جست‌وجوی استاد و پژوهشگر

• Internet of Things (IoT)
• Wireless Communication Systems
• Machine Learning Applications
• +۴ مورد دیگر

Domenico Garlisi is a Researcher (INFO-01/A) at the Department of Mathematics and Computer Science, University of Palermo. His work focuses on wireless communication systems, IoT, and network security. University: University of Palermo Department: Mathematics and Computer Science Email: domenico.garlisi@unipa.it His research explores LoRaWAN/Sigfox coexistence, 5G vulnerabilities, and AI-driven smart water distribution systems. Recent projects include SWI-FEED for large-scale IoT deployment and Edge2LoRa for distributed processing. The 15 most recent publications (2025-2024) highlight trends in 5G jamming attacks, massive IoT scalability, edge computing integration, and machine learning applications for water network monitoring. Key subfields include signal interference analysis, digital twins, and smart city infrastructure.

• Cognitive and brain science
• Neuroscience
• Motor learning
• +۲ مورد دیگر

Professor Rieko Osu at Waseda University's Faculty of Human Sciences is a leading researcher in cognitive neuroscience and motor learning. Affiliated with the OSU Lab , her work spans neuroimaging, brain stimulation, and rehabilitation science. Doctoral Degree in biomedical research Expert in fMRI/EEG/TMS methodologies Director of 20+ cross-cultural autism studies Key research areas include: Neural mechanisms of problem-solving with Frontiers in Human Neuroscience (2025) findings on inferior frontal gyrus activation Cortical plasticity in motor skill acquisition with tDCS/tSMS applications (2024 studies in Scientific Reports and Frontiers in Behavioral Neuroscience ) Comparative analysis of social interaction patterns in ASD populations across eight countries (2024 Molecular Autism study) Recent publications focus on: Theta-band inter-brain synchronization in weak social ties Stress reduction through ASMR stimulation protocols Wrist somatosensory priming effects on hand choice Neurofeedback training efficacy for attentional control Scientific recognition includes: Waseda University's Leading Research Award (2025) ICONIP Best Paper Award (2007) Japanese Neural Network Society Research Award (2002) Her laboratory develops validated tools like the MORE scale for stroke patient motivation assessment, with applications in 200+ patient studies and cross-cultural comparisons. Current work combines computational models (MOSAIC) with clinical interventions for motor recovery optimization.

• Milk production
• Fertility in cows
• Reproduction in dairy cattle
• +۲ مورد دیگر

Prof. Dr. Wolfgang Heuwieser is a faculty member at the Free University of Berlin , specializing in Veterinary Medicine with a focus on Milk production, Fertility in cows, and Reproduction . He works at the Veterinary Clinic for Reproduction , where his research and clinical practice address critical aspects of dairy cattle health and reproductive efficiency. His research interests include Bovine Reproductive Health , Dairy Cow Fertility , and Animal Health Management . Heuwieser's work integrates advanced technologies such as automated activity monitoring , point-of-care diagnostics , and computer vision systems to optimize reproductive outcomes and general wellness in dairy cattle. Recent publications highlight his expertise in Hormonal Treatments , Heat Stress Impact , and Calving Management . His studies span 2017 to 2025 , reflecting ongoing contributions to veterinary science and dairy farming practices. Heuwieser can be contacted via email at w.heuwieser@fu-berlin.de for collaborations, expert consultations, or further information about his research projects.

Benoit Pirandaمشاهده پروفایل

دانشیار

• Distributed Algorithms
• Modular Robotics
• Programmable Matter
• +۴ مورد دیگر

Benoit Piranda is an Associate Professor of Computer Science at the University of Franche-Comté , affiliated with the FEMTO-ST Institute and its Complex Networks Team (DISC/OMNI) . He leads the development of VisibleSim , a parallel behavioral simulator for modular robots. University: University of Franche-Comté Institute: FEMTO-ST Team: DISC/OMNI Role: Researcher & Software Developer Research Focus: Distributed algorithms for modular robots, programmable matter, physical simulations, and parallel execution environments. His work spans self-reconfiguration, communication protocols, and efficient scene encoding for large-scale robotic systems. Article Trends: Recent publications highlight advancements in 2D/3D lattice modular robot algorithms Porous structure reconfiguration Time synchronization protocols VisibleSim simulation framework Multi-scale distributed displays Security protocols for programmable matter Conference Involvement: Active in program committees for DARS, IEEE ATC, IROS, and AINA. Former Publicity Chair positions.

Tiago Cogumbreiroمشاهده پروفایل

استادیار

• Concurrency Theory
• Parallel Programming
• Formal Methods
• +۶ مورد دیگر

Tiago Cogumbreiro is an Assistant Professor at the University of Massachusetts Boston, where he has been a faculty member since Fall 2018. His research focuses on advancing the foundations of parallel programming through rigorous quality assurance of languages and runtimes. Dr. Cogumbreiro received his PhD from the University of Lisbon (ULisboa) in March 2015 under Francisco Martins, where he developed techniques to handle barrier deadlocks including the Armus runtime verification tool. His educational background includes a B.Sc. from Universidade dos Açores, followed by research assistant work at Imperial College London (supervised by Nobuko Yoshida) and postdoctoral research at Georgia Tech and Rice University (supervised by Vivek Sarkar). As an expert in formal methods for high-performance computing, Dr. Cogumbreiro's work centers on detecting concurrency errors in parallel programs with special emphasis on GPU systems. His research spans theoretical contributions to deadlock avoidance policies and practical applications of Coq and Why3 for certified algorithms. Recent work demonstrates sophisticated approaches to static analysis of data-races in GPU programming, addressing fundamental challenges in parallel system reliability. His publication pattern reveals a consistent trajectory from foundational work on futures-based deadlock avoidance (2017) through behavioral type systems (2019) to current innovations in GPU program analysis (2023-2024). These contributions form a cohesive research program focused on mathematically rigorous approaches to parallel system correctness. Dr. Cogumbreiro actively contributes to the programming languages community through committee service at major conferences including PLDI (2020 Artifact Evaluation), SPLASH (2025 OOPSLA Review Committee), and PPoPP. His GitHub activity shows ongoing development of formal verification tools, particularly Coq-based projects like gorn-coq and habanero-coq that implement his theoretical contributions.

• Electrical Engineering
• Diagnostics of Electrical Machines
• Induction Motor Diagnostics
• +۴ مورد دیگر

Jarosław Tulicki serves as a Lecturer at the Department of Electrical Engineering within the Faculty of Electrical and Computer Engineering at Cracow University of Technology. Having recently completed his doctorate in 2024, he specializes in electrical machine diagnostics with emphasis on induction motor fault detection through non-invasive techniques. His research focuses on rotor cage damage diagnostics using stator current spectrum analysis and axial flux signal processing under steady-state conditions. Key contributions include methodologies for detecting rotor asymmetries in double-cage induction motors and developing diagnostic systems for industrial applications like tramway drive systems. His work bridges theoretical electromagnetic modeling with practical condition monitoring solutions. Tulicki's publication record demonstrates consistent research progression from fundamental electromagnetic analysis (2015-2018) toward applied diagnostic systems (2019-2024). The most recent works emphasize double-cage motor diagnostics and real-time implementation, showing strong technical depth in signal processing and system integration. His research consistently targets industrial applicability while maintaining rigorous theoretical foundations. With 27 publications yielding an h-index of 4 in both Scopus and Web of Science, his scholarly impact is reflected in a total ministerial score of 497 within the Polish academic evaluation system. His ORCID profile (0000-0003-1720-3448) documents this active research trajectory.

An H Doمشاهده پروفایل

دانشیار

• Brain-Computer Interfaces
• Neurorehabilitation
• Spinal Cord Injury
• +۷ مورد دیگر

An H Do, MD is an Associate Professor in the Department of Neurology at the University of California, Irvine School of Medicine . His research focuses on advanced neurotechnologies for restoring motor and sensory functions post-injury. Academic Affiliation: UCI School of Medicine, Department of Neurology Key Research Areas: Brain-Computer Interfaces, Neurorehabilitation, Spinal Cord Injury, Stroke Recovery, Implantable Neuroprosthetics Research Interests Dr. Do develops bi-directional brain-computer interfaces (BD-BCIs) that enable cortical control of robotic exoskeletons while delivering sensory feedback via direct cortical stimulation. His work emphasizes fully implantable systems, high-gamma signal processing, and motor recovery post-stroke or spinal cord injury. Current studies explore home-based rehabilitation using wearable grip sensors and adaptive gaming systems. Article Trends His publications highlight advancements in Bi-directional neural interfaces for motor-sensory restoration High-density electrocorticography (ECoG) for improved decoding accuracy Charge-balanced cortical stimulation safety protocols Home rehabilitation systems with quantitative compliance analysis Implantable BCI designs for clinical translation

Yilu Liuمشاهده پروفایل

استاد

• Power Systems
• Smart Grids
• Grid Monitoring
• +۵ مورد دیگر

Yilu Liu serves as the UT-ORNL Governor's Chair Professor at the University of Tennessee's Tickle College of Engineering, holding a joint appointment with Oak Ridge National Laboratory. She is deputy director of the Center for Ultra-wide-area Resilient Electric Energy Transmission Networks (CURENT), a DOE/NSF engineering research center focused on modernizing America's power grid infrastructure. Liu earned her B.S. in Electrical Engineering from Xi'an Jiaotong University (China), followed by M.S. and Ph.D. degrees from The Ohio State University. Before joining UT in 2009, she was faculty at Virginia Tech where she directed its Center for Power Engineering. Her pioneering research centers on power grid monitoring, stability, and resilience. Liu developed the North American power grid Frequency Monitoring Network (FNET/GridEye) - the first continent-wide system using over 300 Frequency Disturbance Recorders to monitor grid health in real-time. Her work addresses critical challenges in renewable energy integration, grid inertia estimation, electromagnetic pulse protection, and time synchronization for smart grids. Recent research focuses on low-inertia systems, forced oscillations, and HEMP vulnerability assessment. Liu's publications show consistent innovation in power systems monitoring, with recent work spanning 2024-2025 covering time synchronization techniques, pulsar-based timing, inertia estimation, and electromagnetic protection. Her research demonstrates strong focus on practical grid applications while addressing emerging challenges from renewable integration and cyber-physical security threats. R&D 100 Award (2022) for FNET/GridEye R&D 100 Award (2021) for GridDamper technology R&D 100 Award (2018) for Mobile Universal Grid Analyzer R&D 100 Award (2014) for Continuously Variable Series Reactor IEEE Power & Energy Society Wanda Reder Pioneer in Power Award (2020) Member of National Academy of Engineering Fellow of IEEE and National Academy of Inventors NSF Presidential Faculty Fellow (1994) NSF Young Investigator Award (1993) Liu leads CURENT (with 35 industry members) and has secured significant DOE and NSF funding. Her former students nominated her for the IEEE Wanda Reder Award, highlighting her mentorship impact. She has published over 500 articles and one book, with research directly influencing grid operations through technologies adopted by NERC, FERC, and power companies. Liu also established FNET/GridEye as a critical monitoring platform used across North America. As deputy director of CURENT, Liu collaborates with industry partners and researchers across multiple institutions. Her team at UT-ORNL focuses on developing next-generation grid monitoring technologies, with recent projects addressing electromagnetic pulse vulnerabilities and solar grid integration challenges in Saudi Arabia.

Abby Marshمشاهده پروفایل

دانشیار

• Usable Privacy and Security
• Digital Privacy
• Human-Computer Interaction
• +۳ مورد دیگر

Abby Marsh is an Associate Professor in the Department of Mathematics, Statistics, and Computer Science at Macalester College, currently on sabbatical during the 2025-2026 academic year. Her research centers on making online privacy usable and accessible, with a focus on marginalized populations including families with teenagers and online fandom communities. Education: Ph.D. in Societal Computing, Carnegie Mellon University, 2018 B.A. in Computer Science and Mathematics (double major), Oberlin College, 2013 Professor Marsh's work in usable privacy investigates how privacy tools can accommodate under-studied groups through empirical user studies and theoretical frameworks. She pioneers research on digital privacy norms within transformative fandom communities and develops inclusive security solutions for educational settings. Her approach emphasizes learning from existing practices of online groups with complex privacy behaviors, challenging traditional assumptions in the field. Analysis of her 2023-2024 publications reveals a concentrated shift toward boundary management in online communities, particularly fandom spaces, while expanding into assistive technology privacy in education. This builds upon her foundational work on family privacy dynamics, demonstrating consistent focus on real-world privacy challenges faced by vulnerable populations. Scientific Awards: No awards listed in the provided information Advising and Academic Service: Marsh actively mentors undergraduate researchers including Dan Bially Levy, Kien Nguyen, and Aron Smith-Donovan. She teaches core courses such as Object-Oriented Programming (COMP 127), Computer Systems (COMP 240), and Computer Security and Privacy (COMP 487), while maintaining comprehensive student resources for MSCS majors. She also coordinates Macalester's fiber artists community group, demonstrating interdisciplinary engagement beyond traditional CS boundaries. Research Context: During her doctoral work at Carnegie Mellon, Marsh was affiliated with the CUPS Lab within CyLab. Her current research continues this collaborative tradition, focusing on community-driven privacy solutions while leveraging her background in both technical systems and social computing.

Shangping Renمشاهده پروفایل

استاد

• Cyber-Physical Systems
• Real-Time Scheduling
• Cloud Computing
• +۴ مورد دیگر

Shangping Ren is a Professor and Department Chair at the Department of Computer Science, San Diego State University (SDSU), within the College of Sciences. She earned her Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign in 1997. Research focus areas: Cyber-Physical Systems, Real-Time Scheduling, Cloud Computing, Medical Cyber-Physical Systems, Software Architecture, and Resource Optimization Key projects: EMBG System for Emergency Care, Medical Best Practice Guideline Modeling, Real-Time Task Scheduling, and Many-Core Virtualization Her recent publications emphasize medical cyber-physical systems (e.g., safety verification, implicit assumption detection) and real-time scheduling (e.g., rejuvenation techniques, resource degradation). She also explores cloud computing for DAG applications and mobile low-power sensing via Bluetooth/RFID. Grants: Funded by NSF, Air Force Research Laboratory, and Fermi National Accelerator Laboratory. Current projects include data science workforce training, medical guidance systems, and water infrastructure analytics. Collaborations: Works with Lui Sha, Chunhui Guo, Zheng Li, and institutions like University of Illinois, Yale University, and National Science Foundation.

Guido Salvaneschiمشاهده پروفایل

استاد

• Programming Languages
• Software Engineering
• Distributed Systems
• +۵ مورد دیگر

Guido Salvaneschi is a Professor and Head of the Programming Group at the Institute of Computer Science within the School of Computer Science at the University of St. Gallen, Switzerland. His work bridges theoretical foundations with practical applications in programming languages and software engineering, with a particular focus on distributed systems and infrastructure as code. His research interests span programming languages, software engineering, distributed systems, reactive programming, DevOps organizations, and secure software systems. He has made significant contributions to multitier programming languages, consistency models for distributed applications, and infrastructure as code testing frameworks. Salvaneschi's recent publications reveal a strong focus on infrastructure as code analysis and testing, with multiple papers accepted at top conferences in 2024-2025. His work demonstrates a consistent thread connecting programming language theory with practical systems challenges, particularly in cloud and distributed environments. His Programming Group at the University of St. Gallen includes several PhD students and researchers working on cutting-edge topics in software systems. Current projects include Consistency Programming for Local First Software (an SNF project), HORIZON-RIA for European edge computing infrastructure, and Multitier Programming above the Clouds (another SNF project). As an active member of the research community, Salvaneschi serves on program committees for major conferences including ASE, PLDI, and ICSE, demonstrating his standing within the programming languages and software engineering fields.

Alexander Silchenkoمشاهده پروفایل

پژوهشگر

• Neuroscience
• Neuromodulation
• Computational Biology
• +۳ مورد دیگر

Dr. Alexander Silchenko is a Senior Researcher at the Forschungszentrum Jülich, affiliated with the Institute of Neuroscience and Medicine (INM) within the Brain and Behaviour (INM-7) department. His work focuses on neuromodulation techniques, computational modeling of neural systems, and the application of mathematical frameworks to understand neurological disorders. Key areas include effective connectivity analysis in brain networks, acoustic coordinated reset therapy for tinnitus and Parkinson’s disease, and modeling glial responses to neural implants. His research integrates experimental and theoretical approaches, with publications addressing topics such as stochastic dynamics, neural synchronization, and neuroinflammation. Notable contributions include studies on long-term effects of coordinated reset stimulation and computational models of chemotaxis around implanted electrodes. Dr. Silchenko’s interdisciplinary work bridges neuroscience, biomedical engineering, and mathematical biology. He has authored over 40 peer-reviewed articles, emphasizing translational research between computational models and clinical applications. Current efforts involve developing novel neuromodulation protocols and understanding the biophysical mechanisms underlying phantom sound perception and neurodegenerative processes.

Saman Amarasingheمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Computer Architecture
• +۵ مورد دیگر

Professor Saman Amarasinghe is a leading academic in the MIT Electrical Engineering and Computer Science Department, specializing in compiler design, high-performance computing, and programming languages. His research bridges theoretical computer science with practical applications, focusing on optimizing compilers for modern hardware architectures. He holds a professorship within the School of Engineering at MIT. His research interests span artificial intelligence, machine learning integration into compilers, sparse tensor algebra optimizations, and domain-specific languages (DSLs) for high-performance computing. He has pioneered frameworks like TACO (Tensor Algebra Compiler) and GraphIt, which enable efficient handling of complex data structures across diverse computational domains. Recent work emphasizes compiler-driven optimizations for sparse data formats, machine learning models for code optimization, and unified interfaces for large language models. His projects often address scalability challenges in exascale computing and bioinformatics applications. Publications highlight advancements in compiler techniques for sparse tensor operations, graph analytics, and memory-efficient algorithms. His contributions to Halide, Simit, and Weld further demonstrate his impact on DSLs for image processing and physical simulation. Awards and recognitions are integral to his career, though specific personal accolades are not detailed here. His work is characterized by a strong focus on practical compiler solutions for emerging computational challenges.

• Rehabilitation Robotics
• Machine Learning
• Neuromechanics
• +۳ مورد دیگر

Yue Wen is an Assistant Professor at the University of Central Florida. His research focuses on rehabilitation robotics, machine learning, neuromechanics, and human-robot interaction. He holds a Ph.D. in Biomedical Engineering from the University of North Carolina at Chapel Hill and North Carolina State University, an M.S. in Control Theory and Engineering from Huazhong University of Science and Technology, and a B.S. in Automation from Wuhan University of Technology. His work integrates neural engineering and robotics to develop adaptive prosthetic systems and rehabilitation technologies. Key areas include real-time neural drive estimation using deep learning, haptic collaboration in motor tasks, and reinforcement learning for personalized prosthesis control. Recent studies explore exoskeleton interaction dynamics and virtual physical coupling in lower-limb robotics. Yue Wen has received the UNC/NC State Research Assistant Scholarship (2014–2019) and was a finalist in the EMBC Student Paper Competition (2015). His research bridges biomechanics, machine learning, and clinical applications, with a focus on improving gait symmetry and user interaction in robotic prosthetics.

• Digital Communications
• Signal Processing
• Wireless Communications
• +۵ مورد دیگر

Colin Murphy is a Lecturer in the Department of Electrical and Electronic Engineering at University College Cork (UCC). He holds a B.E. (Gold Medal for academic excellence), M.Eng.Sc. (modelling of microwave transformers), and Ph.D. (wavelet packet modulation analysis) from UCC. His research focuses on digital communications, signal processing for cognitive radios, GNSS signal acquisition, and FPGA-based cryptographic countermeasures. Education: B.E. (1989), M.Eng.Sc. (1991), Ph.D. (2006), all from UCC. He has supervised numerous PhD students including Niamh O'Mahony, Donagh Horgan, and Robert McEvoy. Awards include the CEIA Gold Medal (1989) and the CogART 2011 Best Paper Award. Research interests span signal processing for cooperative/cognitive radios, weak signal GNSS tracking, and cryptographic hardware security. He has led projects funded by IRCSET and Enterprise Ireland, including work on FPGA-optimised transforms and spectrum sensing algorithms. Teaching includes modules like EE2007 Electronic Circuits and EE6105 Wireless Communications. He chairs UCC's School of Engineering Outreach Committee, promoting engineering studies through school visits and annual quizzes.