جست‌وجوی استاد و پژوهشگر

Tyler Engstromمشاهده پروفایل

استادیار

• Soft Matter Physics
• Biological Physics
• Biomechanics
• +۷ مورد دیگر

Tyler Engstrom is an Assistant Professor in the Department of Physics and Astronomy within the College of Natural and Health Sciences at the University of Northern Colorado, where he also serves as Faculty Associate to the Dean for Internships. His academic journey spans industry and academia with roles at MiTeGen, Hobart and William Smith Colleges, and Syracuse University. His educational background: Ph.D. in Physics, Penn State University (2015) B.S. in Metallurgical Engineering, South Dakota School of Mines and Technology (2005) Dr. Engstrom's research centers on mechanical instabilities in biological systems, investigating how differential growth creates structures like brain folds and retinal foveae. His work uniquely bridges theoretical physics and biological phenomena , exploring quantum-classical analogies in elasticity while collaborating with biologists. Recent publications reveal strong focus on morphogenesis mechanisms and biomechanical modeling , with applications in developmental biology and tissue engineering. His publication record shows increasing specialization in biological physics since 2016, with significant contributions to understanding compression stiffening in tissues and quantum-inspired mechanical models. The 2023 Physical Review E paper exemplifies his innovative approach to connecting classical elasticity with quantum systems. Research funding achievements: National Eye Institute grant R15EY035473 (2024) as co-PI College of Natural and Health Sciences GRIP Awards (2023, 2024) UNC New Project Proposal grant (2021) Dr. Engstrom maintains active collaborations with biologists while mentoring students through research projects. His editorial work for American Journal of Physics demonstrates commitment to physics education. The combination of industry experience (MiTeGen), academic research, and teaching creates a dynamic environment for student involvement in cutting-edge biophysics. Though no formal lab name is specified, his research group employs interdisciplinary methods to study mechanical instabilities in biological contexts, utilizing computational modeling, theoretical frameworks, and experimental collaborations to advance understanding of tissue morphogenesis.

• Machine Learning
• Deep Learning
• Computer Vision
• +۶ مورد دیگر

Yann André LeCun is the Jacob T. Schwartz Professor of Computer Science, Data Science, Neural Science, and Electrical and Computer Engineering at New York University, and serves as Chief AI Scientist at Meta. He holds appointments across multiple NYU institutions including the Courant Institute of Mathematical Sciences, the Center for Data Science, the Center for Neural Science, and the Tandon School of Engineering. LeCun leads the CILVR Lab (Computational Intelligence, Learning, Vision, Robotics) at NYU and is a key figure in Meta's FAIR (Fundamental AI Research) organization. LeCun's research spans machine learning, deep learning, computer vision, robotics, and computational neuroscience. He pioneered convolutional neural networks in the 1980s-90s, which became foundational to modern AI. His recent work focuses on self-supervised learning, energy-based models, and developing architectures for predictive world models that could enable machines to understand and interact with the physical world. LeCun advocates for open-source AI development through projects like Meta's Llama language models. His publication record shows consistent high-impact contributions since the 1980s, with recent work emphasizing self-supervised learning approaches like Joint Embedding Predictive Architectures (JEPA). The 15 most recent publications reveal a strong focus on representation learning, world models, and efficient learning paradigms that reduce reliance on massive labeled datasets. ACM Turing Award (2018) Princess of Asturias Award for Technical and Scientific Research (2022) Member of US National Academy of Engineering (2017) Member of US National Academy of Sciences (2021) Foreign Member of Académie des Sciences, France (2022) Queen Elizabeth Prize for Engineering (2025) VinFuture Grand Prize (2024) LeCun has advised approximately 30 PhD students who now lead AI research at major institutions worldwide. His lab has received significant funding from both government agencies and industry partners to advance fundamental AI research. The CILVR Lab fosters interdisciplinary collaboration across computer science, neuroscience, and engineering disciplines to tackle core challenges in artificial intelligence. LeCun actively engages with policymakers on AI governance, advocating for open research and targeted regulation. His work on open-source AI models represents a strategic approach to democratizing AI development while maintaining safety through community scrutiny. LeCun continues to push the boundaries of what machines can learn and understand about the physical world.

Guido Grossmannمشاهده پروفایل

استاد

• Plant Biology
• Cell Biology
• Plant-Microbe Interactions
• +۴ مورد دیگر

Prof. Dr. Guido Grossmann serves as Head of the Institute of Cell and Interaction Biology at Heinrich Heine University Düsseldorf (HHU), joining CEPLAS (Cluster of Excellence on Plant Sciences) in October 2020. His research program investigates biological interactions from protein-level organization to organism-level symbioses, with particular focus on plant cell dynamics and root-microbe relationships. His academic journey includes: Doctoral research with Widmar Tanner at University of Regensburg studying plasma membrane organization EMBO postdoctoral fellowship at Carnegie Institution for Science in Stanford with Wolf Frommer and David Ehrhardt Independent research group leadership at Centre for Organismal Studies, Heidelberg University (2013-2020) Grossmann's laboratory specializes in developing advanced imaging technologies for plant science, most notably pioneering the RootChip microfluidic platform that enables quantitative microscopy of metabolite dynamics in living plant roots. His research explores how biological systems develop functionalities beyond the sum of their parts, from signaling clusters of membrane proteins regulating cellular growth to root-soil microbe interactions shaping diverse microenvironments. The lab develops soil-inspired cultivation devices for high-resolution imaging of root colonization processes and investigates cell polarization, growth regulation, and intercellular communication in plant roots. Analysis of his publication record reveals consistent innovation in plant imaging technologies alongside fundamental discoveries in root biology, calcium signaling, and plant stress responses. His work bridges theoretical plant biology with practical technological applications, particularly through the development of microfluidic systems that enable precise environmental control for plant studies. Key recognition: EMBO Fellow As head of his institute, Grossmann oversees research programs spanning plant metabolism, metabolomics, and advanced imaging. His mentorship philosophy emphasizes maintaining scientific curiosity while upholding rigorous research integrity. The laboratory maintains specialized facilities including the Plant Metabolism and Metabolomics Facility and Imaging Platform, supporting quantitative approaches to plant science. His current research initiatives within CEPLAS focus on optimizing plant performance through understanding development-metabolism interfaces, plant microbiota networks, and synthetic biology approaches to plant science.

• Biological Materials
• Biomimetic Materials
• Bone Formation
• +۵ مورد دیگر

Wolfgang Wagermaier is a Research Professor and Group Leader at the Max Planck Institute of Colloids and Interfaces in Potsdam, Germany, where he heads the Hierarchical Structure of Biological and Bio-inspired Materials research group. He completed his habilitation in Materials Science at Technische Universität Berlin in 2017. Education Diploma in Materials Science, University of Leoben (1993-2001) PhD in Materials Science, Max Planck Institute of Colloids and Interfaces & University of Leoben (2003-2006) Postdoctoral research at Max Planck Institute of Colloids and Interfaces (2006-2007) and GKSS Research Center (2007-2009) Research Focus His research explores structure-function relationships in biological and bio-inspired materials, with emphasis on bone formation mechanisms, healing processes, and biomineralization. He specializes in hybrid material systems and employs advanced multiscale characterization techniques including synchrotron X-ray scattering (WAXS/SAXS), X-ray microtomography, and electron microscopy to investigate hierarchical material architectures.

• Spiking Neural Networks
• Neuromorphic Information Processing
• Artificial Neural Networks
• +۷ مورد دیگر

Professor Martin Bogdan serves as a Professor for Neuromorphic Information Processing at the University of Leipzig within the Faculty of Mathematics and Computer Science. His research spans multiple interdisciplinary domains including spiking neural networks, neuromorphic computing, and medical signal processing applications. University: University of Leipzig School: Faculty of Mathematics and Computer Science Department: Department of Neuromorphic Information Processing Office: Augustusplatz 10, Room P 531, 04109 Leipzig Contact: +49 (341) 97-32208 | bogdan@informatik.uni-leipzig.de Professor Bogdan completed his doctorate at the University of Tübingen in 1998 with research focused on signal processing of biological nerve signals for controlling prostheses using artificial neural networks. His educational background includes communications engineering at Offenburg University of Applied Sciences and studies at Université Grenoble I Joseph Fourier. Professor Bogdan's research interests center on neuromorphic information processing, with particular emphasis on spiking neural networks (SNNs), neurological plausible learning algorithms, and the incorporation of dynamics within synaptic efficiency. His work bridges computational neuroscience with practical applications in medical diagnostics, embedded systems, and real-time signal processing. His team has made significant contributions to understanding consciousness in locked-in syndrome patients through EEG analysis and developing innovative approaches to agricultural quality control using hyperspectral imaging and neural networks. The research demonstrates a consistent trajectory from foundational neural network architectures toward increasingly sophisticated neuromorphic computing applications. Analysis of Professor Bogdan's recent publication record reveals a strong focus on advancing spiking neural network architectures, particularly liquid state machines and synaptic dynamics models. His work increasingly bridges theoretical neuroscience with practical applications in medical diagnostics (particularly consciousness assessment in locked-in syndrome patients) and agricultural technology (using hyperspectral imaging for seed purity analysis). A notable emerging theme is the exploration of cognitive concepts like boredom in artificial intelligence systems, suggesting expanding interest in higher-order cognitive modeling within neuromorphic computing frameworks. Professor Bogdan leads the Department of Neuromorphic Information Processing at the University of Leipzig, supervising numerous PhD students and postdoctoral researchers. His team includes researchers specializing in various aspects of neural networks, signal processing, and applications in medical and agricultural domains. The department maintains active collaborations with medical institutions for clinical applications of their research, particularly in the area of brain-computer interfaces and consciousness assessment.