جستجوی استاد راهنمای دانشگاهی

• Electronics
• Optics
• Physics
• +۸ مورد دیگر

Dr. Cristina de Dios Fernández is an Associate Professor at Carlos III University of Madrid, affiliated with the School of Engineering and the Department of Electronic Technology . She leads the research group Sensors and Instrumentation Techniques (SIT) and holds an ORCID iD 0000-0001-5474-7407 . Research Interests span Photonics , Terahertz Technologies , Optical Frequency Combs , Quantum Sensing , Biomedical Optics , and Integrated Photonics . Her work focuses on Developing compact confocal microscopes for nitrogen-vacancy centers Advancing dual-comb spectroscopy for biomedical and industrial applications Optimizing VCSEL-based optical frequency combs Designing photonic chips for THz dual-comb spectrometers Projects & Grants include principal investigator roles in initiatives like Cátedra Universidad-Empresa EPIQ (2024-2027) and HYPERTERA (2019-2020), alongside researcher roles in EU-funded programs such as OILTEBIA (2013-2017) and CELTA (2016-2020). Patents include Hyperspectral Imaging based on Dual Frequency Comb (2022), and she supervised the thesis VCSEL-based Optical Frequency Comb Generation, Expansion and Optimization (2016).

• Optoelectronics
• Liquid Crystal Technologies
• Visible Light Communication (VLC)
• +۴ مورد دیگر

Juan Carlos Torres Zafra is a Visiting Professor at Universidad Carlos III de Madrid. His research focuses on optoelectronics, liquid crystal technologies, visible light communication (VLC), and sensor systems. His work spans interdisciplinary areas including energy-harvesting IoT nodes, indoor positioning systems, and optical communication interfaces for high-definition media transmission. Torres Zafra has contributed to advancements in semiconductor materials (e.g., perovskites), low-cost sensor networks, and hybrid RF-VLC positioning systems. His research also extends to educational technology, exploring tools like Telegram and Google Workspace for improving student engagement in cybersecurity engineering programs. Notable projects include the GUTI group's work on optical vortices using liquid crystal devices and the development of tunable resonators based on liquid crystal capacitance. His publications from 2020–2025 highlight trends in VLC system optimization, AI-driven disinformation detection (SmartVote-AI initiative), and medical studies on amyloidosis therapy outcomes. Torres Zafra’s work often emphasizes practical applications in robotics, automotive systems, and sustainable energy solutions. While no formal awards are listed, his extensive publication record (over 80 entries from 2004–2025) reflects sustained contributions to photonics, sensor engineering, and liquid crystal device innovation. His research integrates hardware design, algorithm development, and material science to address challenges in modern communication systems and assistive technologies for visually impaired patients.

• Nanomedicine
• Targeted Drug Delivery Systems
• Antimicrobial Peptides
• +۷ مورد دیگر

Rohan Shah is a Lecturer at Swinburne University of Technology's Department of Chemistry and Biotechnology, School of Science, Computing and Emerging Technologies. He holds a PhD from Swinburne, supported by the Victoria-India Doctoral Scholarship, and was awarded the Sparrho Early Career Researcher Prize for lipid nanoparticle work. His research focuses on nanomedicine, antimicrobial peptides, and sustainable biotechnology solutions for global health challenges. He has held academic roles at Swinburne and RMIT, including Lecturer and Academic Tutor, and is a registered pharmacist and Chartered Member of the Royal Australian Chemical Institute (RACI). Dr. Shah's research explores targeted drug delivery systems, systems biology, and metabolomics applications in food and environmental science. He has secured significant grants (e.g., $1.2M+ in external funding) and collaborates globally. His editorial roles include Frontiers in Sustainable Food Systems, Metabolites, and Food Science and Nutrition Cases. He has authored over 100 publications, with recent work addressing PFAS toxicity in wildlife, food additive health impacts, and nanoformulated drug delivery. Professional activities include serving as Treasurer of the RACI's Early Career Chemists Group and committee roles in the Young Chemists Group. His work spans 15+ years of grants, 99+ publications, and supervision of four HDR students. He advocates for food additive reformulation, sustainable technologies, and improved drug delivery systems.

Patrick Vogelمشاهده پروفایل

پژوهشگر

• Magnetic Particle Imaging
• Medical Imaging
• Nano-Optics
• +۳ مورد دیگر

Dr. Patrick Vogel is a Habilitation candidate and researcher in the Magnetic Particle Imaging (MPI) group at the University of Würzburg's Faculty of Physics and Astronomy, Department of Experimental Physics V. His work focuses on advancing MPI technology for clinical applications, including imaging safety assessments, interventional procedures, and nanoparticle-based diagnostics. He contributes to the development of portable MPI scanners and hybrid imaging systems, collaborating with the AG Behr research group. His research spans magnetic particle spectroscopy, vascular imaging, and biomaterial characterization. Vogel has pioneered studies on MPI-guided endovascular interventions and the application of MPI in perfusion models. His work bridges physics, biomedical engineering, and clinical practice, with a focus on translating MPI into real-world medical diagnostics and surgery support. Key projects include the design of human-sized MPI scanners, safety evaluations of medical implants, and the use of synthetic tracers like Synomag®. He collaborates with interdisciplinary teams to address challenges in vascular imaging, nanoparticle behavior analysis, and real-time imaging systems.

• Particle Physics
• Dark Matter
• Supersymmetry
• +۵ مورد دیگر

Dr. Anwar Bhatti is a Research Professor in the Department of Physics at the University of Maryland, affiliated with the CMS collaboration at CERN's LHC and the LZ Dark Matter Experiment. His research focuses on fundamental particle physics, including searches for dark matter, supersymmetry, and Higgs boson properties. He has contributed to experiments at the Large Hadron Collider (LHC), Fermilab's CDF collaboration, and the Sanford Underground Research Facility. Dr. Bhatti also served as a program manager in the U.S. Department of Energy's High Energy Physics Office, overseeing projects like the LUX-ZEPLIN (LZ) experiment, the Axion Dark Matter eXperiment (ADMX), and cosmic frontier initiatives. His work spans detector development, data analysis, and program management in high-energy physics, with expertise in liquid xenon technology and low-background experiments. He teaches introductory physics laboratory courses, emphasizing experimental techniques and data analysis for undergraduate students. Research Interests: Dr. Bhatti's work revolves around uncovering the nature of dark matter through direct detection experiments (e.g., LZ) and collider searches for supersymmetric particles. He investigates Higgs boson properties, explores models of extra dimensions, and analyzes data from the CDF and CMS detectors. His contributions to the DOE included managing projects like the South Pole Telescope (SPT-3G) and Fermi Gamma-ray Space Telescope, fostering international collaborations in cosmic frontier research. His technical expertise includes detector calibration, data acquisition systems, and background modeling for rare event searches. Key Projects: LZ experiment (dark matter detection), CMS collaboration (LHC physics), CDF top quark studies, DOE program management (ADMX, PICO-60), and teaching experimental physics laboratories.

• Stochastic Simulation
• Optimization
• Machine Learning
• +۵ مورد دیگر

Giulia Pedrielli is an Associate Professor at Arizona State University's School of Computing and Augmented Intelligence, with affiliations as a Senior Global Futures Scientist. She holds a Ph.D., M.Sc., and B.S. in Mechanical and Industrial Engineering from Politecnico di Milano, Italy. Her research focuses on stochastic simulation, optimization, and machine learning applications in biomanufacturing, digital twins, and cyber-physical systems. She has contributed to frameworks for pandemic modeling (PySIRTEM), RNA design, and high-dimensional optimization. Pedrielli has collaborated with institutions like NUS and UC Berkeley, and her work spans biomedical engineering, supply chain resilience, and security of critical infrastructure. Recent articles emphasize co-simulation tools, AI-driven logic translation, and falsification methods for CPS security. Her teaching includes advanced stochastic simulation courses and thesis supervision across multiple disciplines. Education: Ph.D. Mechanical Engineering, Politecnico di Milano, Italy M.Sc. Industrial Engineering, Politecnico di Milano, Italy B.S. Industrial Engineering, Politecnico di Milano, Italy Research interests integrate simulation-based optimization with machine learning, particularly in safety-critical systems like healthcare and smart infrastructure. She develops digital twin methodologies for real-time control under uncertainty, leveraging Gaussian processes and Bayesian approaches. Pedrielli's work bridges theoretical advancements (e.g., BASSO optimization algorithm) with practical applications in biomanufacturing and pandemic response.

Anthony Rizzoمشاهده پروفایل

استادیار

• Integrated photonics
• Quantum photonics
• Neuromorphic photonics
• +۴ مورد دیگر

Anthony Rizzo is an Assistant Professor of Engineering at Dartmouth College, leading the Rizzo Integrated Photonic Systems Laboratory. His research focuses on integrated photonics, quantum photonics, and neuromorphic photonics, with applications in high-speed data communication, quantum computing, and energy-efficient systems. He holds a PhD in Electrical Engineering from Columbia University (2022), an MS from Columbia (2019), and a BS in Physics from Haverford College (2017). His work has been funded by organizations such as the Toyota Research Institute and the U.S. Army Research Laboratory. Key research areas include silicon photonics for ultra-low energy optical interconnects, photonic-electronic integration, and novel photonic materials like aluminum nitride. Notable achievements include the first demonstration of a Kerr comb-driven silicon photonic link and advancements in 3D photonic integration for terabit-scale data links. His lab explores applications in quantum sensing, neuromorphic computing, and visible wavelength photonics for atomic systems. Funding Sources: Toyota Research Institute, U.S. Army Research Laboratory, Thayer School of Engineering, AIM Photonics Courses Taught: ENGS 23 (Distributed Systems and Fields), ENGS 60 (Solid-State Electronic Devices) Recent publications highlight breakthroughs in ultra-low loss waveguides, scalable photonic linear neurons, and energy-efficient modulators. His work bridges fundamental photonics research with practical applications in next-generation communication and computing systems.

Kwaku Dayieمشاهده پروفایل

استاد

• RNA structural biology
• Nuclear Magnetic Resonance (NMR) spectroscopy
• Biophysical methods
• +۷ مورد دیگر

Kwaku Dayie is a Professor in the Department of Chemistry and Biochemistry at the University of Maryland. His research focuses on RNA structural biology, NMR spectroscopy, and biophysical methods to study RNA dynamics and function. He leads a lab developing advanced NMR techniques for large RNA molecules and has contributed to understanding RNA's role in catalysis, gene regulation, and viral processes. Education: B.A., Physics with Honors, 1990, Hamilton College Ph.D., Biophysics, 1996, Harvard University Postdoctoral, MIT (1998), Scripps Research Institute (2000) Research Interests: The structural basis of RNA signaling in pathogenic bacteria, RNA viruses (HIV, HBV), and long noncoding RNAs. His lab develops isotopic labeling methods and NMR tools to study RNA dynamics and function, aiming to guide RNA-based drug design. Awards: Henry C. Welcome Fellowship (2008) National Technical Association Nsoroma Technology Award (2007) Jane Coffin Childs Memorial Fund Postdoctoral Fellowship (1998) Grants & Service: NIH review panelist (2012-2018), NSF reviewer (2005-2006), and judge for Intel ISEF (2003). Serves on editorial boards for Molecules and NPG Scientific Reports (2018). Labs & Teams: Directs an interdisciplinary lab focused on RNA structural biology, collaborating on NMR method development and RNA-drug interaction studies.

Shuvra S. Bhattacharyyaمشاهده پروفایل

استاد

• Signal Processing
• Embedded Systems
• Biomedical Engineering
• +۳ مورد دیگر

Shuvra S. Bhattacharyya is a Professor at the University of Maryland, College Park (UMD), Department of Electrical and Computer Engineering, with a joint appointment in UMIACS. He is also a part-time visiting professor at Tampere University (Finland) and INSA Rennes (France). His research focuses on signal processing systems, embedded systems, biomedical engineering, and machine learning. He has authored 7 books and over 300 papers, and directs the Maryland DSPCAD Research Group. He holds an NSF Career Award and is an IEEE Fellow. His honors include the Fulbright Senior Specialist and FiDiPro Professorship. He advises graduate students and leads projects in neural decoding, cyber-physical systems, and criminal justice AI. Education: B.S., University of Wisconsin-Madison Ph.D., University of California, Berkeley Research Interests: Signal processing architectures, biomedical circuits, embedded software, hardware/software co-design, and AI for healthcare and criminal justice. His work emphasizes real-time systems, energy efficiency, and interdisciplinary applications. Grants & Awards: NIH Grant for real-time neural decoding (2023) IEEE Fellow (2011) Jimmy Lin Entrepreneurship Award (2012) Labs & Teams: Maryland DSPCAD Research Group, collaborating on dynamic data-driven systems, neural interface technologies, and AI ethics in criminal justice. His work integrates academic and industrial partnerships, including roles at Hitachi America and Kuck & Associates.

Thomas Cokelaerمشاهده پروفایل

پژوهشگر

• Bioinformatics
• Data Analysis
• Machine Learning
• +۱۲ مورد دیگر

Thomas Cokelaer is a researcher at the Institut Pasteur, affiliated with the Bioinformatics and Biostatistics HUB and based at the Platform Biomics. Since October 2018, he has led the SALSA (dry-lab) group, focusing on bioinformatics software development and data analysis. His interdisciplinary background spans astronomy, plant modeling, systems biology, and drug discovery. Institution: Institut Pasteur Unit: Bioinformatics and Biostatistics HUB Platform: Platform Biomics Group: SALSA (dry-lab group) leader His research interests center on bioinformatics, next-generation sequencing (NGS) analysis, machine learning, data visualization, and reproducible research. He develops and maintains several widely used open-source tools including Sequana (NGS pipelines), BioServices (biological web services), Bioconvert (format conversion), Sequanix (GUI for Snakemake), and GDSCTools (pharmacogenomics). He is deeply committed to promoting reproducibility in computational research through initiatives like reprohackathons. The recent publications reflect a strong trend in computational biology, with a focus on developing bioinformatics methodologies, improving data analysis workflows, and applying these tools to diverse biological problems such as fungal pathogenesis, cancer pharmacogenomics, mitochondrial metabolism, and viral evolution. The work spans genomics, transcriptomics, systems biology, and software engineering. He has contributed to numerous scientific software projects as Principal Investigator, including Sequana, Bioconvert, GDSCTools, DREAMTools, and Sequanix. He has also taught courses in scientific programming with Python and reproducible data analysis at the Institut Pasteur. His collaborative network includes researchers from EMBL-EBI, Sanger Institute, INRIA, and international partners within the Pasteur Network. The SALSA group hosts master’s students and visiting researchers annually.

• Visible Light Communication
• Optical Wireless Communication
• Mobile Ad Hoc Networks
• +۳ مورد دیگر

Thomas D. C. Little is a Professor at Boston University, USA, specializing in Visible Light Communication (VLC), Optical Wireless Communication, and Mobile Ad Hoc Networks. His research focuses on hybrid RF/VLC systems, interference mitigation, and dynamic network optimization under illumination constraints. Recent work includes 3D localization via zone-based positioning Dynamic FOV receiver optimization Multi-tier transmission for 5G Li-Fi Security-aware OFDM modulation Research interests center on integrating optical wireless with traditional RF networks, developing energy-efficient communication protocols, and creating positioning systems for smart spaces. Publications analyze spectral efficiency, channel modeling, and coexistence strategies in dense optical environments. Collaborations span institutions in the USA and Germany, with applications in Industry 4.0 and coastal monitoring systems. His team has contributed to ns-3 simulator extensions for VLC, beam control in FSO systems, and interference analysis in optical networks. Current projects address reconciling SNR models and optimizing handover parameters via Q-learning for heterogeneous deployments.

Rishabh Dabralمشاهده پروفایل

پژوهشگر

• 3D Computer Vision
• Computer Graphics
• Multi-Modal Interactions
• +۶ مورد دیگر

Rishabh Dabral is a Research Group Leader at the Max Planck Institute for Informatics since August 2024, leading the "3D Visual Intelligence" group. He is also affiliated with the Research Training Group on Neuro-Explicit Models of Language, Vision, and Action at Saarland University. Expertise: 3D computer vision, computer graphics, human-object interaction modeling, and motion synthesis. Leadership: Conducts cutting-edge research on 3D human performance capture and physical plausibility in motion. His research focuses on: 3D human pose estimation under gravity constraints Multi-modal gesture synthesis using neural architectures Quantum auto-encoding for 3D representations Wearable robotics informed by human behavior Temporal dynamics in human-object interaction Recent publications at top venues like SIGGRAPH , CVPR , and ICCV demonstrate his work on: Music-driven motion synthesis Egocentric motion capture systems Reactive two-person interaction models Diffusion-based gesture generation Object-aware motion prediction Wearable robotic limb design

Kevin Macdonaldمشاهده پروفایل

استاد پژوهش

• Nanophotonics
• Optical Metrology
• Metamaterials
• +۳ مورد دیگر

Professor Kevin Macdonald is a Research Professor at the University of Southampton, affiliated with the Nanophotonics Group within the Optoelectronics Research Centre (ORC). His research focuses on advanced optical metrology, nanophotonics, and metamaterials, with particular emphasis on picoscale precision and time crystal dynamics. He currently supervises multiple PhD students in areas such as photonic localization and metamaterial-based systems. Active research projects include: A Photonic-electronic Non-von Neumann Processor Core (EPSRC-funded) Next Generation Optical Metrology Driven by Nanophotonics (EPSRC) Pixelated Chalcogenide Meta-Devices (Samsung-funded) His work bridges fundamental photonics with applied technologies, addressing challenges in high-speed imaging, quantum systems, and nano-scale motion tracking. He collaborates extensively with international researchers and industry partners, including Samsung Electronics. His labs are equipped with cutting-edge facilities for optical metrology and metamaterial fabrication.

Dragan Djurdjanovicمشاهده پروفایل

استاد

• Manufacturing Systems Engineering
• Advanced Quality Control
• Proactive Maintenance Techniques
• +۳ مورد دیگر

Dragan Djurdjanovic is the Accenture Endowed Professor of Manufacturing Systems Engineering at The University of Texas at Austin's Department of Mechanical Engineering. He holds a Ph.D. from the University of Michigan and has expertise in advanced quality control, proactive maintenance, and data analytics in biomedical engineering. His research bridges manufacturing systems, semiconductor processes, and human performance monitoring. Djurdjanovic directed the NSF I-UCRC on Intelligent Maintenance Systems and co-authored over 69 journal papers. Awards include the SME's Outstanding Young Manufacturing Engineer Award and CIRP membership. Education: B.S. Mechanical Eng. & Applied Mathematics (1997), University of Niš, Serbia M.S. Mechanical Eng. (1999), Nanyang Technological University, Singapore M.S. Electrical Eng. (Systems), Ph.D. Mechanical Eng. (2002), University of Michigan Research Focus: Djurdjanovic’s work emphasizes system-level optimization in manufacturing, including virtual metrology for semiconductor processes and predictive maintenance. He applies probabilistic modeling to neuromusculoskeletal systems and integrates IoT in manufacturing metrology. Recent articles address energy-efficient control, fatigue monitoring, and big data analytics in industrial systems. Awards: Fellow of the International Society for Engineering Asset Management 2018 August-Wilhelm Scheer Visiting Professorship Labs/Teams: Associate Director of the NSF Engineering Research Center on Nanomanufacturing (NASCENT) and leader of the Cyber-Physical Manufacturing Metrology Model (CPM3) initiatives.

• Intelligent Transportation Systems
• Connected and Autonomous Vehicles
• Vehicular Networks
• +۶ مورد دیگر

Daxin Tian is a prominent professor at Beihang University's School of Transportation Science and Engineering, specializing in intelligent transportation systems and vehicular networks. With over 170 publications spanning from 2006 to 2025, his research has significantly contributed to the advancement of connected and autonomous vehicle technologies. His work appears consistently in top-tier IEEE journals including IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Intelligent Vehicles, and IEEE Internet of Things Journal, establishing him as a leading authority in the field. Professor Tian's research interests encompass several critical areas in modern transportation technology: Connected and Autonomous Vehicle Systems Vehicular Networking and Communication Protocols Vehicle Platooning and Cooperative Driving Algorithms Edge Computing Applications for Transportation Computer Vision for Autonomous Driving Perception Traffic Flow Optimization and Prediction Models Resource Allocation in Vehicular Networks His recent publications demonstrate an increasing sophistication in addressing complex multi-vehicle scenarios while maintaining practical considerations like communication reliability, energy efficiency, and safety constraints. The research trajectory shows a clear evolution from foundational networking and control problems toward more integrated AI-driven solutions that combine computer vision, natural language processing, and advanced control theory for next-generation transportation systems. Professor Tian maintains extensive international collaborations, particularly with researchers at Canadian institutions including Victor C. M. Leung's group, while leading a substantial research team at Beihang University. His work frequently bridges theoretical advances with practical transportation challenges, resulting in numerous high-impact publications that address real-world implementation barriers in intelligent transportation systems.