جست‌وجوی استاد و پژوهشگر

Martha U Gilletteمشاهده پروفایل

استاد

• Neurobiology
• Circadian Rhythms
• Neuronal Development
• +۶ مورد دیگر

Martha U Gillette is an Alumni Professor in the Department of Cell and Developmental Biology at the University of Illinois. She holds additional roles as Director of the Neuroscience Program and Professor in multiple interdisciplinary institutes, including the Beckman Institute and Carl R. Woese Institute for Genomic Biology. Education: B.A. in Biology, Grinnell College M.S. in Zoology, University of Hawaii Ph.D. in Zoology, University of Toronto Postdoc., University of California-Santa Cruz Research Interests: Neurobiology of circadian rhythms and their role in brain function Neuronal development and repair mechanisms Emergent behaviors in neuronal clusters Actin cytoskeleton signaling in circadian clock coupling Key Achievements: Recipient of AAAS Fellow (1995) Women in Neuroscience Lifetime Achievement Award NSF and NIH grants for BRAIN Initiative projects Co-developed microfluidic platforms for neuronal studies Lab & Collaborations: Leads interdisciplinary teams integrating neuroscience, bioengineering, and nanotechnology. Active in campus initiatives like the Center for Advanced Study and the Micro and Nanotechnology Lab.

Alberto Bartesaghiمشاهده پروفایل

دانشیار

• Computational Imaging
• Cryo-Electron Microscopy (Cryo-EM)
• Structural Biology
• +۳ مورد دیگر

Alberto Bartesaghi is an Associate Professor of Computer Science, Biochemistry, and Electrical and Computer Engineering at Duke University, affiliated with the Pratt School of Engineering and the Duke Institute for Brain Sciences. He holds a D.Phil. from the University of Minnesota, Twin Cities. His research focuses on computational imaging and structural biology, particularly advancing cryo-electron microscopy (cryo-EM) technologies for high-resolution molecular structure determination. Education: D.Phil. in Computer Science, University of Minnesota, Twin Cities, 2005 His work integrates machine learning with cryo-EM to address challenges in visual proteomics, including protein localization, image denoising, and automated data processing. Key contributions include platforms like nextPYP and MiLoPYP , which enable scalable analysis of protein variability in situ. Bartesaghi’s lab also explores applications in virology, neurodegenerative diseases, and antifungal drug discovery through structural insights from cryo-EM. Recent projects include studying α-synuclein fibril structures linked to Parkinson’s disease, HIV-1 envelope glycoprotein conformations, and the molecular basis of viral entry mechanisms. His team has received support from initiatives like the Chan Zuckerberg Initiative to enhance cryo-EM workflows. Bartesaghi teaches advanced courses in computational imaging and cryo-EM, and collaborates across disciplines to bridge engineering, biology, and computer science. His lab develops open-source tools for microscopy automation and high-throughput data analysis, advancing global research capabilities in structural biology.

Sen Chengمشاهده پروفایل

استاد

• Computational Neuroscience
• Neural Mechanisms of Learning and Memory
• Hippocampal Dynamics
• +۵ مورد دیگر

Prof. Sen Cheng is a Professor at the Institute of Neuroinformatics (INI), part of the Faculty of Computer Science at Ruhr-Universität Bochum. His research focuses on computational neuroscience, particularly the neural mechanisms underlying learning, memory, and spatial navigation. He leads a lab investigating hippocampal dynamics, combining mathematical modeling with optogenetic and electrophysiological data analysis. Collaborations span neuroscientists in Germany and internationally. Research interests include hippocampal replay mechanisms, episodic memory functions, and the interplay between sensory inputs and neural networks. His work bridges computational models (e.g., spiking neural networks) with experimental data from rodents and humans. Recent projects explore deep reinforcement learning agents for spatial navigation and the role of grid cells in cognitive mapping. Publications span Neuron , Current Biology , and eLife , addressing topics like hippocampal network stabilizations, spatial coding efficiency, and cerebellar contributions to fear extinction. Teaching includes courses on computational neuroscience, artificial neural networks, and mathematical psychology. Lab activities involve interdisciplinary research through colloquia like Brains in Space and supervision of master’s and bachelor’s theses in areas like reinforcement learning algorithms and embodied associative networks. The INI’s mission drives his work, linking biological insights to artificial cognitive systems design.

Lee Spectorمشاهده پروفایل

استاد مدعو

• Artificial Intelligence
• Artificial Life
• Computational Problem-Solving
• +۸ مورد دیگر

Lee Spector is an Adjunct Professor in the Department of Computer Science at the University of Massachusetts Amherst and a Professor of Computer Science at Amherst College. He holds the MacArthur Chair at Hampshire College and has served as Dean of the School of Cognitive Science and on the Board of Trustees. His research focuses on artificial intelligence, evolutionary computation, and their intersections with cognitive science, physics, and the arts. Notable contributions include work on genetic programming, lexicase selection, and quantum computing algorithms. He has received prestigious awards such as the NSF Director's Award for Distinguished Teaching Scholars and two gold medals in the GECCO Human Competitive Results competition. His editorial roles include Editor-in-Chief of Genetic Programming and Evolvable Machines and associate editorships at ACM journals. Spector's grants include NSF and DARPA funding for projects like robust artificial system synthesis and computational creativity curricula. Education: Ph.D. in Computer Science, University of Maryland, College Park (1992); B.A. in Philosophy, Oberlin College (1984). Research spans evolutionary algorithms, artificial life, and interdisciplinary applications in music, art, and social science. His lab, The PUSH Lab, explores autoconstructive evolution and modular program synthesis. Recent work includes advancements in lexicase selection, quantum circuit optimization, and human-machine collaboration in innovation. Key contributions include the Push programming language for evolutionary processes and the lexicase selection algorithm. He directs initiatives like the Artificial Intelligence in the Liberal Arts program, emphasizing computational creativity across disciplines. Spector's publications span journals like Evolutionary Computation , Genetic Programming and Evolvable Machines , and Artificial Life , with over 100 peer-reviewed articles and two books.

• Functional Neurosurgery
• Brain-Computer Interfaces
• Neuroprosthetics
• +۳ مورد دیگر

Brian Lee is an Associate Professor specializing in Neurological Surgery and Biomedical Engineering, holding leadership roles as Director of the MD-PhD Program and Director of Stereotactic and Functional Neurosurgery. His clinical and research focus spans functional neurosurgery, neuroprosthetics, and brain-computer interfaces. Research interests include developing neural interfaces for sensory restoration, optimizing epilepsy surgery outcomes, and advancing stereotactic techniques. His work integrates engineering principles with clinical neurosurgery to develop innovative treatment modalities for neurological disorders. Publications demonstrate strong focus on neurosurgical innovation and liver disease management, with recent work emphasizing brain-computer interfaces, health disparities, and liver transplantation outcomes. Research trends show integration of engineering solutions with clinical applications in neurology and hepatology.

Chris Eliasmithمشاهده پروفایل

استاد

• Theoretical Neuroscience
• Computational Neuroscience
• Neuromorphics
• +۶ مورد دیگر

Chris Eliasmith is a Professor jointly appointed in the Systems Design Engineering and Philosophy departments at the University of Waterloo, with a cross-appointment to Computer Science. He is the Founding Director of the Centre for Theoretical Neuroscience and holds the Canada Research Chair in Theoretical Neuroscience. His research focuses on mathematical modeling of neural systems, including the Neural Engineering Framework (NEF) and Semantic Pointer Architecture (SPA), which underpin the world’s largest functional brain simulation, Spaun. He leads the Computational Neuroscience Research Group (CNRG), advancing neuromorphic computing, spiking neural networks, and cognitive modeling. Education: PhD in Neuroscience & Psychology (2000), Washington University in St. Louis MA in Philosophy (1995), University of Waterloo BASc in Systems Design Engineering (1994), University of Waterloo Research: His work integrates theoretical neuroscience with practical applications in robotics, AI, and neuromorphic hardware. Key contributions include the NEF, Spaun, and innovations like the Legendre Memory Unit (LMU) and Spatial Semantic Pointers (SSPs). His lab explores adaptive neural systems, decision-making models, and biologically plausible machine learning algorithms. Teaching: Recent courses include SYDE 556 (Simulating Neurobiological Systems), SYDE 750 (Topics in Systems Modelling), and PHIL 356 (Intelligence in Machines, Humans, and Other Animals). Awards: 2015 NSERC Polanyi Prize Labs & Projects: The CNRG develops tools like Nengo for simulating large-scale neural systems and collaborates on neuromorphic hardware platforms such as Loihi. Current projects span neural robotics, cognitive architectures, and biologically inspired AI systems.

• Neuroscience
• Cognitive Psychology
• Social Cognition
• +۳ مورد دیگر

Dr. Richard Ramsey is a Lecturer at the Department of Health Sciences and Technology at ETH Zürich. His research focuses on social cognition, cognitive control mechanisms, and the intersection of artificial intelligence with human behavior. He teaches courses like 'The Social Brain: Critical Perspectives on Science, Society and Neurodiversity.' Key research areas include neurophysiological correlates of imitation, AI ethics, loneliness in neurorehabilitation contexts, and methodological advancements in psychological data analysis. His work often employs computational models and neuroimaging techniques to explore decision-making processes and social perception. Developed Bayesian methods for analyzing time-to-event data in psychological studies Investigated anthropomorphic perceptions of humanoid robots Explored how art education impacts aesthetic and cognitive functions No scientific awards are explicitly listed in the provided materials. His academic contributions span experimental psychology, neuroscience, and interdisciplinary applications of cognitive science.

• Computer Vision
• Geometric Deep Learning
• Biomedical Engineering
• +۳ مورد دیگر

Dr. Xiatian Zhang is a Research Associate at the University of Edinburgh's Deanery of Clinical Sciences, focusing on bronchoscopic robotics vision. He holds a PhD in Computer Science from Durham University, supervised by Prof. Hubert P.H. Shum and Dr. Noura Al Moubayed. His research integrates geometric information into computer vision applications for biomedical engineering videos. Research interests include computer-assisted intervention, clinical outcome analysis, and healthcare education enhancement through machine learning. His work bridges geometric deep learning with practical clinical applications in surgical robotics and medical diagnostics. Articles demonstrate consistent focus on computer vision applications in medical contexts, particularly surgical workflow prediction, endoscopic analysis, and neurological disorder diagnosis using video and imaging data. EPSRC Grant: U-care: Deep Ultraviolet Light Therapies (£6,132,366) British Council Grant: Course Development in Edge Computing and Analytics 2.0 (£30,000) Northumbria University Seed Funding: Pose Estimation for Health Professional Education (£16,428) Currently developing deep learning-based visual navigation systems for bronchoscopic robotics under Dr. Mohsen Khadem. Previously contributed to projects at Durham University and Northumbria University involving edge computing and health professional education.

Mohammad Hasanمشاهده پروفایل

مدرس ارشد

• Computer Networks
• Cyber Security
• Cloud Computing
• +۵ مورد دیگر

Dr. Mohammad Hasan is a Senior Lecturer in Digital, Tech, Innovation & Business at Staffordshire University with extensive expertise in cybersecurity, cloud computing, and network engineering. His educational background includes a PhD in Mobile Ad-hoc Networks, MSc in Computer and Network Engineering, and BSc in Computer Science. His primary research focuses on: Computer networks including wireless systems and IoT Cybersecurity frameworks and threat analysis Cloud computing infrastructure and virtualization Machine learning applications in data analytics Recent publications demonstrate strong trends in machine learning applications for pattern recognition (eSports analytics), network security (XSS prevention), and biomedical signal processing (brain source localization). Dr. Hasan maintains professional certifications including CCSK, CompTIA Security+, and Cisco CyberOps Associate, and holds Senior Fellow status with the Higher Education Academy.

Raheel Nawazمشاهده پروفایل

استاد

• Artificial Intelligence
• Digital Education
• Educational Data Science
• +۴ مورد دیگر

Professor Raheel Nawaz is the Pro-Vice Chancellor (Education and Research) at Staffordshire University, leading academic strategy across four strategic priorities: Next Generation Education, Experience, Environment, and Engagement. He previously served as Pro-Vice Chancellor (Digital Transformation), driving transformative digital initiatives recognized as sector-leading. His career spans leadership roles in diverse institutions, including Russell Group universities and private further education organizations. He is a top-10 global scholar in 'Applied AI' and 'Digital Education', with over £14M in grants and 200+ publications (h-index 47). He advises international educational programs and sits on boards like JISC and UVAC. Research interests focus on AI-driven education, work-based learning, and industry-academia collaboration. His National Teaching Fellowship (NTF) recognizes groundbreaking work on Degree Apprenticeship pedagogies, improving outcomes for underrepresented students. He has advised governments and policy bodies, including Pakistan’s Prime Minister’s Task Force on Science and Technology. Notable contributions include AI applications in Urdu language processing, healthcare diagnostics, and robotics for autism therapy. Awards: NTF, PFHEA, Whatuni Student Choice Awards 2023 Grants: DARPA, CERN, World Bank, UKRI, Innovate UK Leadership: Spearheaded digital transformation, advised three continents’ educational programs Labs/Teams: Led Staffordshire’s Digital Transformation research center and collaborates with global organizations like the National Centre for Artificial Intelligence (Pakistan).

David Huمشاهده پروفایل

استاد

• Fluid Mechanics
• Biomechanics
• Robotics
• +۳ مورد دیگر

David Hu is a Professor of Mechanical Engineering and Biology at the Georgia Institute of Technology. He received his SB (2001) and PhD (2006) in Mechanical Engineering from MIT. His research focuses on fluid mechanics and biomechanics, particularly studying how insects and animals interact with their physical environments, such as survival mechanisms in rainstorms and the physics of animal shaking behavior. He has developed interdisciplinary educational tools like BLOSSOMS modules to teach high school students about fluid dynamics through real-world biological examples. His recent work includes studies on mosquito rain survival, dog shake mechanics, and applications of optical coherence tomography (OCT) in medical diagnostics. Education: SB and PhD in Mechanical Engineering from MIT. His research spans fluid dynamics, biological systems, and medical imaging technologies. He collaborates across disciplines to bridge engineering principles with biological phenomena, with a focus on translating findings into practical technologies and educational resources. Research interests include fluid-structure interactions in nature, biomimetic robotics, and advanced imaging techniques for clinical applications. His work on animal behavior has been featured in media like Good Morning America and the New York Times. He emphasizes scale effects in engineering and biology, using principles from both fields to solve complex problems.

Yizhi Liuمشاهده پروفایل

استادیار

• Construction Robotics
• Human-Robot Interaction
• Robotic Teleoperations
• +۵ مورد دیگر

Yizhi Liu is an Assistant Professor at Syracuse University. His research focuses on construction robotics, human-robot interaction, and physiological sensing for worker safety. He holds a PhD in Architectural Engineering from Penn State University, along with multiple master's degrees in Robotics, Electrical Engineering & Computer Science, Construction Engineering & Management, and a BS in Construction Management from Tianjin University. Education: PhD in Architectural Engineering, Pennsylvania State University MS in Robotics, Columbia University MS in Electrical Engineering & Computer Science, Pennsylvania State University MS in Construction Engineering & Management, University of Michigan BS in Construction Management, Tianjin University Research Interests: Yizhi Liu's work explores innovative applications of robotics in construction environments, including brain-computer interfaces for hands-free robot control, real-time physiological monitoring for worker safety, and advanced algorithms for human-robot collaboration. His research integrates computer vision, machine learning, and neurophysiological techniques to enhance construction site efficiency and safety. Grants & Advising: While specific grants or advising details are not provided in the text, his active research portfolio suggests involvement in collaborative projects addressing cutting-edge robotics and safety challenges in construction.

Sergio Daviesمشاهده پروفایل

مدرس ارشد

• Spiking Neural Networks
• Neuromorphic Computing
• Computer Network Security
• +۳ مورد دیگر

Dr. Sergio Davies serves as a Senior Lecturer in the Department of Computing and Mathematics at Manchester Metropolitan University, leveraging extensive experience from both academic research and industry leadership. His career spans the University of Manchester's SpiNNaker project, the European Human Brain Project, and strategic roles in hardware/software development before returning to academia in 2019. His educational foundation includes an MSc-equivalent in Telecommunication Engineering from the University "Federico II" in Naples and a Ph.D. in Computer Science from the University of Manchester (2012). MSc-equivalent: Telecommunication Engineering, University "Federico II", Naples Ph.D.: Computer Science, University of Manchester (2012) Davies specializes in spiking neural networks and neuromorphic computing, with pioneering work on the SpiNNaker architecture. His current research focuses on applying these technologies to computer network security and robotics, developing event-driven systems for real-time applications like gesture recognition and intrusion detection. This work bridges theoretical neuroscience with practical engineering challenges, emphasizing low-power, real-time operation. Analysis of his 15 most recent publications (2012-2025) reveals a clear evolution from foundational SpiNNaker development toward applied security and robotics. Recent work integrates event-based vision with neuromorphic hardware for multi-object tracking and gesture recognition, while maintaining core contributions to learning algorithms like STDP. The consistent thread is practical implementation on neuromorphic platforms for security-critical applications. Professional recognition includes: Member of the Institution of Engineering and Technology (MIET) Member of the Institute of Electrical and Electronics Engineers (MIEEE) Fellow of the Higher Education Academy (FHEA) His industry experience as an IT consultant at KPMG and subsequent leadership of hardware/software teams informs his applied research approach. Though specific student advisees aren't listed, his work involves mentoring through the SpiNNaker ecosystem and Human Brain Project collaborations. Current projects focus on neuromorphic security solutions developed through university-industry partnerships. Davies operates within Manchester Metropolitan University's neuromorphic computing research group, maintaining active ties to the original SpiNNaker team at Manchester and the Human Brain Project consortium. His lab focuses on translating theoretical neural models into deployable security and robotics systems using SpiNNaker hardware.

Deborah Wonمشاهده پروفایل

استاد

• Biomedical Engineering
• Neural Engineering
• Mobile Health Technology
• +۳ مورد دیگر

Deborah Won is a Professor in the Department of Electrical & Computer Engineering at California State University, Los Angeles, within the College of Engineering, Computer Science, and Technology. With a background in biomedical engineering and electrical engineering, she has focused on integrating research, teaching, and community engagement since 2009. Education: Ph.D. in Biomedical Engineering (Duke University, 2007), B.S. in Electrical Engineering with a Biomedical Engineering minor (MIT, 2000). Research Interests span neural engineering, rehabilitation technology, and mobile health. Her Neural Engineering Technology Laboratory (NETlab) investigates: Electrophysiological biomarkers for Parkinson's disease to improve deep brain stimulation (DBS) algorithms. Mobile health solutions like the WOW-Mobile fitness app for wheelchair users. Neural signatures of spreading depression in stroke progression. Collaborative rodent studies on spinal cord injury rehabilitation. Publications highlight her work in closed-loop DBS systems, exergaming technology, and educational program design. She received the 2020 BEST ZONE IV PAPER and BEST OVERALL ZONE WINNER award for her service-learning research. Leadership: Faculty advisor for the Biomedical Engineering Society (BME Society). Labs: Founder and director of the Neural Engineering Technology Laboratory (NETlab). Service: Co-developer of the BOOST program, which enhances engineering identity through community-focused projects.

Sudha Swaminathanمشاهده پروفایل

استاد

• Early Childhood Mathematics
• Educational Technology
• Teacher Education
• +۳ مورد دیگر

Dr. Sudha Swaminathan is a Professor of Early Childhood Education and Director of the Center for Early Childhood Education at Eastern Connecticut State University. She specializes in early childhood mathematics, educational technology, and teacher education, with a focus on play-based learning and technology integration. Her research explores how coding, robotics, and play-based interactions impact children’s cognitive and mathematical development, particularly among bilingual learners. Dr. Swaminathan holds a PhD and Master’s in Early Childhood Education from SUNY Buffalo. Her teaching emphasizes inquiry-based learning, where students engage with materials and apply knowledge through projects. She is passionate about action research, guiding in-service teachers in designing classroom research projects across disciplines. Her research spans six studies on math talk during play, published in journals like Early Child Development and Care , and has been featured at the American Educational Research Association conferences. She advocates for innovative teaching methods to enhance children’s mathematical reasoning through play and technology. Dr. Swaminathan’s advising philosophy prioritizes student growth, exemplified by her mentorship at conferences where students showcase their research. She believes Eastern’s programs prepare students for diverse careers in education, including roles beyond traditional classroom teaching. She directs the Center for Early Childhood Education, fostering interdisciplinary collaboration in early childhood development. Her work emphasizes the importance of staying connected with alumni and faculty to advance educational practices.