جست‌وجوی استاد و پژوهشگر

Leonid Rubchinskyمشاهده پروفایل

دانشیار

• Computational Neuroscience
• Mathematical Biology
• Mathematical & Computational Neuroscience
• +۳ مورد دیگر

Leonid Rubchinsky is an Associate Professor in the Department of Mathematical Sciences at Indiana University–Purdue University Indianapolis (IUPUI), affiliated with the Stark Neurosciences Research Institute, Indiana University School of Medicine. His research focuses on computational neuroscience, mathematical biology, and dynamical systems applied to understanding basal ganglia function in health and Parkinson's disease. He holds academic appointments since 2004, including postdoctoral research at UC Davis (2001–2004). Education: Ph.D. in Physics (2000, Russian Academy of Sciences), M.S. in Physics (1997, UC San Diego), B.S. in Physics (1995, University of Nizhny Novgorod). Research interests include neural oscillations, synchronization mechanisms, and pathophysiological dynamics in Parkinson's disease. His work bridges mathematical modeling and experimental neuroscience to elucidate basal ganglia operations and therapeutic strategies. Publications (2008–2013) emphasize beta-band synchronization, deep brain stimulation effects, and theoretical frameworks for tremor and neural network dysfunction. Awards include IUPUI Favorite Professor recognition (2006, 2010) and international grants. Professional roles include panelist for NSF/NIH computational neuroscience grants and membership in the Organization for Computational Neuroscience Program Committee. He has organized student competitions at annual neuroscience meetings.

• Control Theory
• Neuroscience
• Dynamical Systems
• +۳ مورد دیگر

Martin Moriame is a Researcher at the University of Namur , affiliated with the Namur Institute for Complex Systems . His work focuses on applying Control Theory to study and manipulate Nonlinear Dynamics in complex systems like Kuramoto oscillators and swarmalator systems , with applications in Neuroscience (e.g., Parkinson's Disease ). Key Research Areas : Desynchronization mechanisms, Hamiltonian control, synchronization in neural networks Recent Publications (2025) demonstrate expertise in controlling synchronized dynamics in systems with higher-order interactions and swarmalators. Collaborations include work with T. Carletti , M. Lucas , and international researchers. Conference Participation : Active contributor at events like Netsci 2025 , SIAM Conference on Dynamical Systems , and organizer roles at WIVACE 2024 .

Mary E. Harringtonمشاهده پروفایل

استاد

• Circadian Rhythms
• Neuroscience
• Aging
• +۵ مورد دیگر

Mary E. Harrington is the Tippit Professor in the Life Sciences (Neuroscience) at Smith College, where she conducts groundbreaking research on circadian clocks and teaches courses in neuroanatomy, sensory systems, Alzheimer's disease, and experimental methods in neuroscience. She maintains an active laboratory that integrates undergraduate students directly into the research process, resulting in numerous student co-authorships on scientific publications. Education: Ph.D., Dalhousie University M.A., University of Toronto B.Sc., Pennsylvania State University Professor Harrington's research program focuses on understanding how circadian rhythms influence aging, neurodegenerative diseases, and overall health. Her laboratory has discovered that circadian clocks are impacted by aging but can be partially restored through exercise. Current investigations examine how light at night disrupts cellular clocks and how these disruptions contribute to Alzheimer's disease progression. She has also developed animal models for studying fatigue that have implications for multiple sclerosis research. Her publication record reveals a consistent trajectory of innovative work in chronobiology, with recent studies exploring the neurovascular unit in aging, the effects of light exposure on circadian rhythms and memory, and novel methods for detecting circadian rhythms across biological systems. She has contributed significantly to educational resources in the field, including CIRCADA, a Shiny application for circadian time series analysis with educational applications. Professional Recognition: Editor-in-Chief of the Journal of Biological Rhythms (since 2020) Tippit Professor in the Life Sciences at Smith College Author of 'The Design of Experiments in Neuroscience' (3rd edition) Professor Harrington is deeply committed to undergraduate research mentorship and educational innovation. She has developed Smith College's neuroscience major into a rigorous program where every student completes at least one year of hands-on research. Her laboratory course, Experimental Methods in Neuroscience, provides students with opportunities to conduct original research using current methodologies. She actively promotes Universal Design for Learning to increase inclusivity in science education, with 27% of neuroscience majors coming from groups underrepresented in the sciences. The Harrington Lab investigates the fundamental mechanisms by which daily rhythms shape biology, how light synchronizes internal clocks through visual pathways, and how age and disease weaken this delicate timing system. Current projects explore how exercise restores aged circadian rhythms by altering neural circuits, how chronic disruptions lead to desynchronization between brain and peripheral clocks, and how these findings could impact treatments for Alzheimer's Disease.

Frédéric Lesageمشاهده پروفایل

استاد

• Biomedical Engineering
• Neuroimaging
• Optical Imaging
• +۵ مورد دیگر

Frédéric Lesage is a Full Professor in the Department of Electrical Engineering at Polytechnique Montréal and holds a Tier 1 Canada Research Chair in Vascular Optical Imaging. His multidisciplinary research bridges biomedical engineering, neuroscience, and AI, with affiliations spanning the Functional Imaging Laboratory (INSERM), Montreal Heart Institute, and Centre for Mathematical Research. Research interests center on neuroimaging innovations for studying cerebral physiology. Key areas include: Neurovascular Coupling: Investigating blood flow dynamics in aging and Alzheimer's using optical coherence tomography and NIRS. Epilepsy Diagnostics: Developing AI models for seizure prediction via EEG/fNIRS fusion. Microvascular Pathologies: Mapping microstroke impacts using two-photon microscopy and adversarial learning. His 15 most recent publications (2020-2025) emphasize AI-driven neurology applications, showing trends in: Machine learning for epileptic EEG analysis Cerebral pulsatility in neurodegenerative diseases Translational vascular imaging (OCT/TPM) Awards include the Canada Research Chair (Tier 1) , renewed in 2022 for pioneering vascular imaging techniques. He has advised 57+ graduate students (27 PhD, 30 Master's) and secured grants from NSERC, CIHR, and CRC. Current projects focus on hypoxia effects, statin therapy in Alzheimer's, and catheter-based surgical simulators.

Jude Savarrajمشاهده پروفایل

استادیار

• Neural Engineering
• Epilepsy Research
• Neuromodulation Therapies
• +۷ مورد دیگر

Dr. Jude Savarraj is an Assistant Professor at The University of Texas Health Science Center at Houston (UTHealth Houston), affiliated with the McGovern Medical School's Department of Neurosurgery. His research focuses on neural engineering and epilepsy treatment through neuromodulation therapies, working collaboratively with clinical teams at UTHealth Houston. Dr. Savarraj earned his PhD in Biomedical Engineering from Louisiana Tech University in 2013, with a dissertation focused on neural engineering and electrical signatures associated with glioma spread. He completed postdoctoral training at UTHealth Houston from 2015 to 2018, specializing in clinical informatics. His expertise spans machine learning, big data analysis, and their applications in neuroscience and neurology. His research investigates network dynamics and neuronal responses to chronic brain stimulation, particularly Deep Brain Stimulation (DBS) for epilepsy treatment. He is currently involved in a clinical trial with Dr. Nitin Tandon on neuromodulation for seizure control, evaluating how chronic low-frequency stimulation impacts neuronal network synchronization. His work aims to develop novel approaches to desynchronize overactive brain regions to prevent seizure occurrence. Analysis of Dr. Savarraj's 40+ publications reveals a strong focus on neurological conditions including epilepsy, subarachnoid hemorrhage, and traumatic brain injury. His recent work (2022-2024) shows increasing integration of machine learning techniques with clinical neuroscience, particularly in biomarker discovery and physiological monitoring using federated learning approaches. Dr. Savarraj maintains an active research program with numerous collaborations across UTHealth Houston departments and with external institutions. His work bridges basic neuroscience with clinical applications, aiming to translate scientific discoveries into improved neuromodulation therapies for neurological disorders. His laboratory work focuses on neural engineering approaches to understand and treat epilepsy through advanced stimulation techniques. Dr. Savarraj collaborates extensively with clinicians, particularly in neurosurgery and neurocritical care, to ensure his research addresses clinically relevant questions in neurological disease treatment.