جست‌وجوی استاد و پژوهشگر

Peter J. Basserمشاهده پروفایل

استاد پژوهشی

• Quantitative Imaging
• Tissue Sciences
• Diffusion MRI
• +۷ مورد دیگر

Peter J. Basser is a leading research scientist at the National Institutes of Health (NIH), specifically within the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), where he heads the Section on Quantitative Imaging and Tissue Sciences (SQITS). His work bridges physics, engineering, and neuroscience to develop non-invasive MRI methods for probing tissue microstructure, particularly in the brain. His educational background is not explicitly mentioned, but his scientific achievements reflect deep training in biophysics and medical imaging. He earned his Ph.D. and has built a career at NIH as a principal inventor of key neuroimaging technologies. Basser's research focuses on quantitative imaging and tissue sciences , especially using diffusion MRI to study brain structure and function. He pioneered Diffusion Tensor MRI (DTI) , Streamline Tractography , and advanced methods like MAP MRI , CHARMED , and AxCaliber , enabling in vivo measurement of axon diameters and microstructural features previously accessible only through histology. His work aims to translate these tools into clinical use for diagnosing developmental disorders, trauma, and neurodegeneration. The 15 most recent articles reflect a consistent focus on developing novel MRI biomarkers, particularly through diffusion and relaxometry methods. They explore water exchange, restriction, glymphatic clearance, latency connectomes, and cortical microstructure, demonstrating a trajectory toward in vivo MRI histology and precision imaging for pediatric and neurological applications. Scientific Awards: National Academy of Engineering (NAE), Inducted 2020 National Academy of Inventors (NAI) Fellow, 2024 Eduard Rhein Technology Award, 2021 ISMRM Gold Medal, 2008 ISMRM Lauterbur Lecturer, 2020 American Society of Neuroradiology Honorary Member, 2019 Victor M. Haughton Award, 2017 ISMRM Fellow, 2010 AIMBE Fellow Best Paper Award, Frontiers in Physics, 2023 Basser leads a dynamic research group that mentors postdoctoral fellows and trainees, many of whom have received prestigious awards. His lab has secured significant grants from the NIH BRAIN Initiative, NICHD, USUHS, and the Bill & Melinda Gates Foundation. The SQITS lab develops open-source software tools like TORTOISE , dmritool , and HI-SPEED , which are widely used in the neuroimaging community. The lab collaborates with institutions such as Uniformed Services University and participates in major initiatives like the Human Placenta Project and the Human Connectome Project. Basser’s vision is to transform clinical MRI scanners into quantitative scientific instruments for precision medicine and large-scale brain mapping. Labs and Teams: Section on Quantitative Imaging and Tissue Sciences (SQITS), NICHD, NIH Neuropathology-Neuroradiology Integration Core (with USUHS) Advanced Translational Neuroimaging Research & Development Core Diffusion – Data Processing Center (DPC)

• Extragalactic Astrophysics
• Cosmology
• Weak Gravitational Lensing
• +۷ مورد دیگر

Tim Schrabback is a Full Professor at the Institute for Astro- and Particle Physics , Faculty of Mathematics, Computer Science and Physics, University of Innsbruck . He leads research in extragalactic astrophysics, focusing on weak gravitational lensing, galaxy clusters, and cosmology through major international collaborations such as the Euclid Mission , eROSITA , DES , SPT , and HSC . His research interests include: Observational cosmology using galaxy clusters Weak and strong gravitational lensing Dark energy and large-scale structure X-ray and Sunyaev-Zel'dovich cluster surveys Machine learning applications in astrophysics Calibration of space-based instruments His recent publications (2023–2025) span high-impact journals including Astronomy & Astrophysics , Physical Review D , and Monthly Notices of the Royal Astronomical Society . The work emphasizes cosmological parameter estimation , cluster mass calibration , systematic error mitigation in weak lensing , and multi-messenger cosmology . A strong trend is the integration of data from optical, infrared, X-ray, and microwave surveys to constrain models of dark energy and modified gravity. Scientific contributions include: Leading roles in Euclid’s weak lensing and cluster science working groups Co-authorship on foundational Euclid mission papers Key contributions to eROSITA all-sky survey analysis Development of shear calibration techniques using deep learning Mass calibration of galaxy clusters via weak lensing He actively participates in advising and collaborative research, working closely with postdocs and early-career scientists such as Sebastian Grandis , Florian Kleinebreil , Henrik Jansen , and Lukas Linke . He has secured access to major datasets and leads analysis efforts in joint cluster cosmology programs. His public engagement includes frequent outreach lectures on astrophysics and telescope observation, particularly through the annual Astronacht events at the University of Innsbruck. He has also contributed to media interviews on cosmological tensions and galaxy cluster physics. He leads or participates in several research labs and teams: Euclid Weak Lensing Science Working Group eROSITA Cluster & Cosmology Working Group Institute for Astro- and Particle Physics Observing Team Alpine Cosmology Collaboration

• Active Matter
• Soft Matter Physics
• Ferrofluids
• +۱۲ مورد دیگر

Jaakko Timonen is an Associate Professor and Vice Head of the Department of Applied Physics at Aalto University, where he leads the Active Matter research group. He is also Deputy Director of the Center of Excellence in Life-Inspired Hybrid Materials (LIBER), and holds significant research funding from the Academy of Finland and the European Research Council (ERC StG). His academic journey includes a doctoral degree from Aalto (2013) and postdoctoral research at Northwestern and Harvard Universities. His research interests lie at the intersection of physics, chemistry, and biology, focusing on soft and active matter systems. Key areas include ferrofluids, electrohydrodynamics, liquid-liquid phase separation, colloidal nanoparticles, magnetic control of non-magnetic matter, and advanced optical microscopy. His recent publications span high-impact journals and reveal a strong trend toward bioinspired materials, responsive systems, and biomedical applications such as 3D bioprinting and cancer diagnostics. His work often involves interdisciplinary collaboration and the development of novel experimental techniques. ERC Starting Grant (2019–2024) Academy of Finland Research Fellow (2019–2023) Distinction prize for doctoral thesis (Aalto, 2013) Distinction prize for master’s thesis (Helsinki UT, 2009) Timonen actively supervises PhD and early-career researchers, with several students contributing to recent publications and projects. He leads multiple active grants, including projects on multiscale electrostatic phenomena in nanoparticles and food applications of Pickering emulsions. He also organizes academic events and participates in public outreach, such as the 'Life inspired materials' seminar. His research group maintains strong ties to both fundamental physics and real-world applications in health, sustainability, and advanced materials. He is involved in several research labs and collaborative networks, particularly through the LIBER Center of Excellence, focusing on hybrid materials with life-inspired functions. His team develops custom imaging systems and explores emergent behaviors in active and biological matter, contributing to fields such as non-equilibrium physics, microfluidics, and synthetic biology.

Martin Bendszusمشاهده پروفایل

استاد

• Magnetic Resonance Imaging
• Neuroradiology
• Neuroimaging
• +۷ مورد دیگر

Professor Martin Bendszus serves as the Medical Director of the Department of Neuroradiology at Heidelberg University Hospital. He has held this position since 2007 and is a leading figure in advanced neuroimaging techniques. His academic career includes medical studies in Bonn, specialized training in Neuroradiology at the University of Würzburg (2003-2007), and a professorship in Neuroimaging at the University of Würzburg. Professor Bendszus's research focuses on innovative imaging methods, particularly in Magnetic Resonance Imaging (MRI). He pioneered Magnet Resonance Neurography for diagnosing peripheral nervous system disorders and made significant contributions to Dental-MRI as a radiation-free diagnostic tool for dental conditions. His expertise also extends to brain and spinal cord diagnostics, including aneurysms, strokes, and arteriovenous malformations. His work bridges clinical practice with advanced imaging research, resulting in numerous high-impact publications across neurology, radiology, and oncology. His publication record shows consistent high-impact contributions, with recent work spanning stroke intervention, neuropathic pain, brain tumor imaging, and advanced MRI techniques. The research trends demonstrate his leadership in translating imaging advances into clinical practice, particularly in time-sensitive neurological conditions where imaging guides critical treatment decisions. Kurt-Decker-Preis Röntgen-Preis Coolidge-Award Lucien-Appel-Award Hermann-Holthusen-Ring der Deutschen Röntgengesellschaft Professor Bendszus leads major multicenter clinical trials and collaborative guideline development efforts, including work with the Response Assessment in Neuro-Oncology (RANO) group and European Association for Neuro-Oncology (EANO). His research has secured significant funding for advancing neuroimaging techniques and their clinical applications. He collaborates extensively with neurologists, neurosurgeons, oncologists, and radiologists to improve diagnostic and therapeutic approaches for neurological conditions. His department serves as a reference center for complex neuroradiological cases and trains the next generation of neuroradiologists. Professor Bendszus maintains active leadership roles in professional societies and regularly contributes to shaping clinical guidelines in neuroimaging and stroke care.

• Alzheimer's Disease
• Huntington's Disease
• Parkinson's Disease
• +۵ مورد دیگر

Frank Longo is a Professor in the Department of Neurology and Neurological Sciences at Stanford University School of Medicine. He actively teaches across the neuroscience curriculum including Medical Scholars Research (NENS 370), Directed Reading courses (NEPR 299/NENS 299), Graduate Research (NENS 399/NEPR 399), and Early Clinical Experience (NENS 280), demonstrating his commitment to training the next generation of neuroscientists and clinicians. His research program centers on neurodegenerative diseases with particular emphasis on Alzheimer's, Huntington's, and Parkinson's diseases. Longo investigates the therapeutic potential of neurotrophin receptor modulation (especially p75NTR and TrkB) using small-molecule ligands like LM11A-31, exploring mechanisms spanning protein aggregation, synaptic dysfunction, neuroinflammation, and metabolic dysregulation. His work bridges molecular neuroscience with translational applications, utilizing advanced techniques including transcriptomics, neuroimaging, and biomarker analysis in cellular and animal models. Analysis of his 2024-2025 publications reveals consistent focus on targeting neurotrophin pathways to reverse disease phenotypes. Key themes include: 1) Development of small-molecule modulators for p75NTR/TrkB to rescue synaptic and cognitive deficits; 2) Biomarker discovery for early detection (e.g., plasma Aβ42/Aβ40 ratios); 3) Mechanistic studies on autophagy, white matter changes, and metabolic dysfunction; and 4) Leadership in collaborative initiatives like the TREAT-AD Center for target validation. His research demonstrates both breadth across neurodegenerative disorders and depth in neurotrophin signaling mechanisms. Through undergraduate and graduate research courses, Longo mentors students in neuroscience research despite no specific advisees being listed. His extensive publication record and involvement in multi-institutional consortia (including EU-US task forces) indicate significant research funding and national leadership in neurodegenerative disease research, though specific grant details aren't provided in the source material.

Reza Zadehمشاهده پروفایل

استاد مدعو

• Machine Learning
• Distributed Computing
• Discrete Mathematics
• +۷ مورد دیگر

Reza Zadeh is a Computational Mathematics professor at Stanford University's School of Engineering and Founder & CEO of Matroid . He previously served as a Technical Advisory Board member for Databricks and leads the Spark Tutorial at Stanford. Research Interests: Specializing in Machine Learning and Distributed Computing , his work bridges theoretical mathematics with practical implementations in big data systems. Key focus areas include Optimization of Apache Spark 3D Convolutional Neural Networks Discrete Mathematics and Graph Theory Medical Imaging Applications Academic Contributions: His publications reveal trends across multiple disciplines: Adapting machine learning for medical diagnostics (2019-2022) Advancing distributed computing frameworks (2014-2016) Developing mathematical foundations for social networks (2009-2013) Creating scalable optimization algorithms (2014-2016) Scientific Awards: Best Paper Award runner-up at KDD 2016 Academic Leadership: He has taught SMACC Consulting and designed courses including CME 323: Distributed Algorithms and Optimization (2015-2024) and CME 305: Discrete Mathematics and Algorithms (2010-2017). His lectures cover graph theory, approximation algorithms, and spectral sparsification. Labs & Teams: Organized Spark Summit workshops and leads Scaled Machine Learning Conference . Collaborates with Stanford's ICME computational consulting services.

Luca Guarneraمشاهده پروفایل

استادیار

• Computer Vision
• Machine Learning
• Multimedia Forensics
• +۶ مورد دیگر

Luca Guarnera is a Fixed-term Assistant Professor (RTDA) of Informatics at the Department of Mathematics and Computer Science, University of Catania. Born in Catania on October 26, 1992, he has been a research fellow in Computer Science at the University of Catania since January 1, 2022. His academic journey includes a PhD in Computer Science (XXXIII cycle, PON number E37H18000330006) from the University of Catania, with part of his research conducted at the University of Hertfordshire under Prof. Salvatore Livatino. PhD in Computer Science, University of Catania (2018-2021) Master's Degree in Computer Science (cum laude), University of Catania (2015-2017) Bachelor's Degree in Computer Science, University of Catania (2011-2015) Guarnera's research focuses on Computer Vision, Machine Learning, and Multimedia Forensics, with special emphasis on Deepfake Detection across images, video, audio, and multimodal data. His work explores intrinsic traces left during content creation processes, VR applications for forensic analysis, and deep learning approaches to forensic problems. He has contributed significantly to forensic firearms ballistics analysis through immersive VR observation and handwritten document analysis. His publication record shows a strong trajectory in deepfake detection technologies, evolving from early work on convolutional traces to current research distinguishing between GAN and Diffusion Model outputs. His research spans both theoretical foundations and practical applications in digital forensics, with increasing focus on multimodal approaches and real-world implementation challenges. Guest Editor for Special Issue 'Advancements in Deepfake Technology, Biometry System and Multimedia Forensic' in MDPI Journal of Imaging Guarnera actively participates in the academic community as a reviewer for international journals and has contributed to prestigious international events as a Technical Program Committee member. His research is supported through collaborations with industry partners like iCTLAB srl and academic institutions. He is involved in the HEALTHY-UNICT project studying dietary habits of college students through ecological momentary assessment approaches. As a member of IPLab (Image Processing Lab) since 2015, Guarnera has been involved in various research initiatives including participation in Mohamed Bin Zayed International Robotics Challenge (MBZIRC) competitions and international summer schools (ICVSS, MISS, S3P). His work bridges theoretical computer science with practical forensic applications, particularly in the rapidly evolving field of deepfake detection and multimedia authentication.

Jitendra Malikمشاهده پروفایل

استاد

• Computer Vision
• Robotics
• Machine Learning
• +۷ مورد دیگر

Jitendra Malik is the Arthur J. Chick Professor of Electrical Engineering and Computer Sciences (EECS) at the University of California, Berkeley, with affiliations in Bioengineering, Cognitive Science, and Vision Science groups. He previously served as Chair of the Computer Science Division (2002-2004) and Department Chair of EECS (2004-2006 and 2016-2017). He also worked part-time as Research Director and Site Lead at Facebook AI Research (Meta Inc.) during 2018-2019. Education : B.Tech in Electrical Engineering (IIT Kanpur, 1980), PhD in Computer Science (Stanford, 1985) Current Research : Computer Vision, Robotics, Machine Learning, Computational Modeling of Human Vision, and Biological Image Analysis Making significant contributions to computer vision , robotics , and machine learning , Malik’s work includes foundational algorithms like anisotropic diffusion , normalized cuts , and R-CNN . His recent research focuses on embodied AI agents , dexterous manipulation , 3D scene reconstruction , and vision-language-action models . His publications have received 11 best paper awards , including test-of-time awards like the Longuet-Higgins Prize (3x) and Helmholtz Prize (3x). Malik has mentored over 80 PhD students and postdoctoral fellows , many of whom hold prominent positions at institutions like MIT, Caltech, Google, and Meta. His lab’s work spans computer vision , robot learning , and 3D modeling , with applications in autonomous systems, medical imaging, and computational biology. Scientific Awards Presidential Young Investigator Award (1989) Distinguished Alumnus Award, IIT Kanpur (2008) IEEE PAMI-TC Distinguished Researcher (2013) K.S. Fu Prize, IAPR (2014) ACM-AAAI Allen Newell Award (2016) IJCAI Award for Research Excellence (2018) IEEE Computer Society Pioneer Award (2019) Fellow, IEEE, ACM, AAAS Member, National Academy of Engineering and National Academy of Sciences As a leader in sensorimotor learning and humanoid robotics , Malik has pioneered approaches for vision-based quadcopter control , humanoid locomotion , and visuo-tactile perception , further advancing the field of artificial intelligence and computational vision .

• Solidification
• X-ray Imaging
• Materials Science
• +۳ مورد دیگر

Ragnvald Mathiesen serves as Professor in the Department of Physics at the Norwegian University of Science and Technology (NTNU), Trondheim. His research leverages advanced synchrotron-based X-ray and neutron imaging techniques to investigate dynamic solidification processes in metallic alloys and geomaterials, with significant contributions to understanding microstructure evolution under varied conditions including microgravity. His primary research interests focus on solidification physics , in-situ X-ray radiography/tomography , and microstructure characterization of metallic systems. Key specialties include dendrite growth kinetics, phase transformation dynamics, grain refinement mechanisms in aluminum alloys, and the application of 4D imaging to capture transient phenomena in materials processing. His work bridges fundamental physics with industrial metallurgy applications, particularly in aluminum and magnesium alloy systems. Analysis of his 15 most recent publications (2019-2025) reveals a consistent emphasis on time-resolved imaging methodologies applied to solidification phenomena. His research demonstrates increasing sophistication in multi-modal imaging (X-ray/neutron), with growing applications in geomaterials and electro-active systems. The publications show strong international collaboration patterns, particularly with European synchrotron facilities like ESRF, and address both fundamental questions in solidification physics and practical challenges in materials processing. Professor Mathiesen actively contributes to the development of advanced X-ray microscopy techniques, as evidenced by his 2017 doctoral dissertation on high-energy X-ray transmission microscopy and recent publications on dark-field imaging and diamond lens optimization. His laboratory work utilizes NTNU's materials characterization infrastructure alongside major international facilities including the European Synchrotron Radiation Facility.

• Compassion Meditation
• Stress Relief
• Neuroimaging
• +۹ مورد دیگر

Julie Brefczynski-Lewis is a Research Assistant Professor at West Virginia University School of Medicine, holding positions in both the Department of Neuroscience and the Rockefeller Neuroscience Institute. She earned her PhD from the Medical College of Wisconsin and serves as the neuroimaging liaison for the Center for Advanced Imaging. West Virginia University School of Medicine Department of Neuroscience Rockefeller Neuroscience Institute Dr. Brefczynski-Lewis's primary research focuses on compassion meditation training for stress relief, particularly regarding difficult interpersonal relations. She has developed a smartphone application to facilitate daily meditation practice and examines the resulting neural, physiological, and behavioral changes. Her work spans multiple neuroimaging techniques including MRI, PET, EEG, and TMS, with applications in working memory, mindfulness, trust, neonatal cognition, pediatric sleep disorders, stroke studies, depression, and auditory processing in disordered populations. Her recent publications demonstrate a strong trajectory in advancing neuroimaging technology, particularly in developing ambulatory PET systems that allow brain imaging during natural movement. This work represents a significant departure from traditional stationary brain imaging approaches and opens new possibilities for studying brain function in real-world contexts. Neuroimaging liaison for the Center for Advanced Imaging Weekly neuroimaging group meetings at Mondays 4:00 PM Provides training in MRI, PET, EEG, and TMS techniques Assists with experimental design and IRB protocols Dr. Brefczynski-Lewis actively collaborates across disciplines, serving as a bridge between technical imaging development and clinical applications. Her work on compassion meditation represents an important integration of traditional contemplative practices with modern neuroscience methodology, while her contributions to ambulatory PET technology showcase her innovative approach to overcoming limitations in current neuroimaging paradigms.

Daniel Twardمشاهده پروفایل

استادیار

• Neuroimaging
• Computational Neuroscience
• Machine Learning
• +۴ مورد دیگر

Dr. Daniel Tward is an Assistant Professor at the University of California, Los Angeles (UCLA), holding joint appointments in the Department of Neurology and the Department of Computational Medicine. He earned his Ph.D. in Biomedical Engineering from Johns Hopkins University and completed postdoctoral training at the Kavli Neuroscience Discovery Institute. His research integrates neuroimaging, machine learning, and differential geometry to analyze brain structure changes in neurodegenerative diseases like Alzheimer's, with a focus on bridging molecular pathology and clinical imaging. Research Interests: Dr. Tward's work addresses challenges in neuroimaging data complexity, developing computational tools to map brain anatomy across scales (from centimeters to microns). Key areas include neurodegeneration in the medial temporal lobe, multi-modal image registration, and spatial transcriptomics. His lab emphasizes high-dimensional statistics and geometry-driven analysis to improve diagnostic accuracy and clinical trial design. Grants & Projects: Secured NIH funding for: A 3D multimodal human brain atlas integrating MRI and histology. CloudReg—a distributed framework for massive neuroimage registration. Contributions to the BRAIN Initiative Cell Census Network (BICCN) for mouse/rat brain atlases. Students & Training: Mentors undergraduate researchers via the BIG Summer program, with projects on neural networks, spatial transcriptomics, and MRI analysis. No PhD/Master's advisees listed.

Maria Castroمشاهده پروفایل

استاد

• Neuro-oncology
• Glioblastoma research
• Brain tumor treatment
• +۵ مورد دیگر

Maria Castro is a Professor in the Department of Neurosurgery at the University of Michigan Medical School, where she leads groundbreaking research in neuro-oncology with a specific focus on brain tumor treatment and glioblastoma research. Her work bridges laboratory science with clinical applications, developing innovative therapies for some of the most challenging brain cancers. Dr. Castro's research primarily centers on developing novel therapeutic approaches for glioblastoma and other malignant brain tumors. Her work spans multiple cutting-edge areas including nanoparticle therapy for brain tumors, oncolytic virotherapy, epigenetic reprogramming in gliomas, and artificial intelligence applications in neurosurgery. She has made significant contributions to understanding how cholesterol metabolism affects glioma progression and has developed HDL nanodisc technology to target brain tumors. Her research on oncolytic viruses has opened new avenues for cancer immunotherapy, while her work on FastGlioma represents a major breakthrough in intraoperative brain tumor detection technology. Analysis of Dr. Castro's recent publications reveals a strong focus on translating basic science discoveries into clinical applications. Her work spans multiple disciplines including neuro-oncology, cancer immunology, nanomedicine, epigenetics, and artificial intelligence. A common thread throughout her research is the development of targeted therapies that address specific molecular vulnerabilities in brain tumors, particularly focusing on IDH-mutant gliomas and pediatric high-grade gliomas. Her publications demonstrate increasing collaboration with interdisciplinary teams including engineers, computer scientists, and clinicians to develop comprehensive treatment approaches. Dr. Castro actively collaborates with numerous researchers, most notably with Dr. Pedro Lowenstein on oncolytic virus therapies and with Dr. Anna Schwendeman on nanodisc technology. Her work has attracted significant research funding for developing novel brain tumor treatments, particularly in the areas of targeted drug delivery systems and immunotherapies. She is involved in multiple translational research projects aiming to move laboratory discoveries into clinical trials for brain tumor patients. Her laboratory operates at the intersection of multiple research areas, with teams focused on nanomedicine development, viral vector engineering, AI applications in neurosurgery, and molecular characterization of brain tumors. The lab utilizes sophisticated mouse models of glioma and works closely with clinicians to ensure research is clinically relevant. Recent work has expanded into studying the tumor microenvironment and how immune cells interact with brain tumor cells, opening new possibilities for combination therapies.

James C. Davisمشاهده پروفایل

استادیار

• Software Engineering
• Cybersecurity
• Human-Computer Interaction
• +۵ مورد دیگر

James C. Davis is an Assistant Professor at the Elmore Family School of Electrical and Computer Engineering (Purdue University). His research focuses on socio-technical approaches to software engineering , emphasizing security , correctness , and usability in software-intensive systems. He leads the Duality Lab , which publishes in top venues like ICSE , USENIX Security , and EMSE , with funding from the NSF , Google , Cisco , and Rolls Royce . PhD in Computer Science from Virginia Tech Current research themes: software supply chain security, pre-trained model engineering, and empirical studies of developer practices His recent publications (2025) analyze LLM jailbreaking , software signing (Sigstore), IoT model optimization , and deep learning reproducibility . Supported by grants from NSF OAC Core (multi-modal deep learning infrastructure) and RFE (prompt engineering education). Recognized with the ASEE Best Paper Award (2024) for trust engineering research. Current students include Paschal Amusuo (PhD candidate), Wenxin Jiang (now at Socket), and Dharun Venkatraman (Chateaubriand Fellow). Advising highlights : Guided 7 PhD/MSc theses (2022-2025) Developed CodeQL experience report (709 defects in 258 projects) Industry collaborations: Google , Microsoft Research , Qualcomm Research trends from 2022-2025 show sustained focus on: Software security (supply chains, signing, ReDoS) Model engineering (IoT optimization, naming conventions) Empirical methods (interview studies, defect analysis) Human factors (developer practices, training effectiveness)

• Biomedical Engineering
• Placental Biology
• Vascular Physiology
• +۴ مورد دیگر

Nikhilesh Bappoo is an Adjunct Research Fellow at the UWA Medical School, affiliated with the UWA Centre for Medical Research and the Harry Perkins Institute of Medical Research. He holds a Doctor of Philosophy (PhD) student status alongside a Master of Professional Engineering (2018) and a Bachelor of Philosophy (Hons) (2017), both from the University of Western Australia. His research focuses on placental vascular structure and hemodynamics, fetal growth restriction, and computational modeling of vascular diseases such as abdominal aortic aneurysms. Key areas include understanding how hemodynamic factors like shear stress influence placental function and aneurysm progression. He employs multidisciplinary approaches blending biomechanics, medical imaging, and computational simulations. Notable awards include the Materialise Mimics Innovation Award (2017), ASME Best Student Paper (2018), and a Convocation Postgraduate Research Travel Award (2019). His work contributes to UN Sustainable Development Goals related to good health and well-being. Research outputs span vascular network modeling, aneurysm biomechanics, and placental oxygen diffusion. Collaborations involve institutions globally, with recent studies exploring rare vascular conditions like pancreaticoduodenal artery aneurysms.

Amanda Marcielمشاهده پروفایل

استادیار

• Polymer Physics
• Soft Matter
• Material Science
• +۵ مورد دیگر

Amanda Marciel is the William Marsh Rice Trustee Assistant Professor of Chemical and Biomolecular Engineering at Rice University, with joint appointments in Chemistry and Applied Physics. She joined Rice in 2019, following postdoctoral work at The University of Chicago (2015-2018) and a Ph.D. in Biophysics from the University of Illinois at Urbana-Champaign (2015), and a B.S. in Chemistry from UC Berkeley (2008). Her research focuses on designing stimuli-responsive materials through understanding charged polymer behavior in solutions and at interfaces. Key areas include pH-responsive polyelectrolyte brushes, polyampholyte phase behavior mimicking intrinsically disordered proteins, and charged polymers at fluid-fluid interfaces for applications in energy, biomedicine, and environmental engineering. Techniques used include precision polymer synthesis, light scattering, interfacial rheology, and advanced imaging. Marciel has published >30 articles on soft matter physics and supervised 5 graduate students. Notable awards include the NSF CAREER Award and ACS PRF Doctoral New Investigator grant. Her work bridges polymer chemistry, materials science, and biophysics, with a focus on interdisciplinary innovation.