2012) MS in Mechanical Engineering, University of Toledo (2007) BS in Mechanical Engineering, Isfahan University of Technology (2004) Research Interests: Brain-computer interfaces for CAD/robotic systems Human-robot collaboration and neuroergonomics Bio-inspired robotics and tactile sensing Swarm intelligence and multi-agent systems Variable stiffness actuators for safe manipulation Key Contributions: Esfahani's work bridges AI with physical systems, emphasizing real-time human-in-the-loop control. Recent trends in his publications focus on scalable swarm robotics, human-swarm interaction dynamics, and adaptive gripper designs for confined environments. His neurophysiological approaches assess cognitive load in collaborative tasks, enhancing system safety and efficiency. Awards: American Power Public Associations DEED Scholarship (2012) UC Riverside Dissertation Year Fellowship (2011–2012) Lung-Wen Tsai Memorial Scholarship (2010) Advising & Labs: Directs the HILS Lab (Human-Inspired Learning Systems), exploring human-centered robotics. Active in grants focusing on AI-driven factories, cognitive modeling in surgery, and variable stiffness mechanisms. Collaborates on projects like SHaSTA (Human-Swarm Team Simulator) and MyoTrack rehabilitation systems. Labs & Teams: HILS Lab: Human-AI collaboration frameworks Stephen Still Institute: Transportation logistics and sustainability

Kevin Jonesمشاهده پروفایل

استاد

• Cyber Security
• Maritime Technology
• Risk Management
• +۳ مورد دیگر

Professor Kevin Jones is the Deputy Vice-Chancellor for Research and Innovation and Executive Dean of the Faculty of Science and Engineering at the University of Plymouth. His primary focus is maritime cyber security, leading the Maritime Cyber Threats Research Group and the Cyber-MAR network, a €7M European initiative enhancing maritime cyber preparedness. He oversees pioneering facilities like the Cyber-SHIP Lab and the Marine Navigation Centre, which test cyber defenses for maritime systems. His research integrates cyber security, autonomous systems, and policy development, addressing vulnerabilities in global shipping, offshore energy, and port operations. Collaborations span industry and academia, including US Coast Guard panels and policy influence at national/international levels. Jones supervises 5 PhD students and advocates for interdisciplinary approaches to cyber safety culture and human factors in autonomous maritime systems. Education background: Not explicitly detailed in provided texts, but his academic role as Professor and Dean suggests advanced qualifications in Computing Science or related fields. Research emphasizes maritime cyber risks, with contributions to risk mitigation frameworks, cost-benefit analyses for energy infrastructure, and malware detection in IoT systems. His work bridges technical innovation with policy, aiming to secure critical maritime infrastructure against evolving cyber threats. Key Projects: Cyber-SHIP Lab, Maritime Cyber Threats Research Group, Cyber-MAR network Focus Areas: Autonomous ship security, port resilience, cyber-physical systems Policy Contributions: Influencing maritime cyber governance and safety standards Research trends show a focus on quantifying cyber risks, developing adaptive security solutions, and addressing socio-technical challenges in autonomous systems. Recent publications highlight vulnerability analysis in IoT, satellite communications, and voyage data recorders. His work underscores the economic impacts of cyber attacks on global trade and the need for robust mitigation strategies. Advising 5 PhD students and leading interdisciplinary teams, Jones fosters innovation in cyber security training, digital twin technologies, and forensic readiness. Grants and partnerships support his mission to create resilient maritime infrastructure through cutting-edge research and industry collaboration.

Yan Zhaoمشاهده پروفایل

دانشیار

• Anomaly Detection
• Autoencoder
• Attention (Machine Learning)
• +۵ مورد دیگر

Yan Zhao is an Associate Professor in the Department of Computer Science at Aalborg University, Denmark, affiliated with The Technical Faculty of IT and Design. His research focuses on data engineering, science, and systems, with a particular emphasis on anomaly detection, machine learning, and spatio-temporal data analysis. He holds a Ph.D. in Computer Science (specific education details not explicitly provided). Research Interests: Dr. Zhao's work spans anomaly detection, autoencoders, attention mechanisms, preference learning, multivariate time series, and computational efficiency. His research often integrates machine learning with real-world applications in spatial crowdsourcing, trajectory analysis, and data privacy. Publications: With 72+ publications, his recent work emphasizes spatio-temporal prediction frameworks, federated learning, and efficient time series analysis. Notable contributions include frameworks for continuous learning on streaming data and privacy-preserving clustering in spatial crowdsourcing. Grants & Supervision: He has supervised one Ph.D. student and actively contributes to research grants focusing on data engineering and smart systems. His work bridges theoretical advancements with practical applications in transportation, social networks, and IoT.

Gianvito Pioمشاهده پروفایل

دانشیار

• Data Mining
• Bioinformatics
• Social Network Analysis
• +۳ مورد دیگر

Gianvito Pio is an Associate Professor at the Department of Computer Science, University of Bari Aldo Moro, Italy. His research spans data mining, bioinformatics, social network analysis, multi-relational data mining, and big data analytics. He holds a PhD in Computer Science from the University of Bari (2015) and has taught courses such as Big Data Management and Analysis and Security in Blockchain Technology . As an expert in heterogeneous network analysis, he develops methods for anomaly detection in cryptocurrency trends, microbiome data interpretation, and legal judgment clustering. He leads the local research unit of the PRIN 2022 project COCOWEARS and contributes to journals like the Machine Learning Journal and Expert Systems with Applications as an associate editor. His recent work includes multi-view learning for risk identification in dynamic networks, spatially-aware models for energy forecasting, and biclustering algorithms for biological data. Collaborations with researchers such as Michelangelo Ceci and Antonio Pellicani highlight his interdisciplinary approach. Gianvito Pio also organizes academic events like the Discovery Science conference and contributes to open-source software tools including HOCCLUS2 and GENERE .

Zhu Hanمشاهده پروفایل

استاد

• Game Theory
• Wireless Networking
• Security
• +۴ مورد دیگر

Dr. Zhu Han is the John and Rebecca Moores Professor at the University of Houston's Cullen College of Engineering, Department of Electrical and Computer Engineering. His research focuses on game theory, wireless networking, security, data analysis, and smart grid applications. He holds doctoral and master's degrees from the University of Maryland and a bachelor's from Tsinghua University. Research interests span: Next-generation wireless systems (6G/7G) AI/ML integration in communications Reconfigurable intelligent surfaces Quantum machine learning applications Secure and efficient network architectures His recent publications demonstrate strong focus on generative AI integration in wireless systems, quantum networking, semantic communications, and security frameworks for future networks. Awards and honors include: IEEE/ACM/AAAS Fellow status IEEE Kiyo Tomiyasu Award (2021) Highly Cited Researcher since 2017 IEEE Distinguished Lecturer (2015-2018) Dr. Han leads research in wireless communications and networking, with extensive industry collaboration. His lab focuses on developing theoretical foundations and practical implementations for next-generation communication systems.

Reza Salkhordehمشاهده پروفایل

مدرس

• Operating Systems
• Solid-State Drives
• Data Storage Systems
• +۵ مورد دیگر

Reza Salkhordeh is a Lecturer and Postdoctoral Researcher at Johannes Gutenberg University Mainz, Germany, where he leads the Efficient Computing and Storage Group. He holds a Ph.D. in Computer Engineering from Sharif University of Technology (2018) and has been affiliated with Ferdowsi University of Mashhad and Sharif University of Technology. His research focuses on operating systems, storage systems, and non-volatile memory technologies, with a particular emphasis on high-performance computing and I/O optimization. He has taught courses such as Storage Systems and Advanced Topics in Operating Systems since 2020. His academic journey includes a B.Sc. from Ferdowsi University (2011), M.Sc. and Ph.D. from Sharif University (2013, 2018). He has held roles such as Technical Lead for the High-Performance Data Storage System (HPDS) project in Tehran, Iran, and has mentored 4 M.Sc. and 6 B.Sc. students. His work spans patented technologies like Reconfigurable Cache Architectures and Load Balancers for I/O caching systems. Research interests include heterogeneous memory management, storage system design, and optimizing I/O performance in distributed environments. His recent publications address challenges in NVMM utilization, garbage collection in SSDs, and I/O tracing for HPC systems. He is actively involved in conference committees (e.g., FAST, ARCS, SC) and has reviewed for top journals like IEEE TPDS and ACM Transactions on Storage. Notable recognitions include membership in Iran’s National Elites Foundation (2012–2015) and top rankings in national exams (3rd in PhD, 35th in MSc). His contributions to storage systems have advanced enterprise-grade architectures and decentralized file systems, with a focus on practical implementations for modern computing challenges.

• Human-Computer Interaction
• Ubiquitous Computing
• Computational Materials
• +۳ مورد دیگر

Sai Swaminathan is an Assistant Professor in the Min H. Kao Department of Electrical Engineering and Computer Science at the University of Tennessee. He earned his PhD from Carnegie Mellon University's Human-Computer Interaction Institute, advised by Scott Hudson. His research focuses on computational materials, ubiquitous computing, and cyber-physical systems, emphasizing low-power, embedded technologies in physical infrastructure. He leads the EPIC Lab, exploring interactive systems integrated into structural materials like concrete and carbon fiber. Education: PhD from Carnegie Mellon University (Human-Computer Interaction Institute). Prior to this, he completed a dual master’s degree at Technical University of Berlin and Universite Paris-Sud XI. Professional experience includes roles at Oak Ridge National Lab, Microsoft Research, and Xerox Research. Research Interests: Developing battery-free interactive devices using non-silicon materials (e.g., concrete, carbon fiber), integrating sensing/actuation into architectural structures. Current projects include OptiStructures (optical sensors in building materials), Duco (large-scale circuit writing), and FiberWire (composite electronics). Notable Awards: Best Paper Honorable Mention at CSCW 2019 for 'Learn2Earn: Using Mobile Airtime Incentives to Bolster Public Awareness Campaigns'. Labs/Teams: Director of the Energy, Printed Infrastructure and Interactive Computing (EPIC) Lab, collaborating with interdisciplinary teams in HCI, ECE, CEE, and Materials Science.

Antonio Calomarde Palominoمشاهده پروفایل

دانشیار

• Low Power Digital Circuits
• Soft Error Resilient Circuits
• Integrated Circuit Design
• +۴ مورد دیگر

Antonio Calomarde Palomino is an Associate Professor at the Department of Electronic Engineering, Polytechnic University of Catalonia (UPC), located at the Higher Technical School of Industrial Engineering of Barcelona. He holds a B.S. in Telecommunications Engineering (UPC, 1986), an M.S. in Electronic Engineering (Universitat Autònoma de Barcelona, 1993), and a Ph.D. in Electronic Engineering (UPC, 2007) with honors. His research focuses on low-power/high-performance digital circuits and soft-error resilient designs, addressing challenges in semiconductor technology and radiation-hardened electronics. Key research areas include FinFET-based memory cells, RRAM modeling, and radiation mitigation strategies for advanced nanoelectronics. He contributes to the High Performance Integrated Circuits and Systems Design (HIPICS) Group, advancing circuit design methodologies and educational initiatives such as integrating autonomous vehicle systems into undergraduate curricula. His work bridges theoretical advancements with practical applications in automotive electronics and embedded systems. Publications span topics from memristor-based associative memory to approximation techniques in object detection systems, reflecting a balance between fundamental research and applied engineering. His recent work emphasizes variability-aware design and energy-efficient architectures, as seen in 2023-2024 studies on RRAM models and automotive case studies. Calomarde actively organizes academic events like the 2022 ETS conference and develops educational materials for digital electronics and audiovisual systems courses. His contributions to both technical research and pedagogical innovation solidify his role as a key figure in electronic engineering education and innovation.

Shuang Liuمشاهده پروفایل

پژوهشگر

• Embedded Systems
• Computer Architecture
• Networks-on-Chip (NoC)
• +۳ مورد دیگر

Shuang Liu is a Researcher at the Institute of Computer Architecture and Computer Engineering, University of Stuttgart. Their work focuses on embedded systems, networks-on-chip (NoC), and chip design methodologies. They specialize in deadlock-free routing, fault-tolerant computing, and application-specific system synthesis using advanced techniques like integer linear programming. Research interests include optimizing NoC architectures for chiplet-based systems, co-design of floorplanning and routing topologies, and energy-efficient signal processing in medical electronics. Their recent work emphasizes formal verification methods and performance optimization in hardware-software co-design. Publications span topics such as deadlock prevention in NoC, ILP-based routing synthesis, and trade-offs in hearing aid ASIP design. Office hours are Monday 2–3 p.m. in Room 1.001, Pfaffenwaldring 5b, Stuttgart.

Sandra Cespedesمشاهده پروفایل

استادیار

• Wireless Networks
• Internet of Things (IoT)
• Vehicular Networking
• +۶ مورد دیگر

Sandra Cespedes is an Assistant Professor at Concordia University's Department of Computer Science & Software Engineering within the Gina Cody School of Engineering and Computer Science. She previously held roles as an Associate Professor and Head of Research at NIC Chile Research Labs, Universidad de Chile, and maintains an honorary Adjunct Professorship at Universidad Icesi, Colombia. She is also an Associate Researcher at the Advance Center of Electrical and Electronic Engineering (AC3E), Chile. Education: B.Eng. (Telematics Engineering) and Specialization (Management of Information Systems), Universidad Icesi, Colombia (2003, 2007) Ph.D. (Electrical and Computer Engineering), University of Waterloo, Canada (2012) Research Interests: Her research focuses on wireless networks, IoT, vehicular communications, and satellite networking. Key areas include: Design of protocols for constrained IoT devices Vehicular safety systems and cooperative communication Direct-to-satellite IoT (DtS-IoT) architectures Rural connectivity solutions Publications: Her recent work explores satellite IoT protocols, vehicular network optimization, and distributed hypothesis testing. Notable contributions include MAC protocol design for satellite IoT and safety message dissemination in VANETs. Teaching: At Concordia, she teaches undergraduate courses like Data Communications and Computer Networks and Embedded Systems , and graduate courses such as Computer Networks and Protocols . Previously, she taught wireless networking and IoT development at Universidad de Chile.

jessie beierمشاهده پروفایل

استادیار

• Post-human Methods in Art Education
• Critical Pedagogy
• Environmental Justice Education
• +۳ مورد دیگر

jessie beier is an Assistant Professor in Art Education at Concordia University, working at the intersection of art, philosophy and pedagogy. Their research-creation practice focuses on developing 'weird pedagogies' to reconceptualize educational futurity amidst ecological crises. Research explores post-human methods, critical disability studies, queer theory, and AI's role in education. Research Focus: Challenges conventional educational paradigms through multidisciplinary approaches including energy humanities, extinction studies, feminist science and technology studies (STS), and speculative design. Recent work examines pedagogical responses to the Anthropocene, de-extinction ethics, and sonic environments as educational spaces. Publications: 15 recent works demonstrate consistent exploration of crisis epistemology, alternative futurities, and pedagogical experimentation. Article analysis reveals strong thematic focus on: Anthropocene education (73%), speculative pedagogies (67%), posthuman ethics (60%), environmental aesthetics (53%), and critical futurism (47%).

Véronique VEQUEمشاهده پروفایل

استاد

• Wireless Networks
• Vehicular Networks
• Network Routing
• +۳ مورد دیگر

Véronique VEQUE is a Professor at CentraleSupélec, working within the L2S research laboratory. Her research focuses on networking technologies including wireless networks, vehicular networks, and satellite communications. She specializes in developing efficient routing protocols, mobility management systems, and energy optimization techniques for next-generation networks. Dr. Veque's current research examines flexible resource allocation in disaggregated RAN architectures, intelligent routing algorithms for dense WiFi networks, and predictive modeling for IoT congestion control. Her work combines theoretical modeling with practical implementations for telecommunications systems. Her publication record spans network architecture design, mobility modeling, routing optimization, and energy-efficient communication. Recent work has focused on Open-RAN functionality placement, Cloud-RAN resource allocation, and stochastic mobility modeling for urban environments.

James Lawمشاهده پروفایل

پژوهشگر

• Human-Robot Collaboration
• Trustworthy Autonomous Systems
• Responsible Innovation
• +۳ مورد دیگر

Dr. James Law serves as a Senior Experimental Officer at Sheffield Robotics and leads the Collaborative Robotics Group within the School of Computer Science at the University of Sheffield. He holds a joint appointment between the Department of Computer Science and the Advanced Manufacturing Research Centre, and serves as Director of Innovation and Knowledge Exchange at Sheffield Robotics. His work integrates academic research with industrial applications in advanced manufacturing. His research focuses on human-robot collaboration, trustworthy autonomous systems, and responsible innovation in manufacturing robotics. Law develops safety assurance frameworks and digital twinning solutions for collaborative workspaces, with particular emphasis on trust engineering, user authentication, and graphical communication systems that reduce human anxiety in robot co-working environments. His interdisciplinary approach bridges computer science, engineering psychology, and industrial implementation requirements. Law's publication portfolio demonstrates consistent advancement in collaborative robotics safety, with recent work (2022-2024) focusing on verified safety controllers, digital twin frameworks, and trust modeling in human-robot triads. His research shows progression from foundational developmental robotics (2010-2015) toward applied industrial solutions, with increasing emphasis on security, safety assurance, and human factors in manufacturing contexts. As an active science communicator, Law serves on the UK Robotics and Autonomous Systems network (UK-RAS) management board and the EPSRC Early Career Forum in Manufacturing Research. EPSRC STAMAN: Robotic skill transfer for manufacturing (Co-PI, £1M+) Horizon Europe OpenSwarm: Energy-aware swarm orchestration (Co-PI, £463k) EPSRC Security of Digital Twins in Manufacturing (Co-PI, £775k) EPSRC UKRI Trustworthy Autonomous Systems Node (Co-PI, £3M) Law leads the Collaborative Robotics Group and contributes to the Complex Systems Modelling research group, focusing on translating theoretical safety frameworks into practical industrial implementations through close collaboration with manufacturing partners and policy stakeholders.

Andrew Westمشاهده پروفایل

پژوهشگر

• Robotics
• Nuclear Engineering
• Radiation Detection
• +۳ مورد دیگر

Andrew West is a researcher affiliated with the University of Manchester, contributing to the Dalton Nuclear Institute. His work focuses on advancing robotics and autonomous systems for nuclear environments, particularly in radiation detection, mobile robot navigation, and hazardous environment exploration. Key areas include radiation mapping, sensor integration, and risk assessment in nuclear facilities. He has developed specialized robots like CARMA II and Vega for nuclear surveying and decommissioning tasks. Collaborations span international institutions such as JSI and LUNL, with datasets publicly available via Figshare. His research aligns with UN Sustainable Development Goals related to sustainable energy and industry innovation. Education: Background in robotics and nuclear engineering, though specific degrees are not detailed in the text. Research interests emphasize the practical application of robotics in nuclear decommissioning, including real-time radiation avoidance, sensor fusion, and multi-robot ecosystems. His work bridges theoretical modeling (e.g., Gaussian process regression) with practical field deployments, ensuring robots can safely operate in high-risk environments. Publications highlight advancements in radiation localization, sensor calibration (e.g., angular responses), and safety protocols for autonomous systems. The top-cited works focus on multimodal sensing and digital twin platforms for nuclear robot fleets, showcasing industry-academia partnerships. Grants & Projects: Contributions to projects like TORONE (Total Characterisation of Nuclear Environments) and the development of open-source platforms like Mona robot. West’s lab focuses on creating affordable, robust robotic solutions for nuclear challenges, with datasets publicly accessible to foster collaborative research.

Laura Balzanoمشاهده پروفایل

دانشیار

• Machine Learning
• Optimization
• Signal Processing
• +۷ مورد دیگر

Laura Balzano is an Associate Professor of Electrical Engineering and Computer Science at the University of Michigan, with a courtesy appointment in the Department of Statistics within the College of Literature, Science, and the Arts. Her research focuses on optimization, machine learning, and signal processing, particularly in high-dimensional data analysis, subspace learning, and low-rank structures. She holds affiliations with the Department of Statistics and is located at 323 West Hall, Ann Arbor, MI. Contact information includes girasole@umich.edu . Her work bridges theoretical foundations and practical applications, addressing challenges in heterogeneous data, online learning, and robust algorithms. Key research areas include subspace clustering, tensor decomposition, and model compression for deep learning systems. Recent contributions explore dynamic networks, control theory integration, and energy-efficient algorithms for large-scale models. Laura Balzano's publications span topics like PCA variants for noisy data, optimization on Riemannian manifolds, and neural collapse analysis. Her methods emphasize scalable solutions for real-time applications, such as energy disaggregation and medical imaging. While no explicit awards are listed, her extensive publication record reflects recognition in her field. Advising and grant details are not provided in the available text.