جستجوی استاد راهنمای دانشگاهی

Masahiko Taniguchiمشاهده پروفایل

دانشگاهی

• Photochemistry
• Synthetic Chemistry
• Spectral Analysis
• +۳ مورد دیگر

Masahiko Taniguchi is an Associate Research Professor in the Department of Chemistry at North Carolina State University, located in Raleigh, NC. He is affiliated with the College of Sciences and contributes to the university's research initiatives in photochemistry and tetrapyrrole chemistry. Education: Dr. Taniguchi holds a Ph.D. in Engineering from Kyushu University (2000) and a B.S. in Pharmacy Science from the University of Tokyo (1995). Research Interests: His work focuses on synthetic tetrapyrrole pigments (porphyrins, chlorins, bacteriochlorins), their spectral properties, and applications in energy transfer, biomedical imaging, and artificial photosynthesis. He pioneers methods for spectral data acquisition using AI tools like chatbots and develops databases for chemical characterization. His studies explore prebiotic synthesis pathways of natural pigments and their modular design for photonic and catalytic systems. Publications: Dr. Taniguchi has published widely in journals like Photochemistry and Photobiology , Journal of Porphyrins and Phthalocyanines , and Dyes and Pigments , emphasizing spectral analysis, synthetic methodologies, and computational modeling. Awards: No awards explicitly mentioned in the provided texts. Advising & Grants: While no students are listed, his research group likely engages in collaborative projects given his extensive publication record. Funding sources are not detailed in the text. Labs & Teams: Based in Dabney Hall, he contributes to interdisciplinary efforts in synthetic chemistry and bio-inspired materials, leveraging NCSU's facilities for molecular design and spectral analysis.

• Structural Engineering
• Seismic Performance of Concrete Structures
• Anti-Terrorist Design
• +۳ مورد دیگر

Assoc Prof Li Bing is an Associate Professor at the School of Civil and Environmental Engineering, Nanyang Technological University (NTU). He specializes in structural engineering, with research focused on seismic performance of reinforced concrete structures, anti-terrorist design for infrastructure, and blast testing for explosive effects on concrete buildings. Dr. Li holds a B.Eng. in Structural Engineering from Tong Ji University and a Ph.D. from the University of Canterbury, New Zealand. He teaches courses on structural design and assessment, emphasizing reinforced concrete applications. His recent work explores innovative materials and methodologies for enhancing building safety and resilience against extreme events. His research interests span advanced materials characterization, failure mechanisms under dynamic loads, and sustainable construction practices. Notably, he has contributed to studies on glass-ceramic composites, MXene-based materials, and energy-efficient structural solutions. His articles reflect interdisciplinary approaches, combining material science, computational modeling, and engineering applications. Dr. Li’s academic contributions include advancements in electromagnetic wave absorption materials, transparent ceramics for laser applications, and neuromorphic device fabrication. His work bridges fundamental research with practical engineering solutions, addressing contemporary challenges in civil infrastructure resilience and safety.

Jeffrey Thomasمشاهده پروفایل

مدرس

• Competition and rivalry
• Voice
• Proactive behaviour
• +۳ مورد دیگر

Dr Jeffrey Thomas is a Lecturer in the Department of Management at the London School of Economics (LSE), joining in September 2017. His academic background includes a PhD in Management and Organizations from NYU Stern School of Business, a Master's in Industrial Organizational Psychology from Florida International University, and a BA in Psychology from the University of Buffalo. His research focuses on competition and rivalry , exploring how these dynamics shape identity and influence cooperative/competitive behaviors. He also investigates employee voice , examining the risks and motivations behind speaking up in organizational settings. Prior to academia, he worked as a consultant in leadership development, employee selection, and training across government, education, and manufacturing sectors. His scholarly work has been published in journals such as the Journal of Occupational and Organizational Psychology and Journal of Personality Assessment . His expertise extends to proactive behavior, leadership strategies, and the psychological underpinnings of organizational dynamics. Notable articles include studies on moral reasoning during global crises and predictive models for pandemic responses. His work bridges social science and organizational behavior, emphasizing practical applications for leadership and policy.

• Nano-optics
• Biophotonics
• Optical antennas
• +۷ مورد دیگر

Mikael Käll is a Professor of Nano- and Biophysics at Chalmers University of Technology. His research focuses on nano-optics, biophotonics, and plasmonic systems with applications in biosensors, nanorobotics, and optical manipulation. He leads a research group funded by the Swedish Research Council and the Knut and Alice Wallenberg Foundation. Research Interests : His work spans optical antennas, metasurfaces, thermoplasmonic effects, and light-driven nanomotors. Key areas include surface-enhanced Raman spectroscopy (SERS), nano-optical force engineering, and quantum light-matter interactions. Current projects explore directional fluid control via laser-induced bubbles and synchronized nanorotor systems. Grants & Funding : - Swedish Research Council grants for plasmonic biosensors and nanomotor systems - Wallenberg Foundation support for metamaterials and nano-optical devices - EU Horizon projects on light-driven nanoscale systems Labs & Teams : - Chalmers Nano-Photonics Lab (specializing in metasurface fabrication) - Biophotonics Group (developing single-molecule detection tools) - Nanorobotics Team (designing light-powered micromachines)

Nasir Mahmoodمشاهده پروفایل

پژوهشگر ارشد

• Functional Materials
• Electrochemical Energy Storage
• Water Treatment Technologies
• +۳ مورد دیگر

Associate Professor Nasir Mahmood is a Vice Chancellor's Senior Research Fellow and Associate Professor at RMIT University's School of Science (City Campus, Australia). His research focuses on functional materials, electrochemical energy storage, environmental science, and water treatment processes. He is actively involved in supervising PhD and Master's research projects related to nanomaterials, 2D materials, and energy conversion technologies. Research Interests: Dr. Mahmood’s work spans functional materials synthesis, electrochemical energy storage systems (e.g., lithium-ion batteries, sodium batteries), seawater electrolysis for hydrogen production, and environmental remediation. His projects include developing novel catalysts for water splitting, designing carbon-based nanomaterials for energy applications, and exploring sustainable waste-to-energy solutions. Recent Projects: Electrocatalytic Seawater Splitting to Hydrogen Nanomaterials for Sodium Batteries Development of Two-Dimensional Heterostructures for Metal Ion Batteries Photonics of Novel Two-Dimensional Semiconductors Publications: His 2025 publications highlight advancements in machine learning-assisted materials discovery, high-performance energy storage systems, and environmental applications of nanomaterials. Recent work includes innovations in carbon nanofiber synthesis, microwave absorption materials, and sustainable hydrogen production from seawater. Contact: nasir.mahmood@rmit.edu.au | ORCID: 0000-0002-8340-1058

• Optical design
• Freeform optics
• Computational imaging
• +۶ مورد دیگر

Yunfeng Nie serves as a postdoctoral researcher at the Applied Physics and Photonics department within the Faculty of Engineering at Vrije Universiteit Brussel. His research integrates optical engineering with computational methods, focusing on advanced imaging systems development. His primary research interests include Optical design , Freeform optics , and Computational imaging , with significant contributions in Deep learning applications for microscopy and endoscopy. His work bridges theoretical optics with practical medical imaging solutions, particularly in aberration correction and resolution enhancement. Analysis of his recent publications reveals a strong trend toward deep learning-enhanced optical systems , with increasing focus on medical diagnostics applications. His 2025 publications demonstrate convergence of optical modeling, neural networks, and hyperspectral imaging for cancer diagnostics and microscopic resolution enhancement. Scientific awards: Michael Kidger Memorial Scholarship award (2016) Rising star award from Journal of Optics (2024) Nie actively supervises graduate research and leads significant projects. His current research includes two major funded projects: Computational Incoherent holographic single-shot plenoptic camera (2024-2027) and Super-sensitive fluorescence biochip detection (2021-2024), demonstrating sustained research funding and leadership in optical engineering. His work is conducted within Brussels Photonics (B-Phot), a leading photonics research group at VUB, where he contributes to both theoretical optical design and practical imaging system development.

Salvatore Torquatoمشاهده پروفایل

استاد

• Statistical Mechanics
• Soft Condensed Matter Theory
• Hyperuniformity
• +۱۱ مورد دیگر

Professor Salvatore Torquato , Lewis Bernard Professor of Natural Sciences at Princeton University, leads the Complex Materials Theory Group at the Princeton Institute for the Science and Technology of Materials (PRISM). His work spans statistical mechanics, soft condensed matter theory, and interdisciplinary applications in biophysics and materials science. Research Interests: Hyperuniformity, packing problems, inverse statistical mechanics, multifunctional materials, quantum mechanics, cancer modeling, and biophysics. Scientific Awards: American Chemical Society Joel Henry Hildebrand Award (2017) Simons Foundation Fellowship (2012) Multiple Institute for Advanced Study memberships Guggenheim Fellow (1998) Publications & Collaborations: Recent work focuses on hyperuniform states across quantum systems, biological tissues, and photonic materials. His group collaborates with experimentalists in physics, applied mathematics, and mechanical engineering while developing novel theories for tumor growth and retinal cell arrangements. Contact: torquato@princeton.edu

Gábor Erdeiمشاهده پروفایل

دانشیار

• Optical Design
• Medical Imaging Systems
• Holographic Storage
• +۳ مورد دیگر

Gábor Erdei is an Associate Professor at the Department of Atomic Physics, Budapest University of Technology and Economics (BME). He specializes in optical design, materials science, and advanced imaging systems. His work focuses on scintillator arrays for PET detectors, holographic storage technologies, and biomedical optics applications. Dr. Erdei has contributed to projects involving photon pair sources, quantum interference, and ophthalmic lens design. Research Interests: Optical system design and optimization Scintillator material characterization Quantum photonics and entanglement Holographic data storage systems Medical imaging technologies Key Research Trends: His recent work explores advancements in quantum optics for secure communication, novel materials for improved PET detector performance, and personalized optics for enhanced visual acuity. He has also contributed to interdisciplinary projects combining machine learning with particle analysis in fluidization processes. Scientific Awards: None explicitly listed in available materials. Advising & Grants: No formal advisee records found. Involved in SPADnet project collaborations and holographic storage system developments. Labs/Teams: Active in BME's Optics and Photonics Research Group, contributing to projects on diffractive optics and biomedical imaging systems.

Antoine LAVIGNOTTEمشاهده پروفایل

مدرس

• Telecommunication Networks
• Machine Learning
• Optical Networks
• +۳ مورد دیگر

Antoine LAVIGNOTTE is a Lecturer at Telecom SudParis' NeSS (Network Security and Services) department. His research focuses on machine learning applications in telecommunications, optical networks, and network security. He has contributed to advancements in fault prediction, reinforcement learning for optical systems, and quality of experience (QoE) in multimedia streaming. Education : PhD in Multimedia (2014), Jean Monnet University - Saint-Etienne: Thesis titled 'Considering the quality of user experience within adaptive HTTP streaming protocols.' Research Interests : MACHINE LEARNING APPLICATIONS: Network fault prediction, optical amplifier control, and dynamic resource allocation in optical networks. NETWORK SECURITY: 5G slice embedding security and multi-provider network virtualization. QUALITY OF EXPERIENCE: User-centric metrics in adaptive streaming and 3D multimedia systems. Recent Trends in Publications : His work emphasizes machine learning-driven solutions for telecom infrastructure resilience, optical network optimization, and security frameworks for next-generation networks. Collaborations with institutions like SAMOVAR highlight his engagement in applied research. Advising : Supervised Killian Murphy's 2024 thesis on predictive maintenance in telecom networks. Active in guiding interdisciplinary projects at Telecom SudParis. Labs & Teams : Member of SAMOVAR lab, a leading research group in network sciences and telecommunications at Telecom SudParis.

Thomas Van Den Driesمشاهده پروفایل

پژوهشگر

• Image Sensors
• CMOS Chip Design
• Fluorescence Lifetime Imaging
• +۳ مورد دیگر

Thomas Van Den Dries is a postdoctoral researcher at the Vrije Universiteit Brussel (VUB), affiliated with the Department of Electronics and Informatics (ETRO). His research focuses on developing sub-nanosecond time-gated image sensors (Current-Assisted Photonic Samplers, CAPS) for real-time fluorescence lifetime imaging applications, particularly in medical diagnostics and surgical guidance. He holds a PhD in micro- and nano-electronics from VUB (2023) and an M.Sc. in Electrical Engineering (2018), both with highest honors. Key research areas include image sensor design, CMOS chip technology, and photonics. He has contributed to projects like CoDaFlight (2022–2026), focusing on fluorescent light imaging. His work spans preclinical studies using animal models, endoscopy imaging systems, and novel fluorophore development for in vivo applications. Affiliations: VUB, ETRO Department, CoDaFlight Project Grants: Active EUAR96 grant (CoDaFlight) Labs/Teams: Collaborates with Hernot, Lapauw, and Ingelberts on FLIM systems Notable awards include the BrEA Prize (2018), IMEC’s Best Master Thesis (2018), and SPIE Europe Innovation Award (2022). He has authored over 20 peer-reviewed publications and contributed to conferences on biomedical imaging and sensor technology.

Abbas Kaziempourمشاهده پروفایل

مدرس

• Deep Learning
• Machine Learning
• Neuroscience
• +۶ مورد دیگر

Abbas Kaziempour is a Lecturer at the School of Data Science, University of Virginia. He holds a Ph.D. in Electrical Engineering from the University of Maryland and a B.S. in Electrical Engineering from the University of Tehran. His research bridges deep learning, signal processing, and neuroscience, focusing on optimization, nonlinear dimensionality reduction, and biomedical imaging technologies. Ph.D., Electrical Engineering, University of Maryland B.S., Electrical Engineering, University of Tehran Kaziempour's work spans three key areas: (1) advancing deep learning theory through analysis of loss landscapes and optimization algorithms, (2) developing compressed sensing and polynomial PCA techniques for neuroscience and biomedical signal processing, and (3) engineering high-speed imaging systems like kilohertz frame-rate two-photon tomography. His recent publications highlight methodological innovations in machine learning and their applications to neural data analysis. As an applied scientist at Amazon's search relevance team, he translates theoretical insights into practical feature design and modeling solutions for industrial-scale problems. His academic contributions include (1) theoretical guarantees for sparse model recovery, (2) stability analysis of autoregressive estimation, and (3) novel approaches to signal deconvolution using state-space models.

Liu Qiمشاهده پروفایل

استادیار

• Natural Language Processing
• Machine Learning
• FinTech
• +۳ مورد دیگر

Qi Liu is an Assistant Professor at the Department of Computer Science, University of Hong Kong, and serves as Programme Director for the BASc(FinTech) Programme. He holds an MS from the National University of Singapore and a PhD from the University of Oxford. His research focuses on Natural Language Processing (NLP), Machine Learning (ML), and FinTech. He has contributed to leading conferences/journals such as NeurIPS, ICML, ICLR, ACL, and EMNLP, and actively serves on their program committees. His work includes advancements in relational memory models, causal inference, graph neural networks, and domain-specific representation learning. Key research areas include NLP applications in dialogue systems, counterfactual data augmentation for translation, and hyperbolic representations for knowledge graphs. Recent articles explore cutting-edge topics in photonics, spintronics, and memory device security, reflecting interdisciplinary interests. Education: MS (NUS), PhD (Oxford) Programme Role: BASc(FinTech) Director Email: liuqi@cs.hku.hk Homepage: leuchine.github.io No scientific awards are explicitly listed in the provided text. His research spans theoretical ML advancements and applied FinTech systems, with a focus on scalable NLP solutions and secure memory technologies.

• Biomedical Imaging
• Cancer Research
• Nanotechnology
• +۲ مورد دیگر

Dong Li serves as a Research Fellow in Biomedical Science Histology within the School of Natural Sciences at Middlesex University. His research integrates computational methods with biomedical science to address challenges in cancer diagnostics and treatment, particularly focusing on human papillomavirus (HPV) and cervical cancer. Research Interests: Dr. Li's work spans four primary domains: Biomedical Imaging : Application of deep learning and GANs to detect and visualize HPV in microscopic images. Cancer Modeling : Development of 3D in vitro models for breast and cervical tissues to study cancer progression. Nanomedicine : Design of folate-mediated liposomal systems for targeted arsenic trioxide delivery in cervical cancer therapy. Molecular Oncology : Investigation of hCG beta's role in epithelial-mesenchymal transition and tumor invasion pathways. Publication Trends: Dr. Li's 14 publications (2008-2022) demonstrate an evolution from molecular/cellular studies toward AI-driven diagnostics. Early work (2008-2015) focused on tissue engineering and drug mechanisms, while recent efforts (2020-2022) leverage deep learning for HPV detection, revealing interdisciplinary innovation at the oncology-computer science-nanotechnology intersection. Scientific Awards: None documented. Advising and Grants: No details provided regarding student supervision or research funding. Research Groups: Affiliated with a Histology Research institute, indicating active collaboration within specialized histology and biomedical imaging research teams at Middlesex University.

John P. Kerekesمشاهده پروفایل

استاد پژوهش

• Remote Sensing
• Imaging Science
• Digital Imaging
• +۳ مورد دیگر

John P. Kerekes is a Research Professor at the Chester F. Carlson Center for Imaging Science within the College of Science at Rochester Institute of Technology (RIT) . With a career focused on advancing remote sensing technology, his work spans theoretical modeling, data analysis, and system design for applications in environmental monitoring, agriculture, and medical imaging. Education: BS, MS, and Ph.D. in Electrical Engineering from Purdue University . Research Interests: Dr. Kerekes investigates end-to-end remote sensing systems, emphasizing statistical parametric models to understand sensor performance. His research includes hyperspectral imaging for subpixel target detection, lidar-based surface profiling, atmospheric monitoring, and biomedical applications. Recent projects explore methane detection, urban air quality, and satellite-based crop yield estimation. Article Trends: His publications focus on hyperspectral imaging , lidar systems , and spectral modeling , with subfields like subpixel detection, environmental monitoring, and algorithm development. Collaborative efforts address real-world challenges in agriculture and climate science. Scientific Awards: Jefferson Science Fellowship (2019) Stanford University’s Top 2% of Scientists List (2022) Advising and Grants: He mentors graduate students in imaging science. Funded by the National Geospatial-Intelligence Agency (NGA) with a $1M grant (2021), his team studies spectral remote sensing limits. He also contributed to NASA’s citizen science initiatives.

Slavisa Aleksicمشاهده پروفایل

استاد

• Communication Technology
• Network Infrastructure and Cloud
• Data Science
• +۷ مورد دیگر

Dr. Slavisa Aleksic is a Professor for Network Technologies and Network Management at the Faculty of Digital Transformation , Leipzig University of Applied Sciences (HTWK Leipzig) since February 2021. Previously, he held academic roles at Hochschule für Telekommunikation Leipzig (2015-2021), TU Wien (2010-2015), IBBT, Ghent University (2011), and TU Wien in various capacities since 1999.