جست‌وجوی استاد و پژوهشگر

• Antenna measurements
• Antennas
• Radar imaging
• +۷ مورد دیگر

Riccardo Maggiora is an Associate Professor at the Department of Electronics and Telecommunications (DET) within the College of Electronic, Telecommunications and Physics Engineering at Politecnico di Torino. He holds a position under academic regulation L. 240 and is actively involved in teaching and research activities through the 2025/26 academic year. His research focuses on antenna measurements, radar imaging, synthetic aperture radar, and electromagnetic fields. His work spans radar system design and prototyping, real-time locating systems, and low-cost space systems. He leads the Applied Electromagnetics and Nanosatellites research groups and is associated with the 4C Polito Space S.p.A. laboratory. His expertise in high-frequency technology and signal processing aligns with UN Sustainable Development Goals 9 (Industry, Innovation, and Infrastructure) and 11 (Sustainable cities and communities). His recent publications demonstrate expertise in automotive radar systems operating at 77 GHz, binary-phase versus frequency-modulated radar technologies, and applications in vehicle safety systems. His work bridges theoretical electromagnetic concepts with practical engineering implementations across multiple domains including automotive, telecommunications, and fusion energy research. SUNIFIX STEM (2022-2023): Development of Climate Neutral Nitrogen Factor Reactor LIFE STOPVESPA (2015-2019): Environmental monitoring project VESPA VELUTINA (2014): System for identification and control of Vespa velutina nests SRT_LOCUPS (2011-2013): Ultra Precise and Secure Real-Time Localization System He supervises PhD students including Simone Porporato, Francesco Biletta, and Mattia Caffa, focusing on antennas, electromagnetic devices, propagation, radars, and radio frequency/microwave electronics. His teaching portfolio includes Radar and Remote Sensing, Applied Communication Systems and IoT, and Guiding Electromagnetic Systems across multiple academic years through 2025/26. His laboratory work involves advanced antenna measurement facilities and radar prototyping with diverse applications from automotive safety to environmental monitoring.

Yurii Vlasovمشاهده پروفایل

استاد

• Neuroengineering
• Integrated neural probes
• Neurophotonics
• +۱۷ مورد دیگر

Dr. Yurii Vlasov is a Professor at the University of Illinois at Urbana-Champaign , holding tenured positions in Electrical and Computer Engineering, Physics, Bioengineering, and Materials Science and Engineering. He serves as the John Bardeen Endowed Chair and is Inaugural Professor at the Carle Illinois College of Medicine. At UIUC, he founded the Integrated Neurotechnology Lab , focusing on silicon-based neural probes, in vivo neurobiology, and machine learning for neural datasets. Prior to academia, he led IBM's Silicon Nanophotonics project for 15 years, driving its commercialization for datacenters. Education: MS in Biophysics (1988, University of St.-Petersburg), PhD in Physics (1994, Ioffe Institute) His research spans three threads: Neuro-engineering (nanofluidic/neurophonic probes), Neuro-biology (in vivo brain activity mapping), and Neuro-informatics (machine learning for neural networks). Recent work in ACS Nano and Lab on a Chip demonstrates attomole-level neurochemical detection using silicon nanofluidics. His innovations in droplet microfluidics and optogenetics have been featured in over 100 invited talks and 300+ patents. Scientific awards include National Academy of Engineering membership , Scientific American's Scientist of the Year , and multiple IBM Technical Achievement Awards . He is a Fellow of APS, IEEE, and OSA. Dr. Vlasov teaches core courses in semiconductor devices, silicon photonics, and neural interface engineering. His lab's silicon microfluidic platforms have enabled breakthroughs in neurochemical sampling and implantable probe fabrication, supported by NIH BRAIN Initiative grants (UF1NS107677, RF1NS126061).

• Neurosurgery
• Medical Imaging
• Inflammation
• +۳ مورد دیگر

Jan Willem Berkelbach vd Sprenkel is an Assistant Professor at the University Medical Center Utrecht, specializing in medical research within the Brain strategic program. His work bridges neurosurgery and biomedical innovation , focusing on improving surgical precision through advanced imaging and simulation technologies. Key Research Areas: Neurosurgery, Medical Imaging, Inflammatory Vascular Pathologies Technologies: Virtual Drilling, Ultra-High-Field MRI, RNA-Sequencing Research Trends in his publications highlight: Image-guided surgical tools for anatomical orientation Molecular insights into brain arteriovenous malformations Infection prevention in neurosurgical procedures Collaborations include international neurosurgical teams and translational research groups focused on cerebrovascular health.

Pim de Jongمشاهده پروفایل

استاد

• Radiology
• Cardiovascular Disease
• AI in Medical Imaging
• +۵ مورد دیگر

Pim de Jong is a Full Professor of Radiology actively engaged in cardiovascular imaging research. He leads projects within strategic programs including Cancer, Circulatory Health, Infection & Immunity, and Regenerative Medicine & Stem Cells. Research Focus: His work centers on calcification formation as a repair mechanism and smoking-related disease, utilizing advanced imaging and AI for individualized detection, prediction, and minimally invasive treatment of cardiovascular disease. Current Positions: PhD Supervisor at Philips Healthcare Adviser to Fahr Patienten Vereniging Nederland Medical Expertise Committee at Nederlandse Vereniging voor Radiologie Contact: Email: pimdejong@gmail.com Research Group: Cardiovascular Imaging and Image-Guided Treatment

• Multi-Dimensional Signal Processing
• System Modelling and Identification
• Image and Video Processing
• +۵ مورد دیگر

Mårten Sjöström is a Professor in Signal Processing at Mid Sweden University, where he serves as the highest representative of the research subject Computer and System Sciences and is part of the managerial group of the Department of Information and Communication Systems (IKS). He leads the Realistic 3D research group and has extensive experience in both academic and industrial settings. His educational background includes a Master of Science from Linköping University (Applied Physics and Electrical Engineering, 1992), a Technical Licentiate degree from the Royal Institute of Technology, Stockholm (Signal Processing, 1998), and a PhD from Ecole Polytechnique Federale de Lausanne (Modelling of Non-linear Systems, 2001). He obtained his Docent degree (Associate Professor) in 2008 and Professor's degree in Signal Processing in 2013. His primary research focuses on Multi-Dimensional Signal Processing with emphasis on System Modelling and Identification. He has successfully applied these techniques to Image and Video Processing, Multi-media Communications, and currently specializes in Multi-Scopic 3D and Light Field Technology including capture, processing, coding, and presentation/visualization. His work spans theoretical foundations to practical implementations across various application domains. His recent publication record demonstrates a clear trajectory toward advanced light field and 3D imaging technologies, with significant contributions to compression algorithms, depth estimation techniques, quality assessment metrics, and telepresence applications. His research bridges theoretical signal processing with practical industrial implementations, particularly in remote operation, mining applications, and immersive visualization systems. Best Paper Award at MMEDIA 2013 Quality Reviewer Award at ICME 2013 Professor Sjöström has supervised an extensive number of doctoral and licentiate students, with numerous current PhD candidates expected to complete their degrees in 2025. His teaching portfolio covers a wide range of subjects including Applied Signal Processing, Automatic Control, Computer Hardware and Architecture, and specialized PhD courses in Video Processing and Realistic 3D. He has led numerous research projects both current and completed, including IMMERSE, PLENOPTIMA, and various initiatives in 3D video technology and visualization. As founder and head of the Realistic 3D research group, he directs activities focused on synthesis and capture of 3D images and video, rendering techniques for virtual perspective views, system modeling for 3D capture and presentation, coding of 3D content, quality metrics and assessments, and remote control and measurement systems. The group maintains strong industrial collaborations across multiple sectors.

• Veterinary Diagnostic Imaging
• Translational Oncology
• Image-Guided Therapy
• +۳ مورد دیگر

Irene Schaafsma is a Physician Scientist at the Department of Clinical Sciences within the Faculty of Veterinary Medicine at Utrecht University . She specializes in Veterinary Diagnostic Imaging and contributes to translational research in oncology and neurosurgery. Research Focus Her work centers on image-guided treatment of brain malignancies using radioactive holmium microspheres , aiming to bridge veterinary and human medicine. This research involves collaborations with institutions like Radboud UMC, TU Delft, and UMC Utrecht, supported by high-tech companies. Scientific Recognition EBVS® European Specialist in Veterinary Diagnostic Imaging Project Involvement She participated in a project (2018-2023) funded by NWO-TTW (Project No. 15499), focusing on developing controlled administration systems for tumor-targeted radiation therapy. The project included two PhD tracks and interdisciplinary partnerships.

• Radiation Therapy
• Medical Physics
• Intraoperative Electron Radiation Therapy
• +۴ مورد دیگر

Christoph Gaisberger is a Medical Physicist at the University Clinic for Radiotherapy and Radio-Oncology and the University Institute for Technology Development in Radiation Therapy at Paracelsus Medical University in Salzburg, Austria. With over 30 publications spanning from 2008 to 2025, Dr. Gaisberger has established himself as a significant contributor to the field of radiation therapy physics, particularly in intraoperative techniques and dose calculation methodologies. Dr. Gaisberger's research primarily focuses on Intraoperative Electron Radiation Therapy , Dose Calculation , and Image Guided Radiation Therapy . His work spans multiple cancer types including Rectal Cancer , Prostate Cancer , and breast cancer applications. A key aspect of his research involves developing and implementing advanced technical approaches for real-time dose calculation and image guidance during radiation procedures. Analysis of Dr. Gaisberger's publication history reveals a strong trend toward integrating artificial intelligence and advanced computational methods into radiation therapy. His recent work (2023-2025) demonstrates increasing focus on deep learning applications for medical image segmentation, particularly using U-Net variants with Transformer and LSTM approaches for Cone-Beam CT segmentation. There's also a clear emphasis on clinical outcomes research, with multiple studies examining toxicity profiles, cosmetic outcomes, and quality of life metrics following various radiation therapy approaches. 1st ÖGRO Prize 2015 2nd Prize ÖGRO 2014 Dr. Gaisberger has been actively involved in research collaborations across multiple institutions, often working with clinical teams to translate technical advances into patient care improvements. His 2023 organization of the ÖGMP Annual Conference demonstrates his leadership role in the medical physics community. While specific grant information isn't detailed in the available text, his consistent publication record suggests successful research funding support. Based on his institutional affiliations, Dr. Gaisberger likely works within the radiation oncology physics team at the Salzburg General Hospital (Landesklinikum Salzburg), which partners with Paracelsus Medical University. His research suggests involvement with teams developing intraoperative radiation therapy protocols and image guidance systems for precision radiation delivery.

• Robotics
• Computer Vision
• Industrial Automation
• +۲ مورد دیگر

Velibor Đalić serves as an Associate Professor in the Department of Automation at the Faculty of Electrical Engineering, University of Banja Luka. His academic career spans over 15 years with continuous research output in robotics and control systems. His research focuses on industrial robotics , computer vision applications , and advanced control systems . Key contributions include markerless calibration techniques for surgical robots, optimization of PI controllers for hydraulic systems, and computer vision solutions for industrial automation. His work bridges theoretical control algorithms with practical industrial implementations. Analysis of his 15 most recent publications reveals a strong emphasis on precision robotics (68% of works), particularly in calibration and vision systems, followed by industrial process control (25%) and educational robotics (7%). The research demonstrates consistent progression from fundamental control theory toward real-world surgical and manufacturing applications. Current research funding includes two active national projects: Razvoj STEM vjestina i interesovanja kod skolske djece (2025, BAM 3,000) and Metodi za analizu signala zasnovani na masinskom ucenju (2024-2025, BAM 4,000), where he serves as a key participant alongside senior researchers from the Faculty of Electrical Engineering.

Aniruddha Kembhaviمشاهده پروفایل

دانشیار

• Computer Vision
• Robotics
• Natural Language Processing
• +۵ مورد دیگر

Aniruddha Kembhavi is an Affiliate Associate Professor at the University of Washington's Computer Science & Engineering department and currently serves as Director of Science Strategy at Wayve AI in London, UK. Previously, he led computer vision efforts as Senior Director at Allen Institute for AI (AI2) in Seattle and contributed to Microsoft's Image and Video Search division. His research spans 20+ years in Computer Vision , Robotics , and Embodied AI , focusing on open-source frameworks like AI2-THOR and Molmo. His work emphasizes procedural environment generation , vision-language integration , and 3D asset creation , with large-scale datasets such as Objaverse becoming foundational in 3D computer vision. CVPR 2025 Best Paper (Honorable Mention) CVPR 2023 Best Paper Winner Neurips 2022 Outstanding Paper CoRL 2024 Outstanding Paper IROS 2024 Best Mobile Manipulation Paper ICRA 2024 Best Paper Winner Allen Institute Test Of Time Award 2020 NVIDIA Pioneer Award 2018 His recent publications analyze vision-language models , 3D generation evaluation , and diffusion architectures for unified generation. He actively contributes to community-building as Program Chair for ICCV 2025 and Senior Area Chair for CVPR 2024.

Wolfgang Wallمشاهده پروفایل

استاد

• Computational Mechanics
• Biomedical Engineering
• Energy Storage Systems
• +۷ مورد دیگر

Wolfgang Wall is a full Professor and founding Director of the Institute for Computational Mechanics at the Technical University of Munich (TUM). Born near Salzburg (Austria), he studied at the University of Innsbruck and received his PhD from the University of Stuttgart. He is a co-founder of AdCo Engineering GW GmbH and Ebenbuild GmbH, and currently serves as Rector of the International Centre for Mechanical Sciences (CISM) in Udine, Italy. A member of both the Austrian and Bavarian Academies of Sciences, he has received numerous prestigious awards including the O.C. Zienkiewicz Award and ERC Advanced Grant. 1983: Matura, Höhere Technische Bundeslehranstalt Salzburg (with distinction) 1991: Dipl.-Ing. degree from University of Innsbruck (with distinction) 1999: Dr.-Ing. (summa cum laude) from University of Stuttgart His research focuses on application-motivated fundamental research in computational mechanics, spanning coupled multifield/multiscale problems (fluid-structure interaction, contact dynamics, electro-chemo-mechano-thermo interaction) and applications in energy storage systems (all-solid-state batteries), additive manufacturing, and computational biophysics/biomedical engineering (patient-specific respiratory/cardiac modeling, cancer nanomedicine, musculoskeletal systems). His group develops advanced computational methods, software frameworks, and physics-based models for high-performance computing. Recent emphasis includes uncertainty quantification, inverse analysis, and machine learning integration. The 15 most recent publications reveal trends in computational mechanics (8/15 articles), biomedical engineering (5/15), and energy storage/additive manufacturing (7/15). Notable themes include novel finite element frameworks for multiphysics problems, Bayesian calibration methods for biological systems, and multiscale modeling of nanomedicine and battery materials. 1986-1988: Excellency in Studying Awards (~ top 1%) 1991: Best graduation ever in Civil Engineering at Innsbruck University 1994: European Academic Software Award 2000: Fritz-Peter-Müller Award, University of Karlsruhe 2000: Rotary Award for doctoral thesis, Stuttgart 2005: Golden Teaching Awards (TUM students) 2008: Fellow Award of the International Association of Computational Mechanics 2011: Chuo University Guest Professorship Award 2012: IACM Computational Mechanics Award 2013: Heinz Maier-Leibnitz Medal 2016: Prandtl Medal (ECCOMAS) 2018: EUROMECH Fellows Award 2021: ERC Advanced Grant 2022: JSCES Grand Prize 2024: O.C. Zienkiewicz Award (IACM) As a dedicated educator, he teaches courses ranging from foundational engineering mechanics (1000+ students) to specialized graduate topics like discontinuous Galerkin methods and biomedical applications. His leadership extends to founding the Munich School of Engineering (2010-2012), establishing the Center for Computational Biomedical Engineering (2012), and serving on multiple editorial boards (IJNME, CMAME, IJNMBE) and scientific councils.

• Nanomedicine
• Theranostics
• Drug Delivery Systems
• +۵ مورد دیگر

Twan Lammers is a full Professor of Medicine at the Institute for Experimental Molecular Imaging (ExMI) within RWTH Aachen University Clinic. He leads the Nanomedicine and Theranostics research group focused on developing image-guided drug delivery systems for cancer and fibrotic diseases. Research Focus: His work centers on nanomedicine tumor targeting , combining drug delivery with molecular imaging to monitor tumor growth, angiogenesis, inflammation, and metastasis. Key areas include engineering polymeric microbubbles for ultrasound-mediated drug delivery, optimizing nanoparticle biodistribution using EPR and ATR mechanisms, and developing clinical translation frameworks for nanotherapeutics. His group pioneered transferrin receptor-targeted microbubbles for blood-brain barrier sonopermeation and desmoplastic tumor priming strategies using corticosteroid liposomes. Awards & Recognition: ERC Starting and Consolidator Grants Controlled Release Society Young Investigator Award (2015) Clarivate Highly Cited Researcher (since 2019) Over 250 publications with significant clinical impact Leadership: Serves as handling editor for Journal of Controlled Release and Molecular Imaging and Biology , and chairs special issues on stimuli-responsive nanotheranostics. His research bridges preclinical innovation with clinical applications through collaborations with pharmaceutical partners and clinical trial networks.

Jennie Taylorمشاهده پروفایل

دانشیار

• Neuro-Oncology
• Brain Tumors
• Molecular Markers
• +۵ مورد دیگر

Jennie Taylor, MD, MPH is an Associate Professor in Neurology at the University of California, San Francisco (UCSF) School of Medicine , affiliated with the UCSF Brain Tumor Research Center . She specializes in adult neuro-oncology with a focus on primary brain tumors. Education: University of Kentucky College of Medicine (MD), Harvard T.H. Chan School of Public Health (MPH) Training: Internship/Residency at University of Virginia Medical Center, Neuro-Oncology fellowship at Massachusetts General Hospital/Dana-Farber Cancer Institute Research interests include molecular and imaging markers of treatment resistance in brain tumors, quality of life optimization for patients and caregivers, and genomic profiling of gliomas. Her recent publications emphasize IDH-mutant glioma evolution , immunosuppressive tumor microenvironment , and precision medicine in neuro-oncology . She co-directs the Neuro-Oncology Gordon Murray Caregiver Program and contributes to clinical trial design and multidisciplinary neuro-oncology care . Her work spans molecular neuro-oncology , radiogenomics , and supportive care innovations .

• Machine Learning
• Computer Vision
• Bioinformatics
• +۴ مورد دیگر

Adriana Birlutiu is a Lecturer in the Computer Science Department at 1 December 1918 University of Alba Iulia , Romania. Her expertise lies in machine learning, computer vision, bioinformatics, and transfer learning, with a recent focus on porcelain-industry optimisation. Education Ph.D., Radboud University Nijmegen, Netherlands (2011) M.Sc., Babeș-Bolyai University of Cluj-Napoca & University of Lorraine (Erasmus), 2005 B.Sc., Babeș-Bolyai University of Cluj-Napoca, 2004 Research Interests Adriana's research spans machine learning , deep learning , computer vision , and bioinformatics . She has contributed to preference learning, domain adaptation, protein–protein interaction prediction, and automated quality control in porcelain manufacturing. Her recent projects integrate deep neural networks with industrial computer-vision systems to detect defects and recognise characters on ceramic surfaces. Publication Trends Across 15 recent publications (2010-2019), Adriana has consistently explored transfer learning , multi-task learning , and Bayesian methods . Articles cluster around two major axes: biomedical applications (protein networks, cancer relapse prediction, respiratory-motion modelling for radiotherapy) and industrial AI (porcelain defect detection, character recognition). The work shows a clear evolution from theoretical machine-learning foundations to practical, domain-specific implementations. Grants & Projects SIVAP (2016-2018): Intelligent ML & computer-vision system for porcelain manufacturing optimisation, UEFISCDI PN-III-P2-2.1-BG-2016-0333. CMRCC (2017-2018): Computational Models for Reproducing Ceramics Colors, UEFISCDI PN-III-P2-2.1-PED-2016-1835. Student Supervision & Mentoring Adriana has supervised more than 25 undergraduate and master’s theses. Her students have won multiple awards at national conferences such as In-Extenso and SCCSS-IEECC , covering topics from automated defect detection to web applications for academic scheduling. Teaching Responsibilities She teaches courses including Machine Learning , Mathematical Software , Fundamental Algorithms , Object-Oriented Databases , and Modelling and Simulation at both undergraduate and master levels.

Aurela Clarkمشاهده پروفایل

دانشیار

• Breast Radiology
• Diagnostic Radiology
• Nuclear Radiology
• +۳ مورد دیگر

Aurela Clark, MD is an Associate Professor of Radiology at the University of Kentucky College of Medicine , where she also serves as Program Director for the Breast Radiology Fellowship. Her work spans multiple divisions including Breast Radiology, Medical Physics, and Nuclear Medicine. Education : MD from University of Kentucky College of Medicine (2013), General Surgery Internship (2013-2014), Diagnostic Radiology Residency with Nuclear Radiology pathway (2014-2018), and Breast Imaging Fellowship from Medical University of South Carolina (2018-2019). Dr. Clark's research focuses on breast imaging, cancer detection, and medical imaging safety . She has published extensively on topics including: Rare breast pathologies (e.g., pilomatrixoma, calcifying fibrous tumors) Diagnostic imaging pitfalls (e.g., Cushing’s syndrome on PET/CT) Quality improvement in breast biopsies Imaging safety during pregnancy and lactation Standardized uptake value (SUV) calibration in nuclear imaging Case studies on complex breast presentations Her work bridges clinical practice, medical physics research, and educational initiatives in radiology training programs.

• Radiation Oncology
• Clinical Epidemiology
• Prostate Cancer Research
• +۵ مورد دیگر

Wilma Heemsbergen is a clinical epidemiologist with over 20 years of experience in radiation oncology, currently affiliated with the Department of Radiation Oncology at Erasmus MC, Rotterdam (2017–present). Previously, she worked at Antoni van Leeuwenhoek Hospital – The Netherlands Cancer Institute, Amsterdam (1998–2016), including a clinical epidemiologist role at their Department of Biostatistics and Epidemiology (2009–2016). PhD (2008) – University of Amsterdam, Thesis: Radiation treatment in prostate cancer: balancing between tumor control and toxicity MSc (1994) – Radboud University Nijmegen, Thesis: A comparison of low molecular weight heparin with unfractionated heparin in prophylaxis of reocclusion after PTA Research Interests focus on radiation-induced secondary cancers, dose-effect relationships, hypo-fractionation in prostate cancer, toxicity scoring systems, and outcome research for head & neck/oropharyngeal cancers. Her work spans: Radiation Toxicity Modeling Prostate Cancer Survivorship Head & Neck Radiotherapy Optimization Dose Escalation and Hypofractionation Patient Setup Verification Cancer Outcome Research Scientific Contributions include co-authoring >60 peer-reviewed publications (h-index 30) and leading projects like: PRORAD : Prospective cohort study on prostate cancer radiotherapy quality of life SPARC : Second primary tumors after prostate radiotherapy (2019 KWF grant) OROPH : Toxicity and outcomes after oropharyngeal radiotherapy Teaching Activities include roles at international ESTRO courses (IMRT/Statistics) and the Oncology Graduate School Amsterdam (2010–2016). She authored chapters on data quality in radiotherapy side effect modeling.