جست‌وجوی استاد و پژوهشگر

Christian Böhmمشاهده پروفایل

دانشیار

• Data Mining
• Machine Learning
• Clustering Algorithms
• +۳ مورد دیگر

Christian Böhm is an Associate Professor at the Faculty of Computer Science, leading the Research Group Data Mining and Machine Learning. His work focuses on clustering algorithms, density-based analysis, and graph construction. He has been active in interdisciplinary projects, including computational modeling for biomedical applications and algorithm benchmarking. Notable contributions include ADOD (Adaptive Density Outlier Detection) and DynoGraph (Dynamic Graph Construction for Nonlinear Dimensionality Reduction). His research bridges theoretical data science with practical applications in healthcare and engineering. Research Group: Data Mining and Machine Learning Key Areas: Clustering, Density Analysis, Graph Algorithms, Medical Data Analytics Collaborations: Biohybrid heart valves, computational biomechanics, and algorithmic benchmarking Recent work emphasizes deep learning integration in clustering, medical outcome prediction, and scalable graph classification. His publications span conferences like IEEE ICDM and interdisciplinary journals.

Monica Wachowiczمشاهده پروفایل

استاد

• Data Science
• Geospatial Science
• Machine Learning
• +۵ مورد دیگر

Professor Monica Wachowicz holds the rank of Professor of Data Science at RMIT University, within the School of Science. Her academic roles include Associate Dean of Geospatial Science, Research Leader of Cyber and Data Analytics at the Space Industry Hub, and Deputy Director of the Sir Lawrence Wackett Defence & Aerospace Centre. She leads interdisciplinary research in streaming analytics, IoT integration, and smart city technologies. Wachowicz has pioneered innovations in edge computing and geospatial intelligence, collaborating with global firms like Cisco, Siemens, and IBM. She is a founding member of the IEEE Technical Sub-Committee on Big Data and serves on nine editorial boards. Her research focuses on leveraging machine learning for IoT data streams to address sustainability challenges in smart cities, including mobility analytics and energy systems. Over 52 students under her supervision have contributed to industries like tech, finance, and academia. Wachowicz is the first woman engineer in Geomatics awarded an NSERC Industrial Research Chair in Canada and holds an Honorary Visiting Scholar title at Flinders University. Her work emphasizes cross-sector collaboration, advancing green economies and data-driven decision-making. Awards include NSERC Industrial Research Chair (2010s) and Honorary Visiting Scholar (Flinders University, ongoing). Key projects include EVStationSIM (EV charging infrastructure analysis), Smart Campus Integration Lab, and IoT-GIS platforms for real-time analytics. She supervises projects on AI for urban sensing, smart mobility, and space situational awareness.

James Spicerمشاهده پروفایل

استاد

• Laser-Material Interactions
• Materials Science and Engineering
• Additive Manufacturing
• +۶ مورد دیگر

James Spicer is a Professor of Materials Science and Engineering and Chair of the Engineering for Professionals Materials Science and Engineering Program at Johns Hopkins University's Whiting School of Engineering. He holds a secondary appointment at the Johns Hopkins Applied Physics Laboratory (APL) and is a member of the Hopkins Extreme Materials Institute (HEMI). His research focuses on laser-material interactions, photochromic materials, and advanced manufacturing techniques with applications in energy, healthcare, and aerospace. Spicer earned a BS in Physics and Mechanical Engineering from Southern Methodist University (1985) and a PhD in Materials Science and Engineering from Johns Hopkins (1991). He has led the Center for Materials Sensing and Detection and contributed to NASA's Parker Solar Probe thermal management system. His honors include the 2011 Gold Cup for Leadership and the 2000 William H. Huggins Teaching Award. His research explores photoacoustic stimulation for retinal prosthetics, nuclear graphite structural analysis, and functional polymer nanocomposites. Collaborations include industry leaders like IBM and GE Healthcare. His work bridges academic and applied research, addressing challenges in energy systems, biomedical devices, and extreme environment materials. Key Research Themes: Laser processing, metamaterials, nuclear graphite characterization, biomedical nanocomposites, and thermal management Professional Memberships: IEEE, APS, OSA, MRS, ASME Leadership: Co-Chair of IEEE Nanoacoustic Symposium, Conference Organizer for IEEE Nano 2018

Mick Bonnerمشاهده پروفایل

استادیار

• Computational Neuroscience
• Cognitive Neuroscience
• Vision
• +۱۱ مورد دیگر

Mick Bonner is an Assistant Professor in the Department of Cognitive Science at Johns Hopkins University, where he leads the Bonner Lab. His research lies at the intersection of neuroscience, artificial intelligence, and computational vision, focusing on understanding how visual information is processed in the human brain using neuroimaging and deep learning models. Research Interests: His work centers on uncovering the statistical principles governing high-dimensional representations in the visual cortex. He investigates how deep neural networks can model brain activity, challenges low-dimensional assumptions in neural coding, and explores hierarchical processing in social vision. His lab employs advanced statistical methods, fMRI, and computational modeling to study neural manifolds, dimensionality, and model-to-brain alignment. Publication Trends: Recent publications reveal a strong focus on high-dimensional neural representations, universal features across models, and the role of unsupervised learning in building biologically plausible visual hierarchies. His team frequently uses fMRI, naturalistic stimuli, and cross-decomposition techniques to study individual differences and shared cortical codes. Glushko Dissertation Prize 2024 – Awarded by the Cognitive Science Society. IDIES Seed Funding Award – From Johns Hopkins for innovative data-intensive research. Advising and Grants: Prof. Bonner advises multiple PhD students, including Emalie McMahon, Raj Magesh Gauthaman, and Ray Chen, whose work has been published in Science Advances , Current Biology , and PLOS Computational Biology . He has secured competitive internal funding and actively mentors students in computational neuroscience. His lab collaborates with institutions like Sakana AI and the Kavli Neuroscience Discovery Institute. Labs and Teams: The Bonner Lab at Johns Hopkins is an interdisciplinary team combining neuroscience, machine learning, and statistics. They develop open educational resources, including a widely used CCN tutorial on high-dimensional neuroscience, and maintain strong ties with the broader cognitive science and AI research communities.

Gowthamمشاهده پروفایل

عضو هیئت علمی

• Parallel Computing
• Supercomputing Platforms
• Computational Workflows
• +۴ مورد دیگر

Gowtham is a Research Associate Professor in Applied Computing and Director of Research Computing at Michigan Technological University (Michigan Tech). He holds a PhD in Engineering Physics from Michigan Tech (2007) and has postdoctoral experience in Physics. His roles include teaching, research, and administration, with a focus on advancing high-performance computing and fostering collaborations through initiatives like the NSF ACCESS Program and Supercomputing Conference. He previously worked at AT&T Research and Development (2007–2009). Research Interests: Parallel computing and visualization Design of supercomputing platforms and computational workflows Technological tools for research/education Interaction of biological matter with nanomaterials Electronic structure calculations of nanoclusters Publications Focus: His work emphasizes multiscale modeling of composites, molecular dynamics simulations of polymers/nanomaterials, and thermal/mechanical property predictions. Recent trends include machine learning applications in nanocomposite interface analysis and graphene-epoxy hybrid systems. Service & Collaboration: Represents Michigan Tech in the HPC Advisory Council and NSF ACCESS Program, promoting partnerships between academia and industry to create opportunities for students/researchers. Labs/Teams: Leads the Research Computing team at Michigan Tech, managing HPC infrastructure and supporting computational science initiatives.

Daniele Salvatiمشاهده پروفایل

دانشیار

• Audio Signal Processing
• Acoustic Signal Processing
• Computer Audition
• +۱۳ مورد دیگر

Daniele Salvati is an Associate Professor in the Department of Mathematics, Computer Science and Physics at the University of Udine, Italy. He is actively involved in research, teaching, and editorial roles in leading signal processing journals. Associate Professor, University of Udine Ph.D. in Acoustic Source Localization, University of Udine (2012) Senior Member, IEEE Associate Editor, IEEE/ACM Transactions on Audio, Speech, and Language Processing Handling Editor, Signal Processing His research focuses on audio and acoustic signal processing , particularly in the areas of source localization, speaker identification, and computer audition. He integrates traditional signal processing with modern machine learning and deep learning techniques to develop robust systems for real-world environments. His recent publications demonstrate a strong trend toward end-to-end deep learning models using raw waveforms, beamforming optimization (especially diagonal unloading), and applications on mobile and drone-based platforms . His work spans both journal and conference venues, with a focus on IEEE and ISCA publications. Scientific recognition includes: National Scientific Qualification as Full Professor (IINF-05/A) Senior Member of IEEE Editorial board roles in top journals He mentors doctoral students as part of the Ph.D. program in Computer Science and Artificial Intelligence and collaborates widely with researchers such as Carlo Drioli and Gian Luca Foresti. His research is supported by publications in high-impact journals and participation in international conferences. He leads work in the G.L. Foresti's Lab, focusing on intelligent systems and signal processing. His work includes developing microphone array-based interfaces for music and human-computer interaction, acoustic scene analysis, and automated sensor configuration. Future directions likely involve further integration of AI with physical sensor systems, especially in autonomous and mobile contexts.

Junpeng Wangمشاهده پروفایل

پژوهشگر ارشد

• lightweight structural design
• structural optimization
• scientific visualization
• +۵ مورد دیگر

Dr. Junpeng Wang is a Postdoctoral Researcher (since June 2023) in the Chair of Computer Graphics and Visualization at the Technical University of Munich, working under Prof. Rüdiger Westermann. Previously, he completed his PhD at the same institution from November 2018 to June 2023. His research focuses on lightweight structural design and optimization with geometry-based approaches, as well as scientific visualization of tensor and mesh data. Wang's research interests span lightweight structural design , structural optimization , and scientific visualization . His work integrates computational mechanics with computer graphics to develop novel methods for stress analysis, lattice structure optimization, and 3D data visualization. His research has practical applications in mechanical engineering, additive manufacturing, and scientific data analysis. His publication portfolio shows a strong trend toward integrating machine learning with traditional computational mechanics methods, particularly in the areas of 3D Gaussian Splatting and neural data structures. Wang has developed the 3D-TSV (3D Trajectory-based Stress Visualizer), a significant tool for exploring principal stress directions in 3D solids under load, which has been published in Advances in Engineering Software (2022). Wang serves as a reviewer for prestigious journals including IEEE Transactions on Visualization and Computer Graphics (TVCG), Computer Methods in Applied Mechanics and Engineering (CMAME), Journal of Mechanical Design (JMD), Optics Express (OPTE), Computer-Aided Geometric Design (CAG), and Shape Modeling International Conference (SPM[C]). His collaborative work primarily involves Prof. Rüdiger Westermann at TUM and Jun Wu at other institutions, demonstrating strong interdisciplinary connections between computer graphics and mechanical engineering research groups.

• Metallurgical Engineering
• Materials Science
• Welding Metallurgy
• +۶ مورد دیگر

проф. др Карло Раић is a full Professor at the Department of Metallurgical Engineering, Faculty of Metallurgy and Materials Engineering (TMF) at the University of Belgrade. He holds a prominent role in metallurgical education and research, specializing in metallic materials for biomedical applications, welding metallurgy, and process optimization. His research focuses on material interfaces, coating technologies, and advanced biomaterials. Key academic contributions include over 60 peer-reviewed articles, 5 authored books on dental materials and metallurgical processes, and leadership in national and international research projects. He has supervised 20+ master's and doctoral students, including notable works on cobalt-chromium alloys and nanocomposite materials. His work bridges fundamental metallurgy with clinical applications, particularly in dental and implant materials. Research highlights include developing nanoscale joining techniques for medical devices and optimizing steelmaking processes. He serves as editor-in-chief of TMF publications and holds professional licenses in metallurgical process design. Research Interests: Metal-ceramic interfaces, biomaterials aging, plasma spraying coatings, transport phenomena in metallurgical systems Grants: Lead researcher on projects like 'Nanofilms for Dental Joining' (EUREKA E!4213) and 'Advanced Biomaterials Analysis' Labs/Teams: Active in TMF's R&D Center for Printing Engineering and Materials Processing groups

Sacha van Albadaمشاهده پروفایل

استاد پژوهشی

• Neural Network Simulations
• Cerebral Cortex
• Predictive Connectomics
• +۳ مورد دیگر

Prof. Sacha van Albada is a Research Professor and Group Leader of Theoretical Neuroanatomy at the Institute for Advanced Simulation (IAS-6, Computational and Systems Neuroscience) at Forschungszentrum Jülich. Her research focuses on constructing and analyzing large-scale spiking neural network models of the cerebral cortex, integrating anatomical and physiological data to understand brain dynamics. Key areas include predictive connectomics, cortical microcircuit organization, and neuromorphic computing applications. Her work emphasizes multi-scale modeling across cell-type interactions, network architectures, and system-level brain functions. She develops computational tools like the NEST simulator for distributed neural network simulations. Recent projects involve modeling neuron-astrocyte interactions and exploring how cortical hierarchies and top-down signals modulate neural activity patterns. She also engages in ethical considerations of brain-inspired AI systems. Dr. van Albada collaborates extensively with experimental neuroscientists and HPC experts, contributing to initiatives like the Human Brain Project. Her models have been applied to study visual and somatosensory cortices, motor cortex dynamics, and resting-state network behavior. Despite no explicit mention of awards/grants, her high publication output and leadership role indicate significant academic impact.

Meiling Chengمشاهده پروفایل

استاد

• Performance Studies
• Live Art
• Intermedia Art
• +۱۲ مورد دیگر

Meiling Cheng is a Professor of Theatre Critical Studies at the University of Southern California’s School of Dramatic Arts, with joint appointments in the USC Roski School of Arts and Design and the USC Dornsife College of Letters, Arts and Sciences. Her research focuses on interdisciplinary performance, live art, and avant-garde theatre, combining critical theory with fieldwork and oral history. She holds a DFA from Yale University and has received grants from the Asian Cultural Council, Bass Fellowships, and the James H. Zumberge Research Fund. Dr. Cheng’s academic career spans over three decades, including roles as Director of Critical Studies and Area Head of Critical Studies at USC. She is affiliated with USC/UCLA’s East Asian Studies Center and co-founded the performance collective MoOM. Her books include In Other Los Angeleses: Multicentric Performance Art and Beijing Xingwei: Contemporary Chinese Time-Based Art , which explore multicultural and transnational art practices. Her research interests intersect performance studies, visual art, and cultural theory, with a focus on marginalized voices and global sociocultural dynamics. Awards include the Phi Kappa Phi Faculty Recognition Award and SC/W 2000 Exposition Award. She has curated international festivals and taught courses on contemporary kinesthetic theatre, intermedia art, and cultural studies. Educations: DFA in Theatre Arts (Yale University, 1993); MFA in Dramaturgy (Yale University, 1989) Key Collaborations: Co-edited Reading Contemporary Performance with Gabrielle Cody; worked with August Wilson, Lee Breuer, and Claudia Bucher Grants: Asian Cultural Council Dissertation Fellowship (1990–93), Newhouse Fellowships in Writing (1992–93) Her articles appear in TDR , Performance Research , and Positions: Asia Critique , analyzing performance art, installation, and feminist practices. She investigates themes like temporal art, multicultural performance, and the intersection of theatre and visual arts.

• Neuroscience
• Pain Research
• Palliative Care
• +۳ مورد دیگر

Carlo Adolfo Porro is a Professor at the Department of Biomedical, Metabolic and Neuroscience Sciences at the University of Modena and Reggio Emilia. His research focuses on neural mechanisms of pain , empathy processing , and palliative care integration in oncology and hematology. He employs fMRI and neuroimaging to investigate pain perception, emotional recognition, and placebo analgesia . Key Research Areas Neurobiology of pain and empathy Clinical applications in palliative care Temporal perception and motor cognition Placebo mechanisms in neurorehabilitation Methodological Expertise Functional MRI analysis Psycholinguistic pain models Placebo-controlled clinical meta-analyses Motor ideation-execution paradigms Collaborative Networks Italian Consensus Conference on Pain in Neurorehabilitation International palliative care research groups Neuroimaging consortia His recent work examines deceptive pain expressions , metaphorical language in palliative care , and neural substrates of semantic pain . Publications span from 2016 to 2025 , with emphasis on clinical neuroscience and patient-centered care models . Porro's team explores neural network interactions , emotional recognition circuits , and contextual factors in pain processing .

• Landscape Archaeology
• Cultural Landscapes
• Archaeological Field Techniques
• +۶ مورد دیگر

Darko Maricevic is a Lecturer in Archaeology at Bournemouth University's School of Applied Sciences, specializing in Field Archaeology and Collections management. His expertise spans landscape archaeology, field techniques, and post-excavation analysis, with a focus on western Scotland, the Southern Levant, and southern England. Education: PhD in Archaeology (University of Reading, 2010) Specialties: Excavation, geophysical prospection, digital survey, building recording, and data visualization Current Projects: Geophysical survey of the Neolithic cursus at Drumadoon (Isle of Arran) His research explores long-term cultural landscape development through archaeological prospection and remote sensing. Recent publications focus on Neolithic chambered cairns, Iron Age crannogs, and Bronze Age ceramic creativity, with recurring themes of stratigraphic analysis and digital archaeology. Scientific Awards: Fellow of the Society of Antiquaries of Scotland (2018-) Darko actively supervises student projects and contributes to public archaeology initiatives, including lectures at Oxford University and University of Reading. His grant history includes funding from the Society of Antiquaries of London and National Environmental Isotope Facility.

Kevin Eliceiriمشاهده پروفایل

استاد

• Biomedical Engineering
• Optical Imaging
• Computer Science
• +۶ مورد دیگر

Kevin Eliceiri is a Professor of Medical Physics and Biomedical Engineering at the University of Wisconsin–Madison, where he also serves as Director of the Center for Quantitative Cell Imaging. His primary affiliation is with the Department of Biomedical Engineering in the College of Engineering, with additional ties to the Wisconsin Institute for Discovery. Research Interests Development of optical imaging methods for cell signaling and cancer progression Software tools for multidimensional bioimage analysis (e.g., ImageJ/Fiji, PyImageJ, napari integration) Quantitative fluorescence lifetime imaging (FLIM) Label-free imaging techniques and polarization microscopy Tumor microenvironment characterization using collagen fiber analysis Machine learning in biomedical image processing Recent publications emphasize advancements in polychromatic polarization microscopy for pancreatic cancer diagnostics, collaborative bioimage analysis frameworks, and live tumor fragment platforms for immunotherapy assessment. His work bridges computational methods with clinical applications. Lab Affiliation Lead Investigator, Laboratory for Optical and Computational Instrumentation (LOCI) since 2000 Director, Center for Quantitative Cell Imaging

• Biophysics
• Dermatology and Venereal Diseases
• Structural Biology
• +۳ مورد دیگر

Lars Norlen is a Senior Lecturer affiliated with the Department of Medicine, Solna at Karolinska Institutet . His research focuses on the biophysical and structural analysis of the human skin barrier , utilizing advanced techniques such as cryo-electron microscopy (cryo-EM) and molecular dynamics (MD) simulations to investigate lipid organization, drug permeation mechanisms, and skin barrier formation. Key research areas include: Biophysics of lipid membranes Structural biology of epidermal components Computational modeling for skin permeability prediction Molecular organization of stratum corneum He has published extensively on skin barrier mechanisms, including landmark studies on ceramide-cholesterol interactions, cubic-to-lamellar phase transitions, and the role of keratin in barrier function. His work bridges dermatology , structural biology , and computational biophysics .

• Analytical Chemistry
• Chromatography
• Mass Spectrometry
• +۶ مورد دیگر

Mag.Dr. Heidi Elisabeth Schwartz-Zimmermann is a researcher at the Institute of Bioanalytics and Agro-Metabolomics within the University of Natural Resources and Life Sciences, Vienna (BOKU). Her work focuses on analytical chemistry, metabolomics, and mycotoxin research, with emphasis on biomarker development and animal health. PhD in Chemistry (University of Vienna, 2008-2011) Erasmus studies in Lille, France (2002-2003) Research interests include: mycotoxin biomarkers , targeted metabolomics methods , animal metabolomics , and food/feed safety . She specializes in HPLC-MS/MS and LC-MS/MS techniques for metabolite quantification. Recent publications highlight her expertise in comparing metabolomics workflows, optimizing chromatographic conditions, and analyzing mycotoxin mitigation strategies during food processing. Her work integrates analytical chemistry with practical applications in livestock health. Scientific Awards IFA Acquisition Award (2018) Czedik-Eysenberg Preis (2010) AKNÖ Förderpreis (2009) Promotion sub auspiciis (2009) Bundesministerium Würdigungspreis (2009) EuroFIR Posterpreis (2006) ISC Young Scientist Award (2004) Active in international collaborations, she contributes to Christian Doppler Laboratories and presents at global conferences like the Metabolomics Society and World Mycotoxin Forum.