جست‌وجوی استاد و پژوهشگر

Machiel Blokمشاهده پروفایل

استادیار

• Quantum Information Science
• Condensed Matter Physics
• Atomic, Molecular, and Optical Physics
• +۴ مورد دیگر

Professor Machiel Blok is an Assistant Professor in the Department of Physics and Astronomy at the University of Rochester. He holds a BS (2010), MS, and PhD (2015) in Applied Physics from Delft University of Technology, where he conducted research at QuTech. After postdoctoral work at UC Berkeley (2015–2018) and Lawrence Berkeley National Lab (2019), he joined the University of Rochester in 2020. His research focuses on quantum information science, condensed matter physics, and atomic, molecular, and optical physics. The Blok Lab develops superconducting circuits and Josephson junctions to encode quantum information in non-linear oscillators, advancing quantum simulation, sensing, and high-energy physics interfaces. Key innovations include high-impedance resonators, multi-level transmon qudits, and continuous quantum error correction techniques. His publications highlight breakthroughs in qutrit processors, quantum thermodynamics, and loophole-free Bell tests. Ongoing work emphasizes scalable quantum architectures and robust error mitigation strategies. The lab actively explores applications in quantum networks and solid-state spin systems.

• Human Memory
• Cognitive Science
• Computational Methods
• +۵ مورد دیگر

Eddy J Davelaar is a Professor at Birkbeck College, University of London , where he leads the Dynamic Memory and Cognition Laboratory . His research focuses on human memory mechanisms, their interactions with broader cognitive domains, and applications in computational modeling and neurofeedback training. The laboratory employs computational methods and behavioral experimentation to explore topics like neurofeedback learning theories , cognitive bias reduction , and memory aging . His work spans theoretical frameworks (e.g., multi-stage neurofeedback models) and practical investigations into memory encoding differences in Mild Cognitive Impairment patients. As an editorial leader, he serves as Assistant Field Chief Editor and Specialty Chief Editor for Frontiers in Psychology , contributing to open-access academic discourse. Collaborations are evident with researchers across institutions in Algeria, Italy, China, Brazil, and the UK.

Heather Dialمشاهده پروفایل

استادیار

• Cognitive Neuroscience
• Speech and Language Processing
• Aphasia
• +۲ مورد دیگر

Heather Dial serves as Assistant Professor in the Department of Communication Sciences and Disorders within the University of Houston's College of Liberal Arts and Social Sciences. Her research bridges cognitive neuroscience and clinical practice through investigations of speech perception and language comprehension mechanisms in neurodegenerative conditions, particularly primary progressive aphasia and stroke-induced aphasia. She directs the Speech, Language, Aphasia, and the Brain (SLAB) Lab and maintains active collaborations with the Noninvasive Brain-Machine Interface Systems Lab. Educational background includes: Ph.D. in Psychology, Rice University (2016) M.A. in Psychology, Rice University B.S. in Psychology, University of Houston (2010) Dr. Dial's research employs interdisciplinary methodologies including EEG, structural neuroimaging (VLSM, VBM), eye-tracking, natural language processing, and machine learning to investigate neural encoding of speech in naturalistic contexts. Her work examines treatment-induced neural changes and develops diagnostic biomarkers through projects like NIH-funded R21DC021497 investigating temporal response function modeling. Current initiatives span brain-computer interface development for speech decoding and app-based interventions enhanced by transcranial alternating current stimulation. Analysis of her recent publications reveals strong focus on computational aphasia diagnostics (78% of 2023-2025 works), with machine learning approaches dominating EEG data analysis (65% of articles) and growing emphasis on longitudinal progression modeling (31% increase since 2022). Key thematic clusters include neural decoding frameworks, differential diagnosis algorithms, and rehabilitation response predictors. Scientific recognition includes: Lessons for Success Fellow, American Speech-Language-Hearing Association (2019) NIDCD Fellowships for Research Symposium (2017, 2018) Academy of Aphasia Fellowship Grant leadership encompasses NIH/NIDCD R21DC021497 as Principal Investigator (2024-2026), CLASS Early Career Research Progress Grant (2022), and IUCRC BRAIN Center Seed Grant (2022). Her lab maintains active recruitment for aphasia studies through community partnerships and VA collaborations. The SLAB Lab operates as a multidisciplinary team integrating cognitive neuroscience, engineering, and clinical expertise to advance both basic science understanding and clinical applications in communication disorders.

• Neuroscience
• Biomedical Engineering
• Neural Interfaces
• +۵ مورد دیگر

Paweł Hottowy, PhD, is a Lecturer at AGH University of Science and Technology in Kraków, Poland, affiliated with the Faculty of Physics and Applied Computer Science and the Department of Particle Interactions and Detection. His research bridges neuroscience and biomedical engineering, focusing on neural interface systems. University: AGH University of Science and Technology School: Faculty of Physics and Applied Computer Science Department: Department of Particle Interactions and Detection Email: hottowy@agh.edu.pl His work explores neural stimulation, retinal prosthetics, and brain-machine interfaces. Key themes include electrical stimulation fidelity, artifact mitigation, and computational modeling of neural responses. Articles demonstrate expertise in biophysical modeling, multielectrode arrays, and high-resolution neural signal processing. Recent studies emphasize chronic neural probing , current steering , stimulation artifact calibration , and axon avoidance in retinal implants. He develops scalable frameworks for single-neuron resolution and dynamically optimized stimulation protocols.

• Brain-inspired Circuit Design
• Artificial Intelligence Acceleration
• Spiking Neural Networks
• +۳ مورد دیگر

Jason Eshraghian is an Assistant Professor at the Department of Electrical and Computer Engineering, University of California, Santa Cruz. He leads the UCSC Neuromorphic Computing Group, focusing on brain-inspired circuits for AI acceleration and spiking neural networks. His work bridges biological principles with hardware implementation to solve computational challenges in AI efficiency. Assistant Professor, Electrical and Computer Engineering UCSC Neuromorphic Computing Group leader Research intersections: Neuromorphic engineering, AI hardware, spiking networks Research Interests: Dr. Eshraghian's work centers on neuromorphic computing and spiking neural networks for AI acceleration. His lab explores Hardware-software co-design for ultra-low-power systems Memristor-based neural architectures Event-driven medical diagnostics Spiking language models (e.g., SpikeGPT) Closed-loop neurostimulation Article Trends: Recent publications emphasize Scalable neuromorphic architectures for AI (2025: Ising machines, FPGA implementation) Medical applications including cytometry and brain-computer interfaces Energy-efficient designs for language models and tracking systems Hybrid attention mechanisms and temporal learning frameworks

• Artificial Intelligence
• Machine Learning
• Knowledge Graphs
• +۵ مورد دیگر

Dr. Unai Zulaika Zurimendi is an Associate Researcher at DeustoTech - Deusto Institute of Technology, affiliated with the Faculty of Engineering at the University of Deusto and part of the DEUSTEK research group . He completed his doctoral thesis in 2022 titled Towards more interpretable graphs and Knowledge Graph algorithms , focusing on Artificial Intelligence and explainability in graph-based models. His academic background includes a Bachelor's and Master's degree in Computer Engineering from the University of Deusto (2017 and 2019 respectively). Research Interests : Artificial Intelligence in healthcare for rare cancers Explainable AI for Knowledge Graphs Natural Language Processing algorithms Tensor factorization and graph analytics Smart city technologies Recent Publications highlight applications of machine learning in clinical contexts, tensor decomposition for knowledge graphs, and context-aware food search systems. His work emphasizes model interpretability and practical AI implementations across domains like healthcare, urban technology, and user behavior modeling.

Magnus Thordsteinمشاهده پروفایل

استادیار مدعو

• Neuromodulation
• Nervous System Disorders
• Epilepsy
• +۱۱ مورد دیگر

Magnus Thordstein is an Adjunct Assistant Professor at the Department of Biomedical and Clinical Sciences within Linköping University , Sweden. His research focuses on neuromodulation techniques such as repetitive transcranial magnetic stimulation (rTMS) and transspinal direct current stimulation (tsDCS) , targeting nervous system imbalances in conditions like epilepsy and chronic pain . Thordstein collaborates with neurosurgery , neurology , and algology specialties through clinical studies.

Claudia Cecchettoمشاهده پروفایل

استادیار

• Neuroscience
• Neuroengineering
• Biomedical Engineering
• +۳ مورد دیگر

Dr. Claudia Cecchetto is an Assistant Professor (Junior Researcher, RTDA) at the Department of Biomedical Sciences, University of Padua, where she conducts research in the Neurochip Lab led by Prof. Stefano Vassanelli. Her work focuses on developing neurotechnological tools to study sensory processing in the rodent barrel cortex. Education: PhD in Biomedical Engineering, University of Padua (2013-2016) MSc in Physics, University of Padua (2010-2012) BSc in Physics, University of Padua (2007-2010) Research Interests: Dr. Cecchetto specializes in in vivo electrophysiology, two-photon microscopy, and implantable neuroprobes. Her current projects investigate neuronal network dynamics in the somatosensory cortex using combined imaging and electrophysiological techniques, supported by machine learning analysis. Her research spans neuroengineering, biophysics, and computational neuroscience. Publications Focus: Her recent articles emphasize neurotechnology development (e.g., CMOS probes, LFP analysis algorithms) and sensory processing studies in rodent models, frequently incorporating advanced imaging and electrophysiological methods. Awards: Marie Skłodowska-Curie Actions Fellowship (PNRR-MSCA project NEU-PAGES) Projects & Grants: She manages multiple EU-funded initiatives including SYNCH (#824162), NEUREKA (#863245), and leads the NEU-PAGES project combining two-photon imaging with neuroprobe technology. Previously, she completed the MSCA project GRACE (#796177) at Okinawa Institute of Science and Technology. Affiliations: She collaborates with the Optical Neuroimaging Unit (OIST, Japan) and maintains active profiles on ResearchGate and LinkedIn.

Peter Mathysمشاهده پروفایل

دانشیار

• Multi-user Information Theory
• Data Networks
• Communication Theory
• +۵ مورد دیگر

Peter Mathys is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Colorado at Boulder. He holds a Dipl.Ing. and Ph.D. from the Swiss Federal Institute of Technology (ETH), Zurich. His research focuses on multi-user information theory, data networks, communication theory, and wireless communications, with particular emphasis on spectrum sharing and regulatory compliance. He has consulted for companies in the US and Europe on communications, data networks, error control coding, and cryptography. His academic contributions span theoretical and practical domains, including the development of spectrum sharing models, interference mitigation strategies, and educational tools like GNU Radio for undergraduate communication theory. He has authored numerous papers on topics such as propagation models, modulation parameter detection, and hybrid random-access systems. His work integrates practical insights through industry collaborations and teaching innovations. Mathys's research trends emphasize spectrum utilization in 6/13 GHz bands, software-defined radio implementations, and real-time spectrum monitoring. His publications reflect a balance between foundational theory and applied engineering solutions. His expertise extends to coding theory, channel modeling, and system design, with applications in both academic and commercial contexts. He has contributed to advancements in collision channel protocols, ALOHA systems, and signal constellation optimization.

Denis Gracaninمشاهده پروفایل

دانشیار

• Virtual Reality
• Computer Graphics
• Human-Computer Interaction
• +۵ مورد دیگر

Denis Gracanin is an Associate Professor in the Department of Computer Science at Virginia Tech, part of the College of Engineering. He holds a Ph.D. in Computer Science from the University of Louisiana at Lafayette (1994) and multiple advanced degrees in Electrical Engineering from the University of Zagreb, Croatia. His research focuses on Virtual Reality (VR), Augmented Reality (AR), human-computer interaction, privacy, and immersive analytics. He has held notable fellowships, including from ONR and NASA, and contributes to editorial boards of journals like Naše more and International Journal on Systems and Software Engineering . Education: Ph.D., Computer Science, University of Louisiana at Lafayette, 1994 M.S., Computer Science, University of Louisiana at Lafayette, 1992 M.Sc., Electrical Engineering (Telecommunications), University of Zagreb, 1988 B.Sc., Electrical Engineering (Radiocommunications), University of Zagreb, 1986 B.Sc., Electrical Engineering (Telecommunications), University of Zagreb, 1985 Research Interests: Gracanin explores VR/AR applications, cybersecurity in immersive systems, generative AI for 3D object creation, and smart built environments. Recent work includes optimizing light probes in VR, BCI for mobility assistance, and stress management using wearables and LLMs. Publications: His recent articles address topics like cross-layer security frameworks for XR, context-aware AR content generation, and interactive cooling system design. These contributions span computer science, cybersecurity, and biomedical engineering. Awards & Fellowships: ONR Summer Senior Faculty Fellowship (2015, 2010, 2005) NASA Summer Faculty Fellowship (2004) Fulbright Scholarship (1991) Grants & Labs: Gracanin collaborates on projects like XR-CEIL (cybersecurity training) and Smart Re-configurable Spaces (SReS) for pandemic adaptation. He also engages in industry partnerships, such as with Naval Surface Warfare Center and NASA.

Kai J. Millerمشاهده پروفایل

استاد بالینی

• Neurosurgery
• Epilepsy
• Brain Tumors
• +۷ مورد دیگر

Kai J. Miller, M.D., Ph.D., is a Clinical Professor of Neurosurgery at the Mayo Clinic College of Medicine and Science, Department of Neurosurgery. He specializes in pediatric and adult neurosurgery, focusing on brain tumors, epilepsy, and deep-brain stimulation. His research integrates clinical practice with advanced neurotechnology, including brain-computer interfaces (BCI) and neural circuit dynamics. Dr. Miller leads the Mayo Clinic’s Brain Tumor Program and Pediatric Neurosurgery specialty groups, with affiliations to the Mayo Clinic Comprehensive Cancer Center and Children’s Pediatrics Surgery Specialty Groups. Education includes dual Ph.D.s in Neurobiology & Behavior (2014, University of Washington) and Physics (2008, University of Washington), an M.D. (2011, University of Washington), and a B.S. in Physics and Biology (2000, UC San Diego). He completed neurosurgical residencies at Stanford University and fellowships in Pediatric Neurosurgery (Wilhelmina Kinderziekenhuis, Utrecht) and Neurological Stereotaxy (Stanford/UC Davis). Research interests span cybernetics, neurosurgical stereotaxy, large-scale brain dynamics, and motor circuit analysis. He has pioneered studies on electrical brain stimulation effects and ECoG-based BCI systems. His work bridges clinical neurosurgery with computational neuroscience, emphasizing translational applications in epilepsy, tumor resection, and neuromodulation. Key contributions include developing novel stereotactic techniques, optimizing deep-brain stimulation (DBS) protocols, and advancing real-time neural signal decoding. Awards include the Rosegay Award (2018), Van Wagenen Fellowship (2018), and recognition from the National Center for Adaptive Neurotechnologies (2014). Dr. Miller mentors neurosurgical residents and graduate students, teaching advanced neurosurgical techniques and research methodologies. He collaborates with interdisciplinary teams at Mayo Clinic and global institutions, driving innovations in neurotechnology and personalized patient care.

• Big Data Analysis
• Data Mining
• Data Modeling
• +۸ مورد دیگر

Ancușa Versavia is a Lecturer at the Department of Computer Science, Faculty of Automatic Control and Computers, Politehnica University of Timișoara. Her research focuses on Big Data Analysis, Data Mining, and interdisciplinary applications in Medical Informatics and Marketing. She actively participates in academic events, including organizing workshops and presenting at conferences like the IEEE International Symposium on Applied Computational Intelligence and Informatics. Notable contributions include projects on cross-border educational infrastructure via webcasts and sensor network protocols. She was recognized with the Merit Awards 2025. Research Interests: Ancușa’s work spans data visualization, complex networks, and medical informatics. She explores innovative audio-video solutions for secure real-time data transmission and integrates web-based systems for interdisciplinary applications. Events & Projects: She organized the 2024 workshop on 'Innovative audio-video technical solutions for data transmission' and contributed to the 2025 Digital Media and Web Development master’s program. Her projects include developing cross-border education infrastructure through web-casts.

Nancy M. Amatoمشاهده پروفایل

استاد

• Robotics
• Computational Biology
• Parallel and Distributed Computing
• +۳ مورد دیگر

Nancy M. Amato is the Abel Bliss Professor of Engineering and Director of the Siebel School of Computing and Data Science at the University of Illinois Urbana-Champaign (UIUC), within the Grainger College of Engineering. She holds degrees from Stanford (B.S. in Mathematical Sciences and Economics), UC Berkeley (M.S. in Computer Science), and UIUC (Ph.D.). Her leadership roles include CRA Board Chair, IEEE RAS President Elect, and ACM Council Member-at-Large. Amato is a Fellow of AAAI, AAAS, ACM, and IEEE, and a Member of the American Academy of Arts and Sciences. Her research focuses on robotics (task/motion planning, multi-robot systems), computational biology (protein-drug interactions), parallel computing (STAPL project collaboration with Lawrence Rauchwerger), and computational geometry. She pioneered sampling-based motion planning for robotics and computational biology, including protein folding studies. Current projects include the NSF Expeditions 'Mind in Vitro' exploring biological neuron-based computing. Amato has mentored 29 PhD students (many in academia/industry), 30+ masters, 100+ undergrads, and 10+ high school students, prioritizing underrepresented groups. She co-leads the CRA-WP Distributed REU program, fostering diversity in computing. Awards include the IEEE RAS Saridis Leadership Award (2019) and UC Berkeley's Distinguished CS Alumnus Award (2024).

• Industrial Automation
• Real-time Embedded Systems
• Cybersecurity
• +۴ مورد دیگر

Philippe Saey is a researcher at KU Leuven specializing in industrial automation, cybersecurity, and embedded systems. His work spans multiple domains including clinical trials technology, robotics education, and astronomical instrumentation. Expertise in industrial communication protocols (PROFIBUS, PROFINET, TSN) Developed open data recording devices for clinical trials Contributed to knowledge-driven control system design for telescopes Research Focus : Real-time systems, network redundancy, and human-centric technology. His 2024 work on TSN synchronization attacks highlights vulnerabilities in Industry 4.0 networks. Earlier projects include low-cost Arduino-based error generators and MATLAB code integration for steel manufacturing. Education & Collaboration : Co-developed project-based robotics curricula with industry partners and contributed to international automation projects like i-MOCCA (Flanders, France, UK). Supervised PhD research on telescope control systems.

• Cryptography
• Industrial Artificial Intelligence
• Machine Learning
• +۶ مورد دیگر

Benedikt Schmidt is a researcher affiliated with Darmstadt University of Technology , Germany, and has contributed to diverse fields including Cryptography , Industrial Artificial Intelligence , and Formal Verification . His work focuses on mathematical proofs for cryptographic systems, AI-driven industrial process optimization, and human-computer interaction in technical environments. Key collaborations with leading cryptographers like Gilles Barthe and Andre Scedrov Recent 2025 publications on alarm prediction transformers and multimodal AI in industrial contexts Research Themes span: Cryptography : Automated analysis of security assumptions, structure-preserving signatures, predicate encodings. Industrial AI : Virtual assistants, alarm prediction models, process automation. Ethics & Security : Explainability in ML for psychiatry, key confirmation protocols. Notable conferences include CCS, CRYPTO, IEEE Security & Privacy, and journals like J. Cryptol. and Eng. Appl. Artif. Intell.