جست‌وجوی استاد و پژوهشگر

Yahya Rahmat-Samiiمشاهده پروفایل

استاد

• Electromagnetics
• Satellite Communication Antennas
• Personal Communication Antennas
• +۵ مورد دیگر

Yahya Rahmat-Samii is a Distinguished Professor and holder of the Northrop Grumman Chair in Electrical Engineering/Electromagnetics within the Department of Electrical and Computer Engineering at the University of California, Los Angeles (UCLA). He directs the Antenna Research, Analysis, and Measurement Laboratory, focusing on cutting-edge electromagnetic systems for space, medical, and communication applications. His research spans electromagnetics with specialization in satellite communication antennas, personal communication antennas (including human interaction effects), biotelemetry, RFID applications, and antennas for remote sensing and radio astronomy. Recent work emphasizes CubeSat antenna miniaturization, implantable/wearable medical devices, and reconfigurable systems using liquid metal and 3D printing. His laboratory pioneers innovations in antenna measurement techniques and optimization algorithms. Analysis of his 15 most recent publications reveals dominant trends in space-constrained antenna design for CubeSats, biomedical applications (ingestible/implantable systems), and reconfigurable structures using novel materials. Key subfields include orbital angular momentum communications, liquid metal microfluidics, metamaterial lenses, and brain-inspired optimization algorithms, demonstrating strong interdisciplinary connections between electromagnetics, aerospace engineering, and medical technology. His scientific awards include the 2019 Ellis Island Medal of Honor, 2017 ACES Computational Electromagnetics Award, 2009 IEEE Antennas and Propagation Society Distinguished Achievement Award, 2008 National Academy of Engineering membership, and numerous IEEE and NASA recognitions. Notable honors span fundamental contributions to reflector antennas, near-field measurements, and optimization algorithms. Rahmat-Samii leads the Antenna Research, Analysis, and Measurement Laboratory at UCLA, which develops advanced measurement systems including bipolar near-field ranges and diagnostic techniques. The lab collaborates extensively with NASA, JPL, and medical research institutions on projects ranging from Mars rover communications to brain-machine interface antennas, maintaining leadership in both theoretical electromagnetics and practical antenna implementation.

Meryem Ayşe Yücelمشاهده پروفایل

استاد پژوهشی

• Functional Near-Infrared Spectroscopy
• Brain Imaging
• Clinical Applications
• +۳ مورد دیگر

Meryem Ayşe Yücel serves as a Research Associate Professor in the Department of Biomedical Engineering at Boston University's College of Engineering, where she also holds the position of Technical Director for the Neurophotonics Center. Her work bridges engineering innovation with clinical neuroscience applications, focusing on advancing functional Near-Infrared Spectroscopy (fNIRS) technology for real-world implementation. Dr. Yücel earned her PhD in Biomedical Engineering from Bogazici University in Turkey. Her educational foundation supports her interdisciplinary approach to neuroimaging research. Her research centers on developing and refining fNIRS methodologies for brain imaging, with particular emphasis on clinical translation and accessibility. She investigates cortical activation patterns during naturalistic activities like walking, conversation, and cognitive tasks, applying these insights to conditions including knee osteoarthritis, aphasia, stroke recovery, and pediatric development. Her work consistently addresses critical barriers in neuroimaging such as signal quality across diverse skin and hair types, driving inclusive research practices. Recent publications highlight her leadership in standardization efforts through projects like the fNIRS glossary and NIRS-BIDS data framework. Analysis of her recent publications reveals a strong trajectory toward mobile, high-density fNIRS systems operating in natural environments. Her research increasingly integrates multimodal approaches (fNIRS-EEG), develops open-source hardware (ninjaNIRS, ninjaCap), and establishes reproducibility standards for the field. Clinical applications dominate her output, particularly in pain assessment, rehabilitation, and cognitive neuroscience. Dr. Yücel's scientific recognition includes: Society of Functional Near-Infrared Spectroscopy Community Award (2022) Light of the Lab Award for Functional Inclusiveness (2022) TUBITAK Fellowships for Visiting Scientists (2022) Facebook Award for Engineering Approaches to Responsible Neural Interface Design (2021) SfNIRS Early Investigator Award Finalist (2016) Britton Chance Symposium Travel Award (2013) TUBITAK Integrated Doctoral Fellowship (2006-2010) As Technical Director of the Neurophotonics Center, she leads a multidisciplinary team developing next-generation optical brain imaging systems. Her leadership extends to community-building initiatives that promote open science and methodological rigor in fNIRS research, while her Facebook-funded project demonstrates successful translation of engineering solutions to neural interface challenges. The Neurophotonics Center under her technical direction pioneers wearable fNIRS technologies for naturalistic neuroscience, with recent innovations including flexible circuit-based imaging systems and 3D-printable headgear that enable high-density measurements during real-world activities. This work directly supports her research on brain function during daily movements and clinical applications.

Adrien MERLINIمشاهده پروفایل

پژوهشگر

• Computational Electromagnetics
• Integral Equations
• Neuroimaging
• +۳ مورد دیگر

Adrien MERLINI is a Researcher at IMT Atlantique's Microwave Department in Brest, France. His work focuses on computational electromagnetics, integral equation methods, and neuroimaging applications. He specializes in developing numerical techniques for low-to-high-frequency electromagnetic modeling, preconditioning strategies for integral equations, and machine learning-enhanced solutions for inverse problems. His research bridges fundamental theory and applied engineering, addressing challenges in medical imaging, material characterization, and high-performance computing. Key areas of expertise include: High-frequency spectral analysis of boundary integral operators Stabilized formulations for low-frequency electromagnetic simulations Supervised learning approaches for electrical source imaging Quasi-Helmholtz projector-based preconditioning techniques Fast direct solvers for integral equations His innovations in numerical methods have advanced applications in brain-computer interfaces, microwave-based medical imaging, and terahertz dosimetry. Collaborative projects include developing the simBCI framework for EEG simulation and the Pythran compiler for accelerating scientific Python codes. Research contributions span over 30 peer-reviewed articles since 2015, with recent emphases on conditioning analysis of electromagnetic integral equations and regularization strategies for neuroimaging inverse problems.

• Ethnolinguistics
• Phraseology
• Phonodidactics
• +۳ مورد دیگر

Aleksandra Blatešić serves as an Associate Professor at the Department of Romance Studies, Faculty of Philosophy, University of Novi Sad, where she has been employed since 2004. Her teaching portfolio includes Italian Language courses (Levels 3-8) for undergraduate students and specialized graduate courses in Phonodidactics of the Italian Language and Comparative Phraseology of the Italian and Serbian Languages. Her academic credentials feature: High School: Graduated from "Jovan Jovanović Zmaj" in Novi Sad (Social and Linguistics major) Bachelor's Degree: Italian Language and Literature, Faculty of Philology, Belgrade (2001) Master's Degree: Thesis on Italian proverbs as a phraseological and translation problem (2007) Doctorate: Dissertation on Zero Article in Modern Italian (2012) Blatešić's research centers on ethnolinguistics, phraseology, and phonodidactics with emphasis on Italian-Serbian comparative analysis. She investigates syntax-semantics interfaces, cognitive linguistics frameworks, and technology integration in language pedagogy, maintaining active ties with Italian institutions including Università per Stranieri di Siena and Ca' Foscari University of Venice. Her 2014-2018 publications reveal consistent focus on Italian linguistic structures through a cross-cultural lens. Key trends include ethnonym-based phraseology studies, zero article syntax analysis, and sociolinguistic documentation of Istrian/Rijeka Italian communities. The works demonstrate interdisciplinary methodology bridging theoretical linguistics, applied pedagogy, and Balkan language contact phenomena. Scientific awards: No awards listed in current profile Professional activities include textbook authorship and Italian cultural promotion but no current advisees or grant projects are specified. Her scholarly output remains concentrated on empirical linguistic analysis without indication of formal advising roles or externally funded research initiatives.

Wei Minمشاهده پروفایل

استاد

• Biophotonics
• Optical Spectroscopy
• Raman Microscopy
• +۶ مورد دیگر

Dr. Wei Min is a tenured full Professor in the Department of Chemistry at Columbia University's Faculty of Arts and Sciences. He leads a prominent Biophotonics Lab focused on developing novel optical spectroscopy and microscopy technologies, particularly stimulated Raman scattering (SRS) microscopy, to address biomedical challenges. His research bridges chemistry, physics, and biology with significant applications in metabolic imaging and cellular dynamics. Dr. Min earned his Bachelor's degree from Peking University in 2003 and completed his Ph.D. in Chemistry at Harvard University in 2008, working with Prof. Sunney Xie on single-molecule biophysics. After continuing his postdoctoral work in the Xie group, he joined Columbia University's Chemistry Department faculty in 2010 and achieved tenure as a full Professor in 2017. His research focuses on developing novel optical spectroscopy and microscopy technologies to address biomedical problems, with particular emphasis on stimulated Raman scattering (SRS) microscopy and corresponding labeling techniques. His lab aims to study the distribution and dynamics of small bio-molecules in living systems, addressing biological problems on metabolism through small molecule imaging and metabolic labeling techniques at both cell level and in vivo. His work has significantly advanced the field of vibrational imaging, breaking through the 'color barrier' of fluorescence microscopy to enable super-multiplexed imaging with unprecedented chemical specificity. Dr. Min's publication record demonstrates a consistent trajectory of high-impact research in biophotonics and chemical imaging. His most recent work focuses on super-resolution vibrational imaging, multiplexed tissue analysis, metabolic tissue atlas mapping, and applications in materials science. The research shows a clear progression from fundamental technique development to diverse biomedical and materials applications, with increasing complexity in multiplexing capabilities and imaging depth. Biophotonics Technology Innovator Award (2023) Craver Award of Vibrational Spectroscopy, Coblentz Society (2022) The Raman Award for the Most Innovative Technological Development, International Conference on Raman Spectroscopy (2022) Scientific Achievement Award, the Royal Microscopical Society (2021) Multiple Blavatnik National Awards for Young Scientists finalist positions (2019-2021) ACS Early Career Award in Experimental Physical Chemistry (2017) National Institute of Health (NIH) Director's New Innovator Award (2012) Dr. Min has mentored numerous students and postdocs, many of whom have gone on to faculty positions at prestigious institutions including Fudan University, Peking University, Tsinghua University, Caltech, and UC San Diego. His lab currently includes five PhD students and three postdoctoral researchers. His research is supported by significant grants, including the NIH Director's New Innovator Award, reflecting the innovative nature and potential impact of his work. The lab operates at the intersection of chemistry, physics, and biology, developing tools that enable new biological discoveries while advancing the fundamental science of optical imaging. Dr. Min's Biophotonics Lab maintains a strong focus on developing next-generation imaging technologies that overcome limitations of existing approaches. The lab's recent work on super-resolution vibrational imaging, multiplexed tissue analysis, and metabolic mapping demonstrates their commitment to pushing the boundaries of what's possible in optical imaging, with applications spanning basic biological research, disease diagnosis, and materials science.

Chen Liuمشاهده پروفایل

استادیار

• Numerical Analysis
• Computational Mathematics
• Fluid Dynamics
• +۲ مورد دیگر

Chen Liu is an Assistant Professor of Mathematics in the Department of Mathematical Sciences at the University of Arkansas's Fulbright College of Arts and Sciences. He holds a PhD in Computational and Applied Mathematics from Rice University. Research Interests: Dr. Liu's research focuses on developing advanced numerical methods for partial differential equations, particularly discontinuous Galerkin schemes for fluid dynamics applications. His work emphasizes structure-preserving algorithms for hyperbolic conservation laws, Navier-Stokes equations, and multiphase flow problems. Key research areas include bound-preserving limiters, high-order accuracy schemes, and efficient solvers for complex physical systems. Publication Trends: His recent publications demonstrate a consistent focus on improving numerical stability and accuracy for challenging fluid dynamics problems. Common themes include positivity-preserving schemes, multiphysics coupling (particularly Cahn-Hilliard-Navier-Stokes systems), and applications to porous media flow. Recent work shows increased emphasis on optimization-based approaches and implicit-explicit time integration techniques. Awards: No scientific awards mentioned. Academic Activities: No information available regarding students advised, research grants, or laboratory facilities.

Lenore Cowenمشاهده پروفایل

استاد

• Computational Molecular Biology
• Data Science
• Graph Algorithms
• +۵ مورد دیگر

Lenore Cowen is a Professor in the Department of Computer Science and Mathematics at Tufts University, with additional affiliation in the Graduate Biomedical Sciences program. She holds a Ph.D. in Mathematics from MIT (1993) and a B.A. from Yale (1987). After postdoctoral work at Johns Hopkins, she joined Tufts in 2001, where her research bridges discrete mathematics, graph algorithms, and computational molecular biology. Education : Ph.D. in Mathematics, MIT (1993); B.A. in Mathematics, Yale (1987) Her research spans computational molecular biology , focusing on protein structure/function prediction, network science for biological systems, and coral bioinformatics. Key projects include developing GLIDE and D-SCRIPT algorithms for protein interaction prediction, leading the Synthetic Coral NSF project, and advancing MEDFORD for metadata markup in ecological studies. Recent publications highlight coral resilience , drug-target interaction prediction , and 3D network visualization . She co-chaired major conferences like RECOMB and SIAM ACDA , and serves as Associate Editor for Bioinformatics and on the editorial board of IEEE/ACM TCBB . Awards include CRA-E and NCWIT mentoring honors, and fellowships from SIAM and ISCB . She mentors graduate students across computational biology and network science , collaborating with interdisciplinary teams like the Tufts BCB group and Wellesley College. Her work is funded by NSF and NIH grants, including contributions to the DREAM Disease Module Identification Challenge and high-dimensional data analysis in genomics.

• Physics
• Biomedical Engineering
• Neuroscience
• +۳ مورد دیگر

Prof. Zdenka Kuncic is a Professor of Physics at the School of Physics , University of Sydney. She holds a BSc (Hons I) from the University of Sydney and a PhD in theoretical astrophysics from the University of Cambridge. Her research bridges physics, medicine, biology, neuroscience, and engineering, focusing on interdisciplinary applications of physics-based approaches to solve complex problems. Key affiliations include the University of Sydney Nano Institute and the Charles Perkins Centre. Her research interests include neuromorphic computing, nanoparticle-based medical imaging, and quantum technologies. Notable grants include the 2024 Reconfigurable Neuromorphic Compute System (ARC LIEF) and the AMTAR Hub (2023). Media highlights include features in The Conversation , Financial Times , and ABC Science . Recent innovations include nanowire networks mimicking brain-like learning and memory, and advancements in MRI-guided radiotherapy using nanoparticles. Her work emphasizes translational research with potential impacts on healthcare and technology.

Frank Ellrichمشاهده پروفایل

استاد

• Terahertz Technology
• Communications Engineering
• Digital Signal Processing
• +۳ مورد دیگر

Prof. Frank Ellrich is a Professor of Communications Engineering, Digital Signal Processing, and Terahertz Technology at the Technical University of Bingen, Department 2 – Technology, Computer Science and Economics. He holds a Dr.-Ing. from TU Kaiserslautern and has extensive research experience at Fraunhofer Institutes (IPM and ITWM). His work focuses on terahertz spectroscopy for industrial applications like layer thickness measurement and non-destructive testing, with notable contributions to THz sensor systems and security technologies. He actively participates in SPIE Photonics West and has authored over 50 publications in optics, materials science, and engineering. Awards include the VDE Prize (2002) and the Fraunhofer Excellence Award (2013). Teaching responsibilities include courses on digital transmission, optical systems, and signal processing at both BA and MA levels. His research integrates advanced measurement techniques with industrial challenges, emphasizing practical applications in automotive, aerospace, and security sectors. Ellrich leads projects on THz-based substance identification and has pioneered interferometric methods for precision measurements. His work bridges fundamental physics with engineering solutions, addressing real-world problems in material analysis and quality control. Key achievements include development of fiber-coupled THz systems, vibration-compensated measurement setups, and real-time self-calibration methods. He collaborates internationally, presenting at conferences worldwide (e.g., IRMMW-THz, CLEO). His patents cover spectral logic for hazardous substance detection and interferometric THz techniques. Current focus areas include industrial automation of THz inspection and enhancing THz imaging resolution for complex environments.

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۷ مورد دیگر

Jiaqi Liu is an Associate Professor in the Department of Computer Science and Engineering at Southern University of Science and Technology in Shenzhen, China. His research spans multiple domains within artificial intelligence, with a particular focus on autonomous systems, multimodal learning, and computer vision. He maintains active collaborations with researchers across China and internationally, particularly with Jian Sun and Peng Hang on autonomous driving projects. Dr. Liu's research interests encompass a broad spectrum of AI and computer science topics. His work in autonomous driving involves developing sophisticated decision-making frameworks for cooperative vehicle systems. In multimodal learning, he has pioneered approaches for handling missing modalities and creating adaptive fusion networks. His signal processing research includes innovative methods for sleep staging and EEG analysis using dynamic mode decomposition techniques. Additional research areas include photonic computing accelerators, graph neural networks, and quantum neural networks. The publication trend shows significant growth in output quality and quantity, with numerous papers in top-tier venues including IEEE Transactions, CVPR, AAAI, and IJCAI. His work demonstrates a strong interdisciplinary approach, bridging computer science with applications in healthcare, robotics, and telecommunications. Recent publications indicate increasing focus on the integration of large language models with reinforcement learning for autonomous systems. Dr. Liu has received recognition through publications in high-impact journals and conferences including: IEEE Transactions on Intelligent Transportation Systems IEEE Robotics and Automation Letters Expert Systems with Applications CVPR (Computer Vision and Pattern Recognition) AAAI Conference on Artificial Intelligence His research program involves collaborations across multiple domains, with current projects focusing on language-guided autonomous driving, multimodal sentiment analysis, and advanced signal processing techniques. He leads research efforts in developing novel deep learning architectures for complex real-world problems, particularly in the domains of autonomous systems and healthcare applications.

Christoph Mengelkampمشاهده پروفایل

مدرس

• Educational Psychology
• Metacognition
• Learning with digital media
• +۵ مورد دیگر

Dr. Christoph Mengelkamp serves as a Lecturer and Study Abroad Advisor at the Institute for Human-Computer Media, University of Würzburg, where he has been employed since 2011. Originally joining the Chair of Instructional Psychology and New Media, he transitioned to the Psychology of Communication and New Media chair in 2017. His academic foundation includes a doctorate from the University of Koblenz-Landau (2009) focused on metacognition in learning, with prior research experience at the Center for Empirical Educational Research in Landau. Mengelkamp's research centers on the intersection of cognitive processes and digital learning environments. His primary interests include how learners process narrative texts, develop metacognitive awareness during self-regulated learning, and interact with multimedia elements such as interactive animations. He investigates pedagogical diagnostics methods and examines how visual design elements (colors, shapes) influence learning outcomes. His work bridges educational psychology with human-computer interaction, particularly examining how digital interfaces shape cognitive processing and comprehension. His publication record reveals consistent research productivity through 2025, with recent work expanding into misinformation correction, teleworking performance, and mobile media consumption. Across these diverse topics, his research maintains a core focus on metacognitive processes and learning regulation. The majority of his publications appear in high-impact educational and cognitive psychology journals, demonstrating substantial collaboration with Professor Markus Appel and colleagues at Würzburg. Mengelkamp teaches courses in communication psychology and research methods, drawing directly from his expertise in learning processes and media effects. His role as Study Abroad Advisor complements his research on learning environments by providing practical experience with diverse educational contexts. While specific grant information isn't detailed in the available materials, his extensive publication record suggests successful funding for multiple research projects examining digital learning environments and cognitive processes.

Merlyn Pulikkatharaمشاهده پروفایل

استادیار

• Nanotechnology
• Materials Science
• Radiation Physics
• +۳ مورد دیگر

Dr. Merlyn Pulikkathara is an Assistant Professor in the Department of Chemistry and Physics at Prairie View A&M University's Brailsford College of Arts & Sciences. A double graduate of PVAMU (BS '01, MS '04) and PhD in applied physics from Rice University, she became the first female physics tenure-track professor at PVAMU in 2020. Her research spans nanotechnology applications in aerospace, petroleum, and cancer research, with over 20 publications and significant grants including a $491,847 DoD award (2022) for STEM research enhancement. Education: BS in Physics & Chemical Engineering (PVAMU '01), MS in Engineering (PVAMU '04), PhD in Applied Physics (Rice University) Research Focus : Nanotechnology for radiation protection and sensing Carbon nanotube-polymer composites STEM/STEAM education innovation Medical applications in cancer treatment Aerospace and petroleum material engineering The 15 most recent publications demonstrate expertise in radiation effects on nanocomposites, functionalized carbon nanotube synthesis, and biomedical applications. Her work shows progression from fundamental material science (2002-2010) to advanced applications in radiation sensing (2010-2024) and STEM education initiatives (2022). Scientific Recognition : Best Faculty Award in Physics (PVAMU 2019) Harry B. Weiser Award for Teaching Excellence (Rice University 2008) Excellence in Chemistry Teaching (Rice University 2007) Dr. Pulikkathara actively mentors students and participates in institutional governance through the Faculty Senate Executive Board. Her teaching philosophy emphasizes student empowerment through problem-solving skills and interdisciplinary thinking, particularly for underrepresented groups in STEM.

Xinwei Dengمشاهده پروفایل

استاد

• Statistical Learning
• Uncertainty Quantification
• High-Dimensional Data Analysis
• +۷ مورد دیگر

Xinwei Deng is a Professor of Statistics and Data Science Faculty Fellow at Virginia Tech, affiliated with the Department of Statistics in the College of Science. He also co-directs the VT Statistics and Artificial Intelligence Laboratory (VT-SAIL). He earned his Ph.D. from Georgia Institute of Technology in 2009 under Professors C.F. Jeff Wu and Ming Yuan, and joined Virginia Tech in 2011. Education: PhD in Statistics (Georgia Tech, 2009), B.S. in Mathematics (Nanjing University, China, 2003). Research Interests: Focuses on the interface between experimental design and machine learning, uncertainty quantification, covariance matrix estimation, high-dimensional data analysis, and applications in nanotechnology, manufacturing, and healthcare. His work bridges statistical theory with practical challenges in emerging technologies like tissue engineering and environmental science. Publications: Over 80 peer-reviewed articles in top journals such as Journal of the American Statistical Association , Technometrics , and Proceedings of the National Academy of Sciences . Recent work emphasizes scalable algorithms, AI resilience in manufacturing, and uncertainty quantification in complex systems. Awards/Honors: Includes Data Science Faculty Fellowships, ISI election (2017), and multiple best paper awards. Recognized for contributions to statistical methodologies in quality engineering and AI robustness. Teaching & Advising: Teaches advanced courses like Data Analytics, Experimental Design, and Multivariate Analysis. Mentors students in interdisciplinary projects spanning statistics, computer science, and engineering. Labs/Teams: Leads VT-SAIL, fostering AI-driven statistical solutions for real-world problems. Collaborates with industry partners (e.g., P&G, Deloitte) and government agencies (NSF, AFRL) on applied research.

• Homogenization Theory
• Calculus of Variations
• Nonlinear Analysis
• +۳ مورد دیگر

Valeria Chiadò Piat is an Associate Professor at Politecnico di Torino, specializing in homogenization theory, calculus of variations, and nonlinear analysis. Her research focuses on multiscale problems, including the analysis of degenerate functionals, oscillating manifolds, and composite materials. She has organized significant events such as the 2025 'Perspectives in the Calculus of Variations' conference and the 2020 'Calculus of Variations and Applications' workshop. Her work bridges theoretical analysis and applied material science, with key contributions to homogenization of high-contrast materials, discrete double-porosity models, and anisotropy properties in polycrystalline magnetic systems. Notable collaborations include projects with A. Braides on extension theorems and non-local functionals, and with O. Bottauscio on magnetic materials' effective properties. Recent publications (2021–2025) emphasize relaxation of degenerate functionals and homogenization in oscillating domains. Her research also explores phase transitions in composite media and variational inequalities for elasto-plastic systems. She has contributed to both foundational theory and numerical methods in material science.

• Organic Chemistry
• Biochemistry
• Biophysics
• +۷ مورد دیگر

Mirna El Khatib is a Research Assistant Professor in the Department of Biochemistry and Biophysics at the Perelman School of Medicine, University of Pennsylvania. She specializes in organic chemistry and biomedical imaging, with a focus on oxygen sensing and the radiobiological effects of FLASH radiotherapy. Her research centers on the development of membrane-anchored imaging probes and understanding the mechanisms behind the FLASH effect, which involves ultra-high dose rate radiation therapy. Her work integrates synthetic chemistry, photophysics, and in vivo imaging techniques to study tumor hypoxia, blood flow dynamics, and therapeutic optimization. The recent publications highlight a strong trend in oxygen monitoring , radiation biology , and photodynamic therapy , often in collaboration with multidisciplinary teams across institutions. Her work bridges fundamental chemistry with translational medical applications, particularly in oncology and neurophotonics. Scientific Awards: NIH K25 Fellowship Dr. El Khatib mentors graduate students, including MD/PhD candidate Charlotte Monsour, and is actively involved in collaborative research projects. She has contributed to studies involving photodynamic therapy optimization, real-time oxygen tracking, and novel probe development. Her group receives support through collaborative grants, particularly within the Vinogradov Lab, which has strong ties to Penn’s Chemistry Department and external institutions such as MGH/Harvard and Dartmouth College. She is a key member of the Vinogradov Lab, which focuses on developing advanced optical imaging tools and sensors. The lab fosters a collaborative environment involving physicists, chemists, and biomedical engineers working on cutting-edge problems in biophysics and medicine.