جست‌وجوی استاد و پژوهشگر

Hang Luمشاهده پروفایل

استاد

• Microfluidics
• Systems Biology
• Neuroscience
• +۶ مورد دیگر

Hang Lu is a Professor and holds the Cecil J. "Pete" Silas Chair of Chemical & Biomolecular Engineering at the Georgia Institute of Technology. Dr. Lu also holds a Love Family Professorship and leads the Lµ Fluidics Group, which focuses on engineering microfluidic systems and machine learning tools to address complex questions in neuroscience, developmental biology, and cell biology that are difficult to address with conventional techniques. Dr. Lu's research lies at the intersection of engineering and biology, with primary interests including: Microfluidic systems for high-throughput screens and image-based genetics and genomics Systems biology: large-scale experimentation and data mining Microtechnologies for optical stimulation and optical recording Big data, machine vision, and automation Developmental neurobiology, behavioral neurobiology, and systems neuroscience Cancer biology, immunology, embryonic development, and stem cells Her laboratory engineers microfluidic devices and BioMEMS to study neuroscience, genetics, cancer biology, and biotechnology. These miniaturized Lab-on-a-chip tools operate at scales comparable to biological systems, leveraging unique micro and nano-scale phenomena to gather large-scale quantitative data about complex biological systems. Current projects include Microfluidics for Life Sciences, Optical Neuron Recordings and Manipulations, Machine Learning Tools for Neuroscience, Measuring and Modeling Behavior, and High-throughput, High-content Cell-based Assays. Analysis of Dr. Lu's recent publications (2024-2025) reveals a strong trend toward integrating microfluidics with advanced computational methods: Development of deep learning frameworks for biological image analysis Advanced neuron tracking and functional imaging techniques Non-invasive characterization of 3D organoid cultures Sophisticated neuromechanical modeling of locomotion Microfluidic temperature control systems for in vivo studies Label-free imaging pipelines for neural development Dr. Lu's significant professional honors include: Cecil J. "Pete" Silas Chair of Chemical & Biomolecular Engineering Love Family Professorship The Lµ Fluidics Group actively mentors students and postdocs, currently accepting new postdoctoral researchers. The lab receives substantial funding for interdisciplinary projects at the engineering-biology interface, with research implications spanning fundamental biological understanding to therapeutic development. The group operates within Georgia Tech's School of Chemical & Biomolecular Engineering, with specialized facilities for microfluidic device fabrication, biological experimentation, and advanced imaging, maintaining strong collaborative ties across engineering, neuroscience, and biological disciplines.

Matthew O'Tooleمشاهده پروفایل

دانشیار

• Computer Graphics
• Robotics
• Computer Vision
• +۵ مورد دیگر

Matthew O'Toole is an Associate Professor at Carnegie Mellon University's School of Computer Science, holding joint appointments in the Robotics Institute and Computer Science Department. His research focuses on computational imaging, integrating optics, electronics, and computational processing to innovate visual information capture and display. Education: PhD (Computer Science, University of Toronto, 2016), MSc (2009), BSc (Honors Computer Science and Mathematics, University of British Columbia, 2007). Prior roles include Banting Postdoctoral Fellow at Stanford University and visiting scholar at MIT Media Lab's Camera Culture group. Research interests emphasize programmable imaging systems, transient imaging, non-line-of-sight sensing, and holographic displays. Key innovations include vibration sensing via dual-shutter optics and radar super-resolution for autonomous vehicles. Awards include runner-up best paper recognitions at ICCV 2007, CVPR 2014, and SIGGRAPH 2017 dissertation honors. Advisees include Dorian Chan and Arjun Teh. Grants supported by Canadian Banting Fellowships. Active in workshop organization (CVPR Computational Cameras 2016-2017) and course development on computational imaging at SIGGRAPH 2014. Labs/Teams: Leads research in computational imaging and robotics at CMU, collaborating with industry partners like NVIDIA and MDA. Current projects explore LiDAR-radar fusion, holographic projection systems, and dynamic scene reconstruction.

• Neural Interfaces
• Micro/Nano Electro Mechanical Systems (MEMS)
• Biosystems & Computational Biology
• +۳ مورد دیگر

Michel M. Maharbiz is a Professor in the Department of Electrical Engineering and Computer Science at the University of California, Berkeley. He leads research on miniaturized bioelectronic interfaces, including neural dust implants and cyborg insects. He holds affiliations with the Berkeley Sensor & Actuator Center (BSAC), Center for Neural Engineering & Prostheses (CNEP), and SWARM Lab. His education includes a Ph.D. in EECS from UC Berkeley (2003) and a B.S. in EE from Cornell University (1997). Maharbiz's research integrates MEMS, ultrasonic systems, and synthetic biology to develop wireless neural interfaces, implantable sensors, and biohybrid devices. Key focus areas are neural dust technology for peripheral nerve recording, magnetoelastic strain sensors for medical applications, and electrochemical biosensing using bacterial flagellar motors. His publications emphasize neural interfaces, ultrasonic implants, and biomedical monitoring. Recent articles explore ultrasonic power delivery (2025), radiation detectors for oncology (2025), and fracture-healing smart plates (2019). Trends include miniaturization of wireless implants, closed-loop therapeutic systems, and novel biomaterials. Scientific Awards: McKnight Technological Innovations in Neuroscience Award (2017) Chan-Zuckerberg Biohub Investigator (2017) NSF CAREER Award (2009) MIT TR10 Top Emerging Technology (2009) Bakar Fellows Spark Award (2012) He directs the Maharbiz Lab, advancing neural dust and bioelectronic interfaces. Projects include impedance-based fracture monitoring, carbon fiber neural arrays, and hernia repair sensors. Funding includes NSF and industry partnerships for implantable device development.

Dennis Säringمشاهده پروفایل

استاد

• Deep Learning
• Medical Image Analysis
• Artificial Intelligence
• +۵ مورد دیگر

Prof. Dr. Dennis Säring is a faculty member at the University of Applied Sciences Wedel , specifically affiliated with the School of Engineering. His academic and research activities focus on Deep Learning , Medical Image Analysis , and applications of Artificial Intelligence in healthcare and biomedical imaging. He has led seminars on Deep Learning topics and supervised student projects in Autonomous Driving at Audi's AADC 2018 competition. Research Highlights : Cardiovascular imaging, forensic age estimation via MRI, neural network-based bone segmentation, and cerebrovascular aneurysm analysis. Technical Expertise : Cardiac MRI, 3D/4D image processing, parametric mapping, and spatiotemporal data fusion. His recent publications (2018-2023) emphasize 3D MR segmentation for age assessment, CMR strain analysis in athletes, and T1/T2 mapping for myocarditis. Key collaborations include institutions like the University Medical Center Hamburg-Eppendorf and Wedler Hochschulbund, with funding for autonomous vehicle research. While no explicit scientific awards are listed, his work spans clinical cardiology, forensic radiology, and AI-driven medical diagnostics.

Joseph Bentsmanمشاهده پروفایل

استاد

• Control of nonlinear systems
• Control of distributed parameter systems
• Nonlinear oscillations
• +۷ مورد دیگر

Joseph Bentsman is a Professor in the Department of Mechanical Science and Engineering at the University of Illinois at Urbana-Champaign's Grainger College of Engineering. He also holds affiliate appointments in the Department of Aerospace Engineering (since 2015) and the Department of Electrical and Computer Engineering (since 2018). His academic journey began with an M.S. from Byelorussian Polytechnic Institute in Minsk, USSR (1979), followed by a Ph.D. in Electrical Engineering from Illinois Institute of Technology (1984). Professor Bentsman's research focuses on control of nonlinear and distributed parameter systems, nonlinear oscillations, network control, stability theory, and stochastic multiscale methods. He pioneered a new class of dynamical systems with active singularities that admit control actions during singular phases of motion, which represent a novel category of hybrid systems characterized by impulsively controlled discrete transitions. His recent work has expanded into biomedical applications, particularly thermophysical modeling of tissue during electrosurgery and control of phase change processes. His recent publications (2021-2024) reveal a strong trend toward biomedical applications of control theory, particularly in modeling heat conduction in biological tissues, electrosurgical processes, and phase change phenomena. Approximately 60% of his recent work focuses on biomedical applications, while the remainder continues his foundational work on nonlinear control systems, distributed parameter systems, and systems with active singularities. Key subfields include Stefan problems, enthalpy-based control, telegraph equation modeling, and PDE-based control of complex physical processes. NSF Presidential Young Investigator Award (1989) Life Fellow of American Society of Mechanical Engineers Life Senior Member of IEEE IEEE Control Systems Society Technical Committee Chair on Power Generation (2015-2019) International Society of Automation POWID Achievement Award (2014) 2018 AIST Computer Applications Best Paper Award Featured in 'People in Control', IEEE Control Systems Magazine (2018) Professor Bentsman has been instrumental in developing educational approaches that integrate signal processing, instrumentation, control, and machine learning, as evidenced by his two textbooks. His work on the steel continuous casting process, particularly the mold oscillation system, has led to practical industrial applications. He has also made significant contributions to power plant control systems and boiler/turbine control. His research group appears to focus on both theoretical control systems development and practical implementation in industrial and biomedical settings, with strong connections to steel manufacturing, power generation, and medical device industries.

Canan Dagdevirenمشاهده پروفایل

دانشیار

• Biomedical Engineering
• Piezoelectric Devices
• Wearable Electronics
• +۶ مورد دیگر

Dr. Canan Dagdeviren is an Associate Professor and LG Career Development Professor of Media Arts and Sciences at the Massachusetts Institute of Technology, where she directs the Conformable Decoders research group at the MIT Media Lab. She joined the MIT faculty in January 2017 and has established herself as a leading innovator in conformable biomedical devices. Education: Ph.D. in Materials Science and Engineering, University of Illinois at Urbana-Champaign M.Sc. in Materials Science and Engineering, Sabanci University, Istanbul, Turkey B.Sc. in Physics Engineering, Hacettepe University, Ankara, Turkey Dr. Dagdeviren's research focuses on creating mechanically adaptive electromechanical systems that can intimately integrate with biological surfaces for sensing, actuation, and energy harvesting. She believes vital information from nature and the human body is 'coded' in various physical patterns, and her work develops 'conformable decoders' to translate these patterns into beneficial signals and energy. Her research spans wearable and implantable medical devices, with particular emphasis on piezoelectric systems that can be twisted, folded, stretched, wrapped, and implanted onto curvilinear surfaces of the human body without damage or significant alteration in performance. Analysis of her recent publications reveals a strong focus on medical applications of conformable electronics, particularly in ultrasound technology for breast cancer detection, deep brain stimulation, and bladder monitoring. Her work consistently bridges materials science, electrical engineering, and medical applications, with increasing emphasis on practical healthcare solutions that can be deployed outside clinical settings. Major Scientific Awards: NSF CAREER Award (2021) 3M Non-Tenured Faculty Award (2021) MIT Technology Review's Top 35 Innovators Under 35 (2015) Forbes' Top 30 Under 30 in Science (2015) National Academy of Engineering US Frontiers of Engineering Symposium participant (2019) Frank E. Perkins Award for Excellence in Graduate Advising Aziz Sancar Science Award Dr. Dagdeviren actively mentors graduate students and has received recognition for her advising excellence. Her research is supported by significant grants including the NSF CAREER award and has resulted in numerous patents and commercialization opportunities. She has developed innovative cleanroom-based courses at MIT that train students in microfabrication techniques for biomedical devices. The Conformable Decoders research group operates a specialized cleanroom facility at the MIT Media Lab, enabling the development and fabrication of novel conformable electronic systems. The group's work has attracted attention from major media outlets including BBC, CNN, and Nature, and has potential applications across multiple medical specialties including neurology, oncology, and urology.

Massimo Mischiمشاهده پروفایل

استاد

• Biomedical Signal Processing
• Diagnostic Imaging
• Ultrasound Technology
• +۴ مورد دیگر

Massimo Mischi is a Full Professor at the Faculty of Electrical Engineering of the Eindhoven University of Technology (TU/e) and chairs the Signal Processing Systems (SPS) Division , the largest division at TU/e with over 250 researchers. He founded the Biomedical Diagnostics (BM/d) Lab in 2012, which now includes 180 researchers and clinical/industrial advisors, focusing on biomedical signal processing for diagnostics and monitoring.

• Inverse problems and reconstruction
• Neuroimaging
• Quantitative MRI
• +۱ مورد دیگر

Daan Christiaens is a tenure track lecturer at KU Leuven's Faculty of Medicine and Faculty of Engineering Sciences. He is affiliated with the Department of Electrical Engineering (ESAT) and Department of Imaging & Pathology, serving as a member of the Medical Imaging Division and the KU Leuven Brain Institute (LBI). His academic responsibilities include membership in the Faculty Councils of Engineering Sciences and Medicine. His research focuses on: Inverse problems in medical imaging reconstruction Neuroimaging techniques for brain analysis Advanced quantitative MRI methodologies Diffusion-weighted imaging for microstructural assessment Dr. Christiaens' recent publications (2023-2025) demonstrate a consistent focus on diffusion MRI innovations, including novel reconstruction algorithms, neonatal brain development mapping, and clinical applications for neurodegenerative disorders. Key technical themes include motion correction, multi-shell modeling, and AI-enhanced image processing, while clinical applications span Alzheimer's disease, cerebral palsy, and autism research. He leads significant research projects including: MRI reconstruction with dynamic field monitoring (2024-2028) Compressed sensing for microstructure imaging (2022-2026) Neonatal diffusion MRI network connectivity analysis (2024-2028) As a core developer of the MRtrix3 software framework for medical image processing, he contributes to essential tools in neuroimaging research.

Nadia Shardtمشاهده پروفایل

دانشیار

• Interfacial thermodynamics
• Phase behavior with curvature
• CO2 storage in subsurface reservoirs
• +۹ مورد دیگر

Nadia Shardt is an Associate Professor in the Department of Chemical Engineering at the Norwegian University of Science and Technology (NTNU). Her research focuses on interfacial thermodynamics, particularly in systems with nanoscale curvature, with applications spanning atmospheric science, biomedical cryopreservation, and industrial process optimization. She contributes to teaching courses such as TKP4580 - Chemical Engineering Specialization Project and KP3100 - Chemical Engineering . PhD in Chemical Engineering (University of Alberta, 2019) BSc in Chemical Engineering (University of Alberta, 2015) Postdoctoral researcher at ETH Zurich (2020-2022) Her work addresses fundamental challenges in phase behavior under curvature constraints, combining microfluidic experimentation , Gibbsian thermodynamic modeling , and machine learning techniques to study systems like CO 2 storage media, cloud microphysics, and food emulsions. Recent publications emphasize surface tension modeling for complex multi-component systems and cryoprotectant loading efficiency. Scientific awards include the ETH Postdoctoral Fellowship Natural Sciences and Engineering Research Council of Canada (NSERC) Postdoctoral Fellowship Outstanding Academic Fellows Programme 2024-2028

Jørgen Arendt Jensenمشاهده پروفایل

استاد

• Medical Ultrasound
• Biomedical Signal Processing
• Digital Signal Processing
• +۴ مورد دیگر

Jørgen Arendt Jensen is a Professor of Biomedical Signal Processing at the Technical University of Denmark (DTU), with dual affiliations in the Department of Health Technology and the Department of Electrical Engineering (DTU Elektro). He leads the Center for Fast Ultrasound Imaging (CFU), a collaborative initiative involving DTU, BK Medical, Rigshospitalet, and DTU Nanotech. His research focuses on advanced medical ultrasound technologies, including synthetic aperture imaging, vector flow imaging, and ultrasound simulation, aiming to improve clinical image acquisition efficiency and accuracy. He teaches medical imaging courses and co-initiated the joint biomedical engineering program between DTU and the University of Copenhagen. Jensen’s work contributes to UN Sustainable Development Goals related to health and innovation. His research interests span algorithm development for fast ultrasound imaging, blood velocity characterization, and simulation of ultrasound systems. He supervises multiple PhD students and collaborates on projects involving transducer design, real-time imaging systems, and microvascular pathology analysis. Recent publications emphasize advancements in super-resolution ultrasound imaging, transducer optimization, and pressure gradient estimation. His lab, CFU, develops cutting-edge imaging solutions for clinical applications. Jensen’s contributions include patents on ultrasound imaging techniques and collaborative ventures to enhance diagnostic capabilities through interdisciplinary engineering.

Taylor Wareمشاهده پروفایل

دانشیار

• Biomaterials
• Micro/Nanotechnology
• Medical Devices
• +۷ مورد دیگر

Taylor Ware is an Associate Professor in Biomedical Engineering and Materials Science & Engineering at Texas A&M University's College of Engineering, holding the Cain Faculty Fellowship. Her research focuses on designing structured biomaterials and medical devices using stimuli-responsive polymers for clinical applications. Education: Ph.D. in Materials Science and Engineering, The University of Texas at Dallas, 2013 Research Interests: Dr. Ware pioneers the development of liquid crystal elastomers as artificial muscles and implantable electronics substrates, engineered living materials for infection treatment, and directed self-assembly of hydrogels. Her lab specializes in polymer formulation, thermomechanical testing, and microfabrication. Key research thrusts include: Smart elastomers, hydrogels, and composites for dynamic medical devices Programming liquid crystalline polymers for shape-morphing applications Engineered living materials that respond to biomolecular cues in urinary tract environments Publication Trends: Recent work (2023-2025) demonstrates convergence of materials science, microbiology, and medical device engineering. Her group advances liquid crystal elastomers for soft robotics and implantable electronics, develops engineered living materials for UTI treatment using microbial competition, and creates novel hemostats and urethral support devices. Publications emphasize translational applications in urology, wound healing, and neural interfaces. Scientific Awards: Invited Participant, NAE Japan-USA Frontiers of Engineering Bilateral (2023) Senior Member, National Academy of Inventors (2022) NSF CAREER Award (2018) Air Force Young Investigator Award (2017) NSF Graduate Research Fellowship (2011) Fellow of AIMBE (American Institute for Medical and Biological Engineering) Advising and Grants: Dr. Ware leads the Ware Lab with significant funding including an NIH R01 grant (with UT Dallas and Case Western collaborators) and the NSF CAREER award. Her lab mentors postdoctoral fellows like Mustafa (winner of a prestigious postdoctoral fellowship) and graduate students. Current projects are supported by the NSF Engineering Research Center HAND, focusing on advanced materials for healthcare applications. Laboratory and Teams: The Ware Lab collaborates globally and is featured in Texas Monthly, Houston Chronicle, and National Geographic for breakthroughs in engineered living materials. As part of the NSF HAND ERC, the lab develops dynamic materials for stress urinary incontinence treatment and collaborates with medical institutions on UTI therapies using engineered E. coli strains.

• Biomaterials
• Nanomedicine
• Drug Delivery
• +۵ مورد دیگر

Marjo Yliperttula is a Professor at the Department of Pharmaceutical Biosciences, Faculty of Pharmacy, University of Helsinki. She serves as a supervisor in the Doctoral Programmes in Biomedicine, Drug Research, and Materials Research and Nanosciences, with expertise in biomaterials and pharmaceutical technology. Her research focuses on nanofibrillated cellulose (NFC) hydrogels for wound healing and drug delivery, extracellular vesicle (EV) engineering for therapeutic applications, and freeze-drying technologies for biomaterial preservation. Key contributions include NFC-based wound dressings that enhance platelet-rich plasma release (2024), Raman spectroscopy methods for monitoring freeze-drying-induced mutarotation (2024), and tandem chromatography techniques for high-purity EV isolation (2023). Her work bridges pharmaceutical sciences with regenerative medicine, emphasizing translational applications in chronic wound treatment and targeted drug delivery. Recent publications (2022-2025) reveal three dominant trends: (1) Optimization of NFC hydrogels for controlled drug release and tissue regeneration, (2) Advanced characterization of EV phenotypes under hypoxic conditions for improved therapeutic efficacy, and (3) Development of analytical methods (Raman spectroscopy, chromatography) to address manufacturing challenges in biopharmaceuticals. These themes reflect her group's commitment to solving critical problems in biomaterial stability, EV-based delivery, and precision wound care. Professor Yliperttula has supervised 10 doctoral theses, including recent work on NFC for skin substitutes (Elle Koivunotko), freeze-drying of hydrogels (Arto Merivaara), and mesenchymal stromal cells for wound healing (Jasmi Snirvi). She currently leads the Academy of Finland-funded GeneCellNa project (2024-2026) on gene/cell/nanotherapy for chronic diseases and a Finnish Red Cross project (2023-2024) on NFC for blood products, with cumulative project funding spanning 18 initiatives since 2005. She heads the Biopharmaceuticals Group within the Drug Research Program, fostering collaborations across pharmaceutical biosciences, materials science, and clinical medicine to advance next-generation therapeutic platforms.

James Ashton-Millerمشاهده پروفایل

استاد

• Biomechanics
• ACL injury
• Sports injury
• +۱۵ مورد دیگر

Dr. James Ashton-Miller is a prominent faculty member in the Department of Mechanical Engineering at the University of Michigan, where he directs the Biomechanics Research Laboratory. He serves as a Center Member of the University of Michigan Injury Prevention Center and maintains affiliations with the Institute of Gerontology. His interdisciplinary work bridges engineering principles with medical applications, focusing on injury prevention across sports medicine, obstetrics, and geriatrics. Dr. Ashton-Miller's educational background includes: PhD from the University of Oslo, Oslo, Norway (1978-1983) MSME from M.I.T., Cambridge, MA, U.S.A (1972-1974) B.SC. (Hons) from the University of Newcastle-upon-Tyne, Newcastle-upon-Tyne, England (1967-1972) His research focuses on the biomechanics of injury prevention across multiple critical domains. In sports medicine, he has demonstrated that some ACL injuries are overuse injuries resulting from too many sub-maximal loading cycles that prevent healing of collagen damage. In women's health, his work on childbirth injuries addresses conditions that affect more women than breast cancer. His research on fall-related injuries in older adults reveals the dual threat of physical and cognitive factors. He also investigates sciatica, disc degeneration, and develops new medical devices for screening, diagnosis and treatment. Dr. Ashton-Miller's recent publications show a strong trend toward developing practical clinical applications from fundamental biomechanical research, with emphasis on advanced imaging methods, wearable sensors, and computational modeling for pelvic floor function assessment. His work consistently aims to translate engineering insights into clinical solutions for injury prevention. His research insights have earned him numerous national and international research awards, though specific awards aren't detailed in the available information. His work involves close collaboration with clinicians and surgeons who meet weekly to discuss progress and next steps. Dr. Ashton-Miller is deeply committed to mentoring, working with NIH K-series fellows along with 1-2 post-doctoral fellows, 3-5 PhD students, 2-4 M.S. students, 4-5 undergraduate students, and 2-4 young clinicians. His research is generously supported by the National Institutes of Health, National Science Foundation, National Basketball Association, Fortune 500 companies, and startup companies including Procter & Gamble and Hologic, Inc. He directs the Biomechanics Research Laboratory and co-leads the Pelvic Floor Research Group, where his teams develop new medical devices to improve screening, diagnosis, and treatment of various biomechanical conditions. These laboratories maintain strong clinical connections, ensuring research remains grounded in real-world medical challenges.

• Cancer Genomics
• Liquid Biopsies
• Machine Learning in Oncology
• +۷ مورد دیگر

Ash A. Alizadeh is the Moghadam Family Professor of Medicine, Oncology, and Hematology (by courtesy) at Stanford University, where he serves as leader of the Cancer Genomics Program at Stanford Cancer Institute. He holds multiple academic appointments including Professor in Medicine - Oncology, and membership in Bio-X, the Institute for Stem Cell Biology and Regenerative Medicine, and the Maternal & Child Health Research Institute (MCHRI). Dr. Alizadeh received his BS in Biochemistry from UCLA (1994), MD from Stanford Medical School, and PhD in Biophysics from Stanford. He completed additional training at the National Cancer Institute (NCI), the National Institutes of Health (NIH), and the Howard Hughes Medical Institute (HHMI). His primary research focuses on developing and applying genome technologies and computing (machine learning & data science) to problems in human disease, with special emphasis on cancer detection, classification, monitoring, and tumor immunology. His laboratory pioneers noninvasive cancer genomic techniques including CAPP-Seq, PhasED-Seq, and EPIC-Seq for "liquid biopsies" that analyze circulating nucleic acids for early cancer detection and monitoring therapeutic response. Using machine learning approaches, his group studies how cellular compositional variation impacts cancer behavior and therapeutic response, including anti-tumor immunity. His work spans molecular, cellular, organism and population levels of tumor behavior analysis. Dr. Alizadeh has received numerous prestigious awards including the Scholar Award from the American Society of Hematology (ASH), the Leukemia & Lymphoma Society (LLS), the V-Foundation, as well as awards from the American Red Cross, Damon Runyon Cancer Research Foundation, and Doris Duke Charitable Research Foundation. He is an elected member of the American Society for Clinical Investigation (ASCI) and serves on the Scientific Advisory Board of the Lymphoma Research Foundation (LRF). As an educator and mentor, Dr. Alizadeh advises numerous doctoral students, postdoctoral fellows, and medical scholars. He teaches in the Department of Medicine and Immunology and serves on various admissions panels at Stanford. His laboratory, the Alizadeh Lab, is a hub for interdisciplinary cancer genomics research that combines computational biology, molecular genetics, and clinical oncology to develop novel cancer diagnostics and therapeutics.

Franz Lennard Ricklefsمشاهده پروفایل

استاد

• Neurosurgery
• Neuro-oncology
• Molecular Neurobiology
• +۵ مورد دیگر

Prof. Dr. med. Franz Lennard Ricklefs is a Senior Physician and Head of the Working Group at the Department of Neurosurgery, University of Hamburg Faculty of Medicine. He is a Medical Specialist in Neurosurgery with cross-disciplinary expertise in neuro-oncology, molecular pathology, and extracellular vesicle research. Affiliations: University Medical Center Hamburg-Eppendorf (UKE), European Liquid Biopsy Society (ELBS), International Consortium on Meningiomas (ICOM) Research Interests: His work focuses on neurosurgical oncology, particularly glioblastoma and meningioma pathobiology. He investigates DNA methylation patterns, extracellular vesicle biomarkers, and liquid biopsy implementation in clinical neuro-oncology. Additional interests include surgical outcomes for epilepsy and aneurysm management. Article Trends: Over the last decade, Dr. Ricklefs has published extensively on: Extracellular vesicle applications as liquid biopsy markers DNA methylation subclasses for glioblastoma and meningioma Multicenter surgical outcome benchmarking Immune evasion mechanisms in neuro-oncology Technological innovations in neurosurgical visualization Molecular characterization of rare CNS tumors Professional Contributions: He co-authored the MISEV2023 guidelines for extracellular vesicle studies and participates in international consensus reviews for meningioma classification. His collaborations span institutions across Europe and North America.