جستجوی استاد راهنمای دانشگاهی

Bin Yangمشاهده پروفایل

استاد

• Computer Science
• Data Management
• Machine Learning
• +۹ مورد دیگر

Bin Yang is a Professor at the Department of Computer Science, Aalborg University, affiliated with The Technical Faculty of IT and Design. His research focuses on data engineering, artificial intelligence, and machine learning, with emphasis on spatiotemporal data analysis, representation learning, and time series forecasting. He leads projects like aSTEP (spatio-temporal data analytics) and Light-AI for Cognitive Power Electronics. Key contributions include advancements in trajectory data processing, anomaly detection, and lightweight neural architectures. Research interests span machine learning, data mining, intelligent transport systems, and material science applications. Notable awards include the IJCAI 2019 Distinguished PC Member and Sapere Aude Research Leader (2018). He has supervised six PhD students and contributed to over 119 publications. His work is supported by grants from Villum Foundation and EU initiatives. Yang is involved in interdisciplinary collaborations, including data-driven decision-making frameworks and environmental monitoring systems. Labs and teams include the Daisy Center for Data-intensive Systems and AI for the People initiatives. Projects emphasize real-world applications in smart cities, traffic forecasting, and sustainable technologies. His research bridges theoretical foundations with practical implementations in domains like oceanography and crowdsourcing systems.

Saptarshi Debroyمشاهده پروفایل

دانشیار

• Computer Networking
• Network Security
• Big Data Networking
• +۹ مورد دیگر

Saptarshi Debroy is an Associate Professor of Computer Science at Hunter College and a member of the Doctoral Faculties at The Graduate Center, CUNY. He leads the Distributed Systems and Security (DiSSect) Lab and co-leads the CoSSMO Lab, focusing on resilient distributed systems, edge computing, and cyber security. His research addresses challenges in disaster response systems, federated cloud workflows, and moving target defense mechanisms. He holds a PhD in Computer Engineering from the University of Central Florida and has held roles including Post-Doctoral Fellow at the University of Missouri. Education: PhD (Computer Engineering, UCF, 2014), MTech (Distributed & Mobile Computing, Jadavpur University, 2008), BTech (Information Technology, West Bengal University of Technology, 2006) Research Interests His work spans distributed systems, edge/AI-driven networks, cyber security, and resource optimization in disaster scenarios. Key areas include fog computing frameworks for real-time video processing (EFFECT), secure federated workflows (ADON), and MTD-based cloud defense strategies. He emphasizes practical applications like disaster response and healthcare data security. Grants & Awards Recipient of NSF CAREER Award (2020), NSF grants totaling over $1.1M, and Google Research Award. Notable projects include a trusted framework for health incident response (NSF), volunteer edge-cloud resource allocation (NSF), and DDoS mitigation strategies (NSF). Teaching & Service Teaches graduate courses on distributed systems, cloud computing, and networks at CUNY. Serves on NSF review panels and as chair for IEEE/ACM conferences. Leads initiatives like the Cyber Security Summer School for Women to promote diversity in tech. Labs & Collaborations Directs the DiSSect Lab, which develops edge-native systems for disaster response and secure AI. Collaborates with FDNY, perfSONAR, and NSF-funded testbeds like PAWR. Partnerships include projects with bioinformatics and high-performance computing communities (CyVerse, XSEDE).

Arjuna Madanayakeمشاهده پروفایل

دانشیار

• Multidimensional systems
• Wireless communications
• Array processing
• +۷ مورد دیگر

Arjuna Madanayake is an Associate Professor in the Department of Electrical & Computer Engineering at Florida International University (FIU), part of the College of Engineering. His research focuses on multidimensional systems, wireless communications, array processing, and analog computing. He holds a Ph.D. from the University of Calgary and B.S. from the University of Moratuwa, Sri Lanka. Dr. Madanayake's work emphasizes low-complexity algorithms for multi-beam beamforming, RF sensing, and FPGA implementations. His lab (RAND Lab) develops innovative solutions in terahertz communications, spectrum intelligence, and AI-driven signal processing. He teaches EEL 5500 Digital Communication Systems and collaborates on projects involving reconfigurable intelligent surfaces and 5G/6G technologies. His recent publications (2020–2025) address challenges in ultra-broadband communication systems, analog computing for PDEs, and spectrum management. He has contributed to IEEE journals and conferences, focusing on practical implementations in hardware and software-defined radio platforms.

Hadi Mardani Kamaliمشاهده پروفایل

استادیار

• VLSI design
• Hardware security
• FPGA design
• +۳ مورد دیگر

Hadi Mardani Kamali is an Assistant Professor at the University of Central Florida (UCF) in the Department of Electrical and Computer Engineering . His research focuses on VLSI design and testing , Hardware security and trust , FPGA design , Electronic design automation (EDA) , and Applied machine learning in hardware contexts. Dr. Kamali is actively engaged in research projects related to IC/IP protection , security-aware EDA , and security of learning models .

• Wireless Communications
• Satellite Communications
• RF and Microwave Engineering
• +۵ مورد دیگر

Dr. Viktor Doychinov is a Lecturer in Electronics and Software Engineering at the University of Bradford, affiliated with the Bradford-Renduchintala Centre for Space AI. His academic journey includes a BEng in Telecommunications from Sofia Technical University, an MSc in Spacecraft Technology from University College London, and a PhD in Electronic and Electrical Engineering from the University of Leeds. He previously worked as a postdoctoral researcher in robotics at Leeds' Institute of Robotics, Autonomous Systems, and Sensing. His research focuses on wireless communications, satellite systems, and millimeter-wave technologies. Key areas include nanosatellite transceiver hardware, mesh networks for robotics/satellites, and open-source tools for space engineering. He also explores applications in resource-constrained environments like exploration robotics and biomedical devices. Teaching responsibilities include modules on embedded electronics, digital signal processing, satellite communications, and space mission design across undergraduate and postgraduate programs such as BEng/MEng Biomedical Engineering and MSc Satellite Systems Engineering. He actively engages in STEM outreach through roles like Transpennine Hub Ambassador and has received an RAEng Ingenious grant. Education: BEng (Telecom), MSc (Spacecraft Tech), PhD (Electronic Engineering) Professional Skills: RF/microwave design, SDR prototyping, robotics frameworks (ROS2/MAVLink), C/Python programming Outreach: STEM Ambassador, RAEng grant recipient (2020/21) His 19 publications span topics like wireless energy harvesting, antenna design, and underground robotics communication. He collaborates with industry on projects such as the Pipebots infrastructure inspection system and space mission simulation using STK/GMAT software.

Samuel Mulderمشاهده پروفایل

دانشگاهی

• Cyber Security
• Program Analysis
• Reverse Engineering
• +۲ مورد دیگر

Samuel Mulder is an Associate Research Professor in the Department of Computer Science and Software Engineering at Auburn University. He holds a Ph.D. in Computer Science from Missouri S&T, along with an M.S. and B.S. in Computer Science from Missouri S&T and Texas Tech University, respectively. His research focuses on cybersecurity, program analysis, reverse engineering, adversarial analysis, and machine learning applications. He is affiliated with the Center for Artificial Intelligence and Cybersecurity Engineering within the College of Engineering. His research interests include developing immersive virtual reality techniques for binary reverse engineering, modeling adversarial competition in satellite communication systems (P-LEO constellations), and enhancing cybersecurity through dynamic defense mechanisms like moving target defense. He has contributed to frameworks for tracking cyber adversaries using adaptive indicators of compromise and improving solver algorithms for constraint satisfaction problems. Mulder's work spans both theoretical advancements (e.g., neuromorphic computing surveys) and applied solutions (e.g., supply chain binary program assessments). His recent efforts emphasize gamification of competitive cybersecurity scenarios and embodied cognition approaches to software analysis. While no scientific awards are explicitly listed, his contributions reflect impactful work in cybersecurity innovation. He collaborates with Auburn's engineering research centers, particularly in AI-driven cybersecurity solutions. His advising and grant activities are not detailed in the provided text, but his research aligns with Auburn's focus on interdisciplinary engineering challenges.

• Human-Computer Interaction
• Medical Informatics
• Digital Health
• +۴ مورد دیگر

Rebecca Randell is Professor of Digital Innovations in Healthcare at the University of Bradford . Previously, she held roles at the University of Leeds (Senior Translational Research Fellow, Lecturer, Associate Professor), University of York , and City University London . She founded the Health Technologies for Quality & Safety research group and directs the Centre for Digital Innovations in Health & Social Care . Education: BSc in Software Engineering (Durham University), PhD in Human-Computer Interaction (Glasgow University, 2004) Her research focuses on the social aspects of healthcare IT design , including medical handover practices, histopathology diagnostics, and multidisciplinary team collaboration. She examines how nurses customize ICU equipment, use decision support systems, and how novel hardware affects GP-patient communication. Her work emphasizes qualitative methods and realist evaluation , with applications in virtual reality for pathology teaching and AI adoption in healthcare. Recent publications highlight AI workload impacts in radiology, EPR systems in ICU during pandemics, and digital tools for cancer referrals. She leads NIHR-funded projects on robotic surgery, clinical dashboards, and falls prevention systems. Scientific Awards: 1 unspecified award She has advised on healthcare fieldwork ethics, clinical audit data use, and strategic workforce planning. Her lab collaborates with the National Pathology Imaging Cooperative and the NIHR Yorkshire & Humber Patient Safety Research Collaboration .

Yanjie Chenمشاهده پروفایل

استاد مهمان

• Robotics
• Computer Vision
• Control Systems
• +۳ مورد دیگر

Yanjie Chen is a Visiting Professor in the Department of Computer Science at Aberystwyth University. Their research focuses on robotics, computer vision, control systems, and artificial intelligence, with notable contributions in aerial manipulators, neural architecture search, and fuzzy logic systems. Chen holds the prestigious Newton International Fellowship since 2022. In robotics, Chen explores advanced control strategies for unmanned aerial vehicles and manipulators, addressing challenges like dynamic tracking, impedance control, and environmental disturbances. Their work in AI emphasizes optimization techniques for neural networks, including pruning and architecture search, enhancing computational efficiency. In computer vision, Chen develops attention-based mechanisms for super-resolution tasks. Key Achievements: Recipient of the Newton International Fellowship (2022) High-impact publications in IEEE Transactions and Springer venues Collaborations with institutions like Fuzhou University and Hunan University Chen’s research bridges theory and application, with practical solutions for robotics, autonomous systems, and AI-driven image processing.

• FPGA Neural Networks
• Robotic Locomotion
• Pattern Recognition
• +۱ مورد دیگر

Dr. Horacio Rostro González is an Assistant Professor in the Department of Industrial Engineering at IQS School of Engineering, Ramon Llull University. His research focuses on neural network implementations using field-programmable gate arrays (FPGAs), with applications in robotics, motor imagery systems, and industrial automation. Research Focus: Development of hardware-accelerated AI systems for pattern recognition, robot locomotion control, and human-machine interfaces. Key projects include neuromorphic computing for spatio-temporal classification and AI-driven photonics parameter optimization. Projects: Member of the Industrial Engineering Research Group (GEPI), working on offshore wind farm data analysis using machine learning and renewable energy prediction systems.

Hussein Abdeltawabمشاهده پروفایل

استادیار

• Power system modernization
• Smart grid technologies
• Energy management
• +۱۰ مورد دیگر

Hussein Abdeltawab is an Assistant Professor specializing in power system modernization and smart grid technologies. His research integrates artificial intelligence with energy systems to improve grid operation and planning. Education Ph.D. in Electrical Engineering (2017), University of Alberta MSc in Electrical Engineering with distinction (2012), Cairo University BSc in Electrical Engineering with distinction (2012), Cairo University Research Focus His work addresses: Smart grid technologies and renewable energy integration Energy storage optimization and distributed resources Deep learning applications for multi-carrier systems Transportation-energy infrastructure synergy (e.g., smart highways) He leads the Intelligent Power and Energy Management Lab, focusing on AI-driven energy solutions. Publications Trends His research spans 2012–2024, with recent works emphasizing: Neural architecture search for hybrid energy systems Wildfire resilience in distribution grids Piezoelectric energy harvesting for smart infrastructure Deep reinforcement learning for EV battery stations Hydrogen-infrastructure integration frameworks

Michel Barbeauمشاهده پروفایل

استاد

• Wireless Communications and Networking
• Underwater Communications
• Quantum Communications
• +۴ مورد دیگر

Michel Barbeau is a Professor and Director at the School of Computer Science, Carleton University. He holds a Ph.D. in Computer Science from Université de Montréal (1991) and has held academic roles at Université de Sherbrooke (1991–1999) and a visiting position at the University of Aizu, Japan. His research focuses on non-classical wireless networks, including underwater acoustic communication systems, quantum networks, and resilience assessment of cyber-physical systems. He leads projects involving acoustic signal processing, underwater node communication, and challenges like multipath propagation in aquatic environments. His team tested prototypes in Ottawa’s Rideau Canal. His work spans underwater communication protocols, quantum encryption, and AI-driven network optimization. He is active on YouTube and Twitter, and his ORCID profile highlights interdisciplinary contributions. His research emphasizes practical applications in environmental monitoring, coastal navigation, and secure quantum communication frameworks. Education: Ph.D. Computer Science, Université de Montréal (1991) M.Sc. Computer Science, Université de Montréal (1987) B.Sc. Computer Science, Université de Sherbrooke (1985) Research Interests: Underwater Acoustic Networks Quantum Communications and Cryptography Cyber-Physical Systems Resilience Ad Hoc and Mobile Networks Machine Learning for Network Optimization His current projects address challenges such as signal interference in underwater environments and developing quantum-safe cryptographic algorithms. Collaborations involve interdisciplinary teams of students and researchers. Advancement and Grants: Lead projects on underwater surveillance systems Explores quantum encryption protocols for post-quantum security Investigates AI-driven solutions for UAV and MIMO networks Labs and Teams: His research group focuses on experimental prototyping, including underwater acoustic networks and quantum communication frameworks. Collaborations span academia and industry for real-world applications.

Gabriel A. Wainerمشاهده پروفایل

استاد

• Discrete-Event Modeling and Simulation
• Real-Time Systems
• Cellular Models
• +۴ مورد دیگر

Professor Gabriel A. Wainer holds a Ph.D. from the Universidad de Buenos Aires and is a Full Professor at Carleton University's Department of Systems and Computer Engineering, Faculty of Engineering and Design. His research focuses on Discrete-Event Modeling and Simulation (DEVS), Real-Time Systems, and Parallel/Distributed Simulation. He leads the Advanced Real-Time Simulation (ARS) Lab at Carleton's V-Sim Centre, collaborating with industry partners like Ericsson Canada on projects such as channel reconstruction for wireless networks and AI-driven spectrum sharing. Wainer is a Fellow of the Society for Modeling and Simulation International (SCS) and an ACM Distinguished Speaker, with over 450 publications and significant grant funding. He has mentored numerous students and researchers, contributing to Carleton's academic and research excellence. Education: Ph.D. (Computer Science, Universidad de Buenos Aires, 1998), M.C.S. (Universidad de Buenos Aires, 1993). He has held visiting roles at institutions worldwide, including INRIA and the University of Nice. Research interests include DEVS formalism, cellular models, and real-time operating systems. His work bridges theory and application, addressing challenges in embedded systems, IoT, and pandemic modeling. Awards include the McLeod Founder Award (2022), SCS Outstanding Professional Achievement (2020), and IEEE Outstanding Engineering Award (2019). Labs/Teams: Advanced Real-Time Simulation Lab (ARS), part of Carleton's V-Sim Centre. Grants: Over $4.3M as PI and $1.2M as co-applicant, totaling $30M+ in collaborative funding. Advising: Supervised 12 postdocs, 19 PhDs, 16 RAs, 71 MSc students, and 150+ undergrads since 1997.

Shashank Agnihotriمشاهده پروفایل

پژوهشگر

• Adversarial Robustness
• Out-of-Distribution (OOD) Robustness
• Neural Architecture Search
• +۵ مورد دیگر

Shashank Agnihotri is a Researcher & PhD Candidate at the Chair for Machine Learning within the Data and Web Science Group at the University of Mannheim. He is affiliated with the School of Business Informatics and Mathematics . His research focuses on adversarial and OOD robustness of vision models, pixel-wise prediction tasks, and neural architecture search. He has contributed to projects like CosPGD (an efficient adversarial attack for pixel-wise tasks) and Improving Feature Stability during Upsampling . Education: PhD Candidate in Computer Science, University of Mannheim (2023–Present) PhD Candidate in Computer Science, University of Siegen (2022–2023) MSc. Computer Science, Albert-Ludwigs Universität Freiburg (2018–2021) B.E. Computer Engineering, VESIT, University of Mumbai (2014–2018) Research Interests: Adversarial and OOD robustness of deep learning models Sensor layout optimization and task-specific camera parameters Signal processing impact on model reliability Neural architecture search (NAS) methodologies Publications & Awards: Published at ICML, ECCV, ICCV, NeurIPS, and ICCP Outstanding Reviewer (CVPR 2025) and Notable Reviewer (ICLR 2025) Organized the 45th DAGM German Conference on Pattern Recognition (GCPR 2023) Labs & Collaborations: Part of the Machine Learning Group at Mannheim and previously at the Machine Learning Group in Freiburg under Prof. Frank Hutter and Prof. Thomas Brox.

Dirk Pflügerمشاهده پروفایل

استاد

• Scientific Computing
• High-Performance Computing (HPC)
• Parallel and Distributed Systems
• +۳ مورد دیگر

Dirk Pflüger is a Professor at the University of Stuttgart's Institute of Parallel and Distributed Systems, within the Faculty of Computer Science, Electrical Engineering and Information Technology. His research focuses on high-performance computing (HPC), parallel and distributed systems, and sparse grids. He has led projects in astrophysical simulations, machine learning applications, and uncertainty quantification. Notable contributions include developing scalable algorithms for exascale computing using HPX, Kokkos, and SYCL frameworks. His expertise spans distributed computing architectures, task-based parallel programming, and interdisciplinary applications in astrophysics and medical AI. Recent work includes optimizing hyperparameter tuning, simulating stellar mergers, and enhancing blood glucose prediction models using deep reinforcement learning. Pflüger's research emphasizes performance portability, fault tolerance, and cross-platform collaboration. He has contributed to open-source tools like PLSSVM and hws, which address hardware monitoring and GPU acceleration challenges. His work bridges theoretical advancements with practical implementations for real-world computational problems.

Dieter Schmalstiegمشاهده پروفایل

استاد

• Augmented Reality
• Virtual Reality
• Computer Graphics
• +۲ مورد دیگر

Dieter Schmalstieg is the Alexander von Humboldt Professor of Visual Computing at the University of Stuttgart's Faculty 5: Computer Science, Electrical Engineering and Information Technology, leading the Institute for Visualization and Interactive Systems (VIS). He also holds an adjunct professorship at Graz University of Technology's Institute of Computer Graphics and Vision. His research focuses on augmented reality (AR), virtual reality (VR), computer graphics, visualization, and human-computer interaction. He earned his Dipl.-Ing. (1993), Dr. techn. (1997), and Habilitation (2001) from Vienna University of Technology. He has authored/co-authored over 400 peer-reviewed publications, with over 29,000 citations and numerous awards, including the IEEE ISMAR Career Impact Award (2020) and the IEEE Virtual Reality Technical Achievement Award (2012). His professional roles include editorial leadership in top journals like IEEE Transactions on Visualization and Computer Graphics, and steering committee memberships in major conferences like IEEE ISMAR. Research interests span AR/VR applications, situated visualization, coherent rendering, spatial interaction, and medical visualization. Notable projects include the Christian Doppler Laboratory for Handheld Augmented Reality (2008–2015), and collaborations with industry partners like Qualcomm and VRVis. He has advised over 50 PhD students, many now professors or researchers globally. Grants include the Alexander von Humboldt Professorship (2023), SNAP Mixed Reality Lab funding, and EU projects like MiReBooks (mining education). His work bridges theory and application, with impactful contributions to AR/VR systems, medical visualization tools, and GPU techniques for real-time rendering.