جست‌وجوی استاد و پژوهشگر

Ipek Oguzمشاهده پروفایل

دانشیار

• Medical Image Analysis
• Graph Theoretic Techniques
• Longitudinal Imaging Studies
• +۱۰ مورد دیگر

Ipek Oguz is an Associate Professor at Vanderbilt University, holding joint appointments in the Department of Computer Science, Electrical and Computer Engineering, and Biomedical Engineering. She received her PhD in Computer Science from the University of North Carolina at Chapel Hill in 2009 and previously worked at leading institutions such as the University of Pennsylvania and the University of Iowa. Education PhD, Computer Science, University of North Carolina-Chapel Hill (2009) M.S., Computer Science, University of North Carolina-Chapel Hill (2007) B.S., Computer Engineering, Middle East Technical University (2004) Dr. Oguz specializes in medical image analysis , focusing on graph-based segmentation methods, longitudinal studies, and machine learning. Her research bridges computational techniques with clinical applications in neurodegenerative diseases, ophthalmology, and obstetrics. She leads the Medical Image Computing Laboratory (MedICL) , which develops algorithms to enhance diagnostic and predictive capabilities through MRI, OCT, and diffusion imaging. Key projects include: Early detection of Huntington’s Disease via longitudinal basal ganglia and cortical thickness analysis Characterizing cortical gray matter atrophy in Multiple Sclerosis Innovative placental assessment using multi-modality imaging She serves on the VISE Steering Committee and co-chaired the VISE Seminar Series (2023-2024). Her work intersects Big Data , Biomedical Engineering , and Clinical Applications , with collaborations across Vanderbilt’s Schools of Engineering and Medicine.

Xiaoyao Fanمشاهده پروفایل

استادیار

• Image Guidance
• Neurosurgery
• Brain Deformation
• +۸ مورد دیگر

Xiaoyao Fan is an Assistant Professor of Engineering at Dartmouth College, specializing in image guidance systems for neurosurgery and spine surgery. His work focuses on improving intraoperative imaging accuracy through computational modeling, stereovision, and ultrasound technologies. He collaborates with the Center for Surgical Innovation (CSI) at Dartmouth-Hitchcock Medical Center (DHMC) and has contributed to over 400 surgical cases involving real-time imaging and feedback systems. Education: B.E. in Electrical Engineering, Tsinghua University (2007) Ph.D. in Biomedical Engineering, Dartmouth College (2012) Research Interests: His research emphasizes minimizing surgical errors via real-time brain deformation compensation, spine motion correction, and intraoperative imaging systems. Techniques include stereovision, 3D ultrasound, and machine learning for image registration and navigation. Key applications include open and minimally invasive neurosurgical procedures. Publications: His work spans stereovision systems for spinal surgery, brain shift compensation algorithms, and intraoperative ultrasound registration. Recent contributions address human feasibility and porcine model validation of surgical navigation tools. Grants & Labs: Collaborates with Medtronic on integrating updated imaging into navigation systems. Active in the CSI DHMC lab, focusing on clinical translation of real-time imaging solutions. Teaches ENGS 111: Digital Image Processing. Labs & Teams: Works within Dartmouth’s engineering and medical collaboration networks, advancing surgical precision through interdisciplinary research.

Ralf Haefnerمشاهده پروفایل

استادیار

• computational neuroscience
• perceptual decision-making
• causal inference
• +۳ مورد دیگر

Ralf Haefner is an Assistant Professor in the Departments of Brain & Cognitive Sciences and Physics & Astronomy at the University of Rochester, holding this joint appointment since 2014. His interdisciplinary research bridges neuroscience and physics to investigate computational principles of perception and decision-making. Education and professional background: PhD, Oxford University, 1999 Visiting Research Fellow, Department of Neurobiology, Harvard Medical School Swartz Fellow, Sloan-Swartz Center for Theoretical Neurobiology, Brandeis University Haefner's research program centers on computational neuroscience , with primary focus on how the brain forms perceptual beliefs and uses them for decisions through Bayesian modeling . He employs machine learning tools to construct mathematical models explaining neural responses and behavior, particularly in the visual domain. His work addresses neural representation of uncertainty, causal inference mechanisms, and probabilistic computation in cortical circuits. Analysis of recent publications (2023-2025) reveals three dominant trends: (1) causal inference frameworks applied to motion perception and segmentation, (2) Bayesian modeling of perceptual biases and confidence computations, and (3) integration of generative and discriminative neural computations. His work extends beyond traditional neuroscience into scientific methodology through 'Generative Adversarial Collaborations' for improving research discourse. Honors and Awards: Swartz Fellowship, Sloan-Swartz Center for Theoretical Neurobiology NSF CAREER Award (2022) for 'Approximate inference at the intersection of neuroscience and machine learning' Haefner secured significant research funding through his NSF CAREER award, which supports foundational work on probabilistic inference at the neuroscience-ML interface. While specific students aren't listed, his active publication record and lab infrastructure suggest ongoing mentorship of graduate students and postdocs. His research has clinical relevance as shown by studies on perceptual abnormalities in autism spectrum disorder, indicating translational potential for understanding neurological conditions.

Peter Doerschukمشاهده پروفایل

استاد

• Biomedical Engineering
• Bioengineering
• Signal and Image Processing
• +۱۵ مورد دیگر

Peter Doerschuk is a Professor in the Department of Electrical and Computer Engineering at Cornell University's College of Engineering. He joined Cornell in July 2006 after serving on the faculty at Purdue University in both Electrical and Computer Engineering and Biomedical Engineering. His educational background includes: B.S. in Electrical Engineering, MIT (1977) M.S. in Electrical Engineering, MIT (1979) Ph.D. in Electrical Engineering, MIT (1985) M.D., Harvard Medical School (1987) Peter Doerschuk's research focuses on biological and medical systems through the lens of computational nonlinear stochastic systems. His work spans biomedical imaging , signal and image processing , statistical modeling , and computational inverse problems in biophysics . He develops high-performance algorithms and software systems that integrate accurate physical models with computational efficiency. His research addresses problems across multiple spatial scales—from 3D virus reconstruction using electron microscopy to modeling whole-body ethanol pharmacokinetics. The recent publications highlight a strong trend in computational biomedical imaging and physiological modeling . Key areas include 3D reconstruction of heterogeneous biological structures, cryo-EM dynamics analysis, and physiologically based pharmacokinetic modeling. The work consistently combines advanced statistical and machine learning methods with domain-specific physical models, particularly in virology and neurovascular physiology. His scientific awards and honors include: Fellow, American Institute for Medical and Biological Engineering (AIMBE) University Faculty Scholar, Purdue University Motorola Excellence in Teaching Award Ernst A. Guillemin Thesis Prize (MIT) Department of Biomedical Engineering Faculty Service Award (Purdue) Dr. Doerschuk has advised graduate students, including Keyuan Xu, whose M.Eng. thesis at MIT received the prestigious Ernst A. Guillemin Thesis Prize. His research has been supported through academic grants and collaborations with institutions such as The Scripps Research Institute and Indiana University School of Medicine. He has developed parallel software systems for high-performance computing applications in biophysics and biomedical signal processing. His research has involved collaboration with multiple labs and teams, including work with Professor J. E. Johnson at The Scripps Research Institute on virus structure determination and with Professor S. J. O’Connor at Indiana University on ethanol pharmacokinetics modeling. These interdisciplinary teams integrate expertise in engineering, medicine, and computational science to solve complex biomedical problems.

• Self-organized criticality
• Neuronal network dynamics
• Excitation/Inhibition balance
• +۵ مورد دیگر

Anna Levina is an Assistant Professor for Computational Neuroscience at the University of Tübingen , affiliated with the Department of Computer Science under the Faculty of Science. Her research focuses on the self-organization of neuronal activity, critical dynamics in neural networks, and the excitation/inhibition balance in cortical circuits. Current positions: Assistant Professor (since 2018), Group Leader (2017-2018), Equality Officer (Computer Science) Previous roles: IST Fellow (2015-2017), Associated Researcher (2011-2015), Postdoc/PI (2011-2015), Postdoc (2008-2011) Her research integrates mathematical modeling , statistical physics , and computational neuroscience to study criticality phenomena, neural avalanches, and adaptive network dynamics. Key interests include: Self-organized criticality in neural systems Excitation/Inhibition balance mechanisms Network topology and dynamics Timescale analysis in neural processing Stochastic modeling of neural activity Recent publications reveal trends in understanding critical dynamics across biological and artificial networks, with applications to memory systems, sensorimotor integration, and disease modeling. She has received recognition as an IST Fellow .

Stéphanie P. Lacourمشاهده پروفایل

استاد

• Bioelectronics
• Neuroprosthetics
• Soft Electronics
• +۹ مورد دیگر

Stéphanie P. Lacour is a Full Professor at the School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), where she holds the Foundation Bertarelli Chair in Neuroprosthetic Technology. She leads the Laboratory of Soft Bioelectronic Interfaces (LSBI) and is affiliated with multiple departments including INX-STI, STI-SMT, SV-SSV, and AVP-DLE-EDOC. Since 2025, she has served as EPFL’s Vice-President for Support to Strategic Initiatives, overseeing institutional research strategy. Her research is centered at Campus Biotech in Geneva, where she was the founding director of the Neuro-X Institute. PhD in Electrical Engineering, INSA Lyon, France (1998–2001) Postdoctoral Research, Princeton University and University of Cambridge Joined EPFL in 2011 Her research focuses on soft bioelectronic interfaces that seamlessly integrate with biological tissues. She pioneers the development of stretchable, compliant electronics for implantable and wearable applications, using techniques from MEMS and microelectronics adapted to elastomeric substrates. Her work enables long-term, minimally invasive neural interfacing for applications in neuroprosthetics, rehabilitation, and health monitoring. Key innovations include soft electrocorticography arrays, liquid metal sensors, and encapsulation methods for chronic implants. Her recent publications span high-impact journals such as Nature , Science Robotics , Advanced Materials , and Nature Nanotechnology , covering topics like neural stimulation, soft robotics, wireless implants, and hydrogel-based interfaces . The work demonstrates a strong trend toward multimodal, closed-loop, and translational neurotechnologies with real-world clinical potential. Scientific Awards: No scientific awards explicitly mentioned in the provided text. She advises a large cohort of PhD students and postdoctoral researchers, many of whom have completed their theses under her supervision. Her team has received funding for projects in neural interfacing, bioelectronics, and soft robotics. She is actively involved in teaching courses such as Soft Microsystems Processing and Devices and Neural Interfaces . Lacour leads the Laboratory of Soft Bioelectronic Interfaces (LSBI) , a multidisciplinary research team focused on the fabrication, characterization, and in vivo evaluation of soft bioelectronic systems. The lab collaborates extensively across EPFL and with clinical partners to translate technologies from bench to bedside.

Daniel Razanskyمشاهده پروفایل

استاد

• Biomedical Imaging
• Functional Imaging
• Molecular Imaging
• +۷ مورد دیگر

Daniel Razansky is a Full Professor at the Department of Information Technology and Electrical Engineering, ETH Zurich, leading the Professorship for Biomedical Imaging. His research spans engineering, physics, biology, and medicine, focusing on developing advanced in vivo imaging tools like optoacoustic tomography and ultrasound neuromodulation. His recent work emphasizes multi-scale functional and molecular imaging , with applications in neuroscience , Alzheimer’s disease , and stroke diagnostics . Collaborations include National Tsing Hua University and the EU Horizon consortium SWEEPICS. Current projects target hybrid imaging systems (e.g., MRI-MSOT) and image-guided neuromodulation. Scientific awards include the IPPA James Smith Prize for his contributions. His lab has secured significant grants, including a $2.5M NIH award and SNSF funding. He mentors PhD students like Quanyu Zhou and Eva Remlova, who have received accolades for their research. The Razansky Lab at ETH Zurich’s Preclinical Imaging Center explores medical microrobotics , dynamic fluid flow imaging , and neuroimaging techniques , aiming to bridge engineering with clinical applications.

Vibhu Sahniمشاهده پروفایل

استادیار

• Neuroscience
• Neuroregeneration
• Motor Circuit Development
• +۳ مورد دیگر

Vibhu Sahni, Ph.D., is an Assistant Professor of Neuroscience and Lab Director of the Laboratory for Cell Fate Specification and Circuit Development at the Burke Neurological Institute, an affiliate of Weill Cornell Medicine. His research focuses on understanding molecular mechanisms underlying corticospinal circuit development and regeneration, particularly after injuries like spinal cord injury or stroke. His work integrates developmental neuroscience principles to identify strategies for repairing neural circuits involved in motor control. Research interests include axon guidance, segment-specific neural circuit formation, and the molecular basis of neural regeneration decline during development. Key projects investigate how genes like Cbln1 direct axon targeting to thoraco-lumbar regions and why long-distance regenerative ability varies across spinal segments. Recent publications highlight discoveries in segmental axon targeting specificity and the dynamic loss of regenerative capacity in corticospinal neurons. His lab employs advanced techniques such as single-cell RNA sequencing, in vivo electroporation, and microsurgical lesion models to study these processes. Current grants include funding from the Craig H. Neilsen Foundation and Wings for Life Spinal Cord Research Foundation to advance molecular strategies for corticospinal circuit repair.

• Biomaterials
• Peripheral Nerve Injury
• Neuromuscular Modeling and Repair
• +۲ مورد دیگر

Suradip Das is a Research Assistant Professor in the Department of Neurosurgery at the Perelman School of Medicine, University of Pennsylvania, where he serves as a Senior Research Investigator. His work bridges neural engineering and regenerative medicine to address critical challenges in nerve and muscle repair. His academic training includes: B.Tech in Biotechnology from Heritage Institute of Technology (2010) PhD in Biosciences and Bioengineering from Indian Institute of Technology Guwahati (2016) Dr. Das specializes in biomaterials development , peripheral nerve injury models , neuromuscular interface engineering , and stem cell-based regeneration . His research pioneers innervated tissue-engineered muscle constructs, demonstrating how motor neurons and endothelial cells synergistically enhance skeletal myocyte maturation. He innovates custom mechanobioreactors that apply tensile forces to guide nanofiber alignment for optimal myofiber formation, significantly advancing volumetric muscle loss treatments. Analysis of his 15 most recent publications reveals a dominant focus on neuromuscular regeneration (75% of articles), with emerging exploration of psychedelic compounds in neural repair. His work consistently integrates human iPSC-derived models , multi-cellular co-cultures , and large-animal validation to address translational gaps. Key trends include optogenetic control of motor units (2023), porcine nerve injury models (2020), and the critical role of pre-innervation in creating pro-regenerative microenvironments (2020-2022). As a core member of the Cullen Lab, Dr. Das collaborates on developing biofabricated neural microtissues for delayed nerve fusion and rapid functional recovery. His research directly informs clinical strategies for peripheral nerve repair and muscle regeneration through rigorous mechanistic studies and innovative engineering solutions.

• Neuroimaging
• Functional Neuroimaging
• Biomedical Imaging
• +۳ مورد دیگر

Evelyn Lake is an Associate Professor in the Department of Radiology and Biomedical Imaging at Yale University, with affiliations to the Wu Tsai Institute and Yale Biomedical Imaging Institute. Her research focuses on functional neuroimaging, particularly using rodent models to study brain connectivity, neurovascular coupling, and disorders like Alzheimer’s disease and autism spectrum disorder. PhD in Medical Biophysics, University of Toronto (2016) Postdoctoral Associate, Yale University (2019) BSc (Honors) in Biophysics, University of Guelph (2010) Her work spans multimodal imaging techniques (e.g., simultaneous Ca2+ and fMRI), examining how genetic mutations (e.g., PTEN, KATNAL2) affect cerebrospinal fluid dynamics and neuronal connectivity. She investigates longitudinal changes in Alzheimer’s models and methodological aspects of animal neuroimaging, such as sample size optimization and awake imaging protocols. Recent publications highlight her contributions to understanding autism-related white matter abnormalities, transdiagnostic connectome predictive modeling, and the impact of neurovascular uncoupling in awake mice. Collaborations include Todd Constable, Francesca Mandino, Xilin Shen, and Xenophon Papademetris.

Leslie Valiantمشاهده پروفایل

استاد

• Complexity Theory
• Machine Learning
• Parallel Computation
• +۴ مورد دیگر

Leslie Valiant is the T. Jefferson Coolidge Professor of Computer Science and Applied Mathematics in Harvard University's School of Engineering and Applied Sciences, where he has held a faculty position since 1982. A foundational figure in theoretical computer science, his work bridges artificial and natural computational phenomena across multiple disciplines. His academic background includes education at: King's College, Cambridge Imperial College, London Ph.D. in Computer Science from Warwick University (1974) Valiant's research spans computational complexity , machine learning theory , parallel systems , and computational neuroscience . He pioneered the PAC (Probably Approximately Correct) learning framework that established computational learning theory as a rigorous field. His holographic algorithms work revealed deep connections between computational complexity and statistical physics, while his neuroidal model and evolvability theory provide computational explanations for cognitive processes and biological evolution. Current investigations focus on cortical computation primitives and knowledge infusion architectures. His publication trends show increasing integration of neuroscience with computational theory since 2010, with dominant themes in holographic computation (2006-2018), cortical modeling (2012-2018), and evolvability (2009-2017). The work consistently applies computational complexity analysis to biological and cognitive systems. Major recognitions include: Nevanlinna Prize (1986) for mathematical aspects of computer science Knuth Award (1997) for foundational algorithms contributions EATCS Award (2008) for theoretical computer science impact Turing Award (2010) for computational learning theory and complexity Fellowship in the Royal Society and National Academy of Sciences Valiant's research has been supported by NSF and international grants enabling cross-disciplinary work in computational neuroscience and evolutionary algorithms. While specific advisees aren't documented in source materials, his theoretical frameworks have shaped generations of researchers in machine learning and complexity theory. His current research group explores neuroidal architectures for cognitive computation, investigating how cortical circuits achieve robust information processing through in-circuit testing methodologies. Ongoing projects aim to identify fundamental computational primitives in neural systems and develop biologically inspired AI frameworks.

• Cell Biology
• Biophysics
• Mechanobiology
• +۳ مورد دیگر

Pere Roca-Cusachs Soulere is a Full Professor at the University of Barcelona and Group Leader at the Institute for Bioengineering of Catalonia (IBEC). His research focuses on understanding how cells detect and respond to mechanical signals through physical and molecular mechanisms. He holds significant roles in both academic and research institutions, including leadership in IBEC's Cellular and Molecular Mechanobiology group. Education: PhD in cellular biophysics (2007) from the University of Barcelona Medical School; postdoctoral research at Columbia University (2007–2011). Established his group at IBEC in 2012. Awards include the EMBO Young Investigator Award, City of Barcelona Award, and EBSA Young Investigator Award. Research Interests: Mechanobiology, cellular mechanotransduction, force transmission, nuclear mechanics, and integrin-mediated adhesion. His work bridges biophysics, cell biology, and engineering to study how mechanical forces influence cellular behavior and disease processes. Awards: Recognized for contributions to mechanobiology, including EMBO membership and multiple prestigious awards. His lab develops innovative tools like the MIRO chip to model tumor-immune interactions. Advising & Grants: Leads a multidisciplinary team, collaborating on projects funded by grants focusing on cell mechanics, cancer biology, and tissue engineering. His work integrates experimental and computational approaches to advance understanding of cellular force dynamics. Labs/Teams: Directs the Cellular and Molecular Mechanobiology group at IBEC, a hub for cutting-edge research on mechanosensing and mechanotransduction.

Hillel Adesnikمشاهده پروفایل

استاد

• Neuroscience
• Neural Circuits
• Optogenetics
• +۶ مورد دیگر

Dr. Hillel Adesnik is a Professor in the Department of Neuroscience at the University of California, Berkeley, and a leading researcher in the neural basis of sensory perception. His lab focuses on cortical microcircuits, optogenetics, and neural coding, with emphasis on visual processing and memory formation. Key Research Areas: Cortical Microcircuits Optogenetic Tools Gamma Band Rhythms Neural Coding Mechanisms Dr. Adesnik has pioneered high-speed optical methods like 3D-MAP and 3D-SHOT to manipulate neural activity. His work spans cortical dynamics, synaptic plasticity, and cortical layer interactions, with applications in understanding learning algorithms and sensory inference. Selected Trends from Publications: Recent preprints and papers highlight advancements in cortical VIP neuron function, channelrhodopsin structures, and inter-areal computations. His team utilizes two-photon holography, cryo-EM, and computational modeling to decode perception-related neural codes. Scientific Awards: NIH Director's New Innovator Award (2013) Dr. Adesnik's lab collaborates with institutions like NIH and develops tools for awake animal studies. Funding includes grants from the Beckman Young Investigator Program and NIH.

Istvan Modyمشاهده پروفایل

استاد

• Neuroscience
• Neurology
• Pharmacology
• +۱۲ مورد دیگر

Istvan Mody is a Professor at the University of California, Los Angeles (UCLA) with appointments in the Department of Neurology and Department of Physiology . His research focuses on synaptic signaling in health and disease, including mechanisms of GABAergic transmission, calcium homeostasis, and their roles in neurological disorders such as epilepsy, Alzheimer's disease, Huntington's disease, stress, alcoholism, and postpartum depression. He utilizes advanced techniques like patch-clamp electrophysiology, neuroanatomical and immunohistochemical methods, and molecular biology in animal models and human brain tissue . Research Interests: Dr. Mody investigates the physiology, pharmacology, and pathology of synaptic transmission and extrasynaptic receptor activation , with a particular emphasis on GABA(A) receptors and their subunit-specific modulation. His work explores how disruptions in excitation-inhibition balance contribute to neurological diseases, including mechanisms of tonic inhibition , calcium signaling , and neurosteroid interactions . He also studies the effects of chronic stress and hormonal fluctuations on neural excitability and behavior. Publications Trends: Recent studies highlight his work on gamma oscillations in Alzheimer's models, microglial dynamics , and rehabilitation strategies for stroke. His lab develops optical tools like dqGEVI for neuronal activity monitoring and investigates human brain organoids to model network dysfunction in epilepsy and intellectual disability. Laboratory Location: 635 Charles Young Dr S, Los Angeles, CA 90095, United States.

Denise Headمشاهده پروفایل

استاد

• Cognitive Aging
• Neuroimaging
• Alzheimer's Disease
• +۹ مورد دیگر

Denise Head is Professor of Psychological & Brain Sciences and Associate Chair at Washington University in St. Louis, with an additional appointment as Associate Professor in Radiology. Her research integrates cognitive neuroscience and neuroimaging to study cognitive aging and Alzheimer's disease. PhD, University of Memphis MS, University of Memphis BS, University of New Orleans Her research focuses on age-related cognitive changes and their neural underpinnings. Key areas include spatial navigation deficits in aging, the role of lifestyle factors (exercise, sleep, stress) in brain aging, and interventions to support cognitive function in older adults. She uses virtual reality, mobile eye-tracking, and neuroimaging techniques such as fMRI and DTI. The recent publications highlight a consistent trajectory in cognitive neuroscience and aging research, with emphasis on neuroimaging biomarkers, structural brain changes, and cognitive performance in normal and pathological aging. Her work bridges psychology, neurology, and radiology, contributing to early detection and understanding of Alzheimer's disease. Scientific Awards: No awards listed in the provided text. Dr. Head advises graduate students and leads a research lab focused on cognitive aging, though specific student names are not listed. Her lab investigates mediators of brain aging and develops methods to support spatial navigation in older adults. While specific grants are not mentioned, her ongoing research and recent publications suggest active external funding. She leads a research team in the Department of Psychological & Brain Sciences, utilizing advanced neuroimaging and behavioral methods to study aging and dementia. The lab integrates real-world and virtual experimental designs to understand spatial cognition and brain health in older populations.