جست‌وجوی استاد و پژوهشگر

Mehmet Kurtمشاهده پروفایل

دانشیار

• Brain Biomechanics
• Neuromechanics Imaging
• Nonlinear Systems
• +۵ مورد دیگر

Mehmet Kurt is an Associate Professor at the University of Washington in the Department of Mechanical Engineering and an Adjunct Associate Professor in the Department of Radiology. He directs Kurtlab , a multidisciplinary research group focused on brain mechanobiology and advanced neuroimaging. B.Sc. in Mechanical Engineering, Bogazici University (2010) Ph.D. in Mechanical Science and Engineering, University of Illinois at Urbana-Champaign (2014) Postdoctoral Scholar, Department of Bioengineering at Stanford University (2014–2016) Assistant Professor at Stevens Institute of Technology (2016–2022) Research interests span brain biomechanics, neuromechanics imaging, nonlinear systems, and smart biomedical devices. His work integrates advanced neuroimaging tools (e.g., 3D aMRI, 7T MRI, MR Elastography) with multi-scale computational models to study traumatic brain injury (TBI), Alzheimer's Disease, Chiari Malformation I, intracranial aneurysms, and hydrocephalus. Key projects include: Investigating perfusion-mechanics coupling in the hippocampus Developing 3D amplified MRI (aMRI) for intrinsic brain motion quantification Characterizing brain tissue viscoelasticity across age groups Designing patient-specific computational fluid dynamics simulations Creating AI-driven tumor segmentation frameworks Scientific awards include: NSF Vizzie Best Scientific Visualization Award (2018) Lucile Packard Children's Hospital Postdoctoral Fellowship Thrasher Research Foundation Early Career Award Provost's Early Career Award for Research Excellence Fortune Magazine's 40 Under 40 in Turkey (2020) Annals of Biomedical Engineering Editor's Choice Award Grants from NSF, NIH, and DoD support his work. He actively mentors LGBTQ+ students in STEM through programs like PRIDE and Kurtlab , which trains undergraduates, graduate students, and postdocs in neuroimaging and biomedical device development.

Otto Muzikمشاهده پروفایل

دانشیار

• Medical Imaging
• Neuroimaging
• Pediatric Radiology
• +۴ مورد دیگر

Dr. Otto Muzik is an Associate Professor in the Department of Pediatrics at Wayne State University School of Medicine . His research focuses on PET imaging and Pediatric imaging , with specific interests in Epilepsy , Brown Adipose Tissue (BAT) , and brain network connectivity using PET and fMRI methodologies. Key research themes include: Understanding neural mechanisms in human thermoregulation Developing automated AI-driven solutions for motion correction in total-body PET/CT Optimizing dose reduction strategies in PET/MR epilepsy imaging Translating novel radiotracers like [18F]FETrp for clinical cancer imaging Advancing theranostic approaches in nuclear medicine Exploring predictive processing models in brain function He actively teaches graduate courses in Nuclear Medicine Physics and Imaging Physics , and collaborates with Vaibhav Diwadkar on neuroimaging research. His work appears in journals like Wiley Interdisciplinary Reviews: Cognitive Science and Journal of Nuclear Medicine .

Smita Krishnaswamyمشاهده پروفایل

دانشیار

• Unsupervised Machine Learning
• Manifold Learning
• Deep Learning
• +۷ مورد دیگر

Smita Krishnaswamy is an Associate Professor of Genetics and Computer Science at Yale University with joint appointments in both departments. She is affiliated with multiple interdisciplinary programs including the Applied Mathematics Program, Computational Biology and Bioinformatics Program, Yale Center for Biomedical Data Science, Yale Cancer Center, and the Wu Tsai Institute. Her research bridges computational methods development with biomedical applications, focusing on unsupervised machine learning approaches for high-dimensional data analysis. Associate Professor of Genetics, Yale School of Medicine Associate Professor of Computer Science, Yale University Affiliated Faculty, Applied Mathematics Program Affiliated Faculty, Computational Biology and Bioinformatics Member, Yale Center for Biomedical Data Science Member, Yale Cancer Center Member, Wu Tsai Institute Dr. Krishnaswamy's research focuses on developing unsupervised machine learning techniques, particularly manifold learning and deep learning methods, to analyze high-dimensional biomedical data. Her lab creates algorithms for non-linear dimensionality reduction, data geometry learning, denoising, imputation, and inference of multi-granular structures from complex datasets. These methods are applied to diverse data types including single-cell RNA-sequencing, mass cytometry, electronic health records, and connectomic data across multiple biological systems. Her work spans several key application areas including immunology and immunotherapy, cancer research, neuroscience, developmental biology, and health outcomes analysis. The lab employs approaches from geometric deep learning, multiscale graph signal processing, and topological data analysis to extract meaningful biological insights from complex datasets. Recent publications demonstrate the lab's leadership in developing methods for spatial transcriptomics, brain-state trajectory modeling, and organ donation prediction. Excellence in Science Early-Career Investigator Award from FASEB (2022) Yale Cancer Center Class of '61 Cancer Research Award (2025) Dr. Krishnaswamy maintains active collaborations across Yale and secures research funding supporting her work in computational biomedicine. She advises students through multiple programs including Genetics, Computer Science, and the Biological and Biomedical Sciences Graduate Program, fostering interdisciplinary training at the intersection of computation and biomedicine. The Krishnaswamy Lab operates at the forefront of computational biomedicine, developing mathematical approaches that enable new biological discoveries from complex datasets.