جست‌وجوی استاد و پژوهشگر

Abidemi Bolu Ajiboyeمشاهده پروفایل

استاد

• Brain-Computer Interfaces (BCI)
• Neuroprosthetics
• Spinal Cord Injury Rehabilitation
• +۵ مورد دیگر

Abidemi Bolu Ajiboye, PhD, is the Robert & Brenda Aiken Professor of Biomedical Engineering at Case Western Reserve University's Case School of Engineering. He holds key administrative roles including Faculty Director of Postdoctoral Affairs, Associate Chair, and Executive Vice Chair of the Case School of Engineering. His research focuses on developing brain-computer interface (BCI) technologies to restore motor function in individuals with spinal cord injuries and stroke. Notable projects include the ReHAB initiative, aiming to reconnect paralyzed limbs to the brain through bidirectional neuroprostheses. Education: PhD Biomedical Engineering (Northwestern University, 2008), MS Biomedical Engineering (Northwestern, 2003), BS Biomedical & Electrical Engineering (Duke University, 2000) Research interests span neural control mechanisms, FES-based systems, and clinical translation of BCI technologies. He has pioneered closed-loop systems for natural movement restoration and received VA Career Development Awards. His work integrates neuroscience with engineering to address complex rehabilitation challenges. Publications emphasize BCI system design, neural signal processing, and clinical applications. Recent efforts focus on tactile feedback restoration and addressing biocompatibility challenges in neural implants. He advises on postdoctoral training programs and contributes to interdisciplinary neural engineering initiatives through the Cleveland Neural Engineering Workshop.

• Neuroscience
• Neurophysiology
• Biophysics
• +۳ مورد دیگر

Dejan Zecevic is a Senior Research Scientist at the Department of Cellular and Molecular Physiology, Yale University School of Medicine. He holds a PhD in Biophysics from the University of Belgrade (1981) and trained under Dr. Lawrence Cohen, a pioneer of voltage-sensitive dye recording. His research focuses on intracellular voltage-sensitive dye imaging, a cutting-edge technology for studying electrical signaling in axons, dendrites, and dendritic spines. Key research interests include action potentials, synaptic integration, and membrane potential dynamics in neuronal structures. Education: PhD in Biophysics, University of Belgrade, Serbia (1981) Research Interests: Zecevic’s work centers on understanding electrophysiological properties of dendritic spines and axons using advanced imaging techniques. He developed voltage-sensitive dye methods to visualize submillisecond membrane potential changes, enabling studies of synaptic signal integration and action potential propagation. His contributions include insights into spine head electrical coupling, axonal conduction mechanisms, and stochastic aspects of dendritic signaling. Key Research Trends: Recent publications highlight his focus on holographic illumination for spine imaging, stochastic backpropagation in dendrites, and leak-resistant axonal conduction. Techniques like computer-generated holography and combined optical methods (voltage + calcium imaging) are central to his work, advancing neurophotonics and systems neuroscience. Labs/Teams: Zecevic collaborates with the Yale Neuroscience community, particularly within the Cellular & Molecular Physiology department. His lab integrates biophysics, optics, and electrophysiology to explore fundamental neuronal mechanisms.

Lasse Riis Østergaardمشاهده پروفایل

دانشیار

• Medical Imaging
• Biomedical Engineering
• Image Processing and Computer Vision
• +۴ مورد دیگر

Lasse Riis Østergaard is an Associate Professor at the Department of Health Science and Technology, Aalborg University, affiliated with The Faculty of Medicine. His research focuses on medical imaging, AI applications in healthcare, and computational methods for analyzing medical images, particularly in CT and MRI. He leads projects such as 'Modelling and quantification of the cerebral cortex' and contributes to initiatives like the Danish Centre for Health Informatics and AI for the People. Key research areas include: Medical Image Analysis: Specializing in segmentation, artifact reduction, and quantitative measurements in CT/MRI AI in Surgery: Developing deep learning models for surgical action recognition and robotic skill assessment Clinical Applications: Investigating body composition via CT, lung function correlations, and placental vascular imaging He has authored over 120 publications and supervised 5 PhD students. Notable collaborations include work with the Virtual Brain project and NemoMed. Recent studies explore ethnic differences in body composition and AI-driven surgical training. Awards: None explicitly listed, but his work has received media attention including coverage in Surgical Endoscopy and Advances in Respiratory Medicine .

Liliana Caldeiraمشاهده پروفایل

پژوهشگر

• Artificial Intelligence in Medicine
• Medical Image Analysis
• Radiology
• +۴ مورد دیگر

Dr. Liliana Caldeira serves as a Core Scientist and team leader at the Center for Data and Simulation Science (CDS) within the University Hospital of Cologne, University of Cologne. She directs innovative data science research in the Department of Diagnostic and Interventional Radiology, specializing in AI algorithm development for 3D medical imaging analysis including Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). Research Focus: Her work centers on clinical AI implementation in radiology, with expertise in deep learning for medical image segmentation (brain tumors, lymph nodes, organs), image denoising, and disease classification. Key applications include brain metastasis detection in melanoma, lymph node staging for cancer, kidney segmentation in polycystic disease, and pulmonary hypertension assessment—emphasizing clinical validation and multicenter study designs to bridge AI research with practical medical workflows. Publication Trends: Analysis of her 2020-2023 publications reveals consistent focus on clinically validated AI tools, particularly using 3D convolutional neural networks for segmentation tasks. Her research demonstrates strong collaboration across radiology subspecialties, with shared last authorship indicating principal investigator leadership in translating algorithms to clinical practice. Scientific Awards: No awards were documented in the provided text. Advising and Grants: Student mentorship and grant funding details were not specified in the source material. Labs and Teams: Dr. Caldeira leads a dedicated data science team within the radiology department, collaborating with CDS under Scientific Domain 2 (Computational Biology and Medicine). The team focuses on high-quality dataset creation, AI evaluation frameworks, and algorithm implementation for medical imaging diagnostics, operating from the University Hospital campus at Kerpener Str. 62.

Stuart Coganمشاهده پروفایل

استاد

• Bioengineering
• Neural Interfaces
• Materials Science
• +۳ مورد دیگر

Stuart Cogan is a Professor in the Department of Bioengineering at the University of Texas at Dallas (UT Dallas), affiliated with the Erik Jonsson School of Engineering and Computer Science. He leads the Neural Interfaces Lab, focusing on materials and devices for chronic neural stimulation and recording. His research emphasizes implantable electrode stability, electrochemical characterization, and minimizing tissue damage. Education: ScD in Materials Science (MIT, 1979), MS in Materials Science (Duke, 1977), BS in Mechanical Engineering (Duke, 1975). Research interests include neural prosthetics, thin-film electrode fabrication, and long-term implant performance. Key innovations involve amorphous silicon carbide coatings and flexible microelectrode arrays. Recent work explores electrode materials for chronic use, including iridium oxide and ruthenium oxide, and evaluates their electrochemical stability under stimulation. Studies address mechanical insertion mechanics, parasitic capacitance in arrays, and wireless stimulation systems for peripheral nerves. Publications span neural interface design, in vivo testing, and material degradation analysis. His lab’s advancements aim to improve chronic implant longevity and therapeutic efficacy in neural prosthetics and neuromodulation therapies.

• Neuroscience
• Neurobiology
• Sensory Systems
• +۳ مورد دیگر

Gizem Sancer is a Postdoctoral Associate in Neuroscience at the Yale School of Medicine, Yale University. Her research focuses on understanding neural circuits underlying sensory processing in Drosophila, particularly visual navigation and olfactory systems. She investigates how neurons process skylight polarization for orientation and odor tracking, combining experimental and computational approaches. Key research areas include the development of thalamic organoids to model human brain structures and the functional architecture of visual systems. Her work bridges neurobiology, developmental biology, and systems neuroscience, with a focus on interdisciplinary methods like connectomics and organoid engineering. Recent publications highlight advancements in mapping neuronal wiring diagrams, analyzing olfactory sensory neuron dynamics, and generating thalamic organoids. Collaborators include prominent neuroscientists such as Ferdi Kiral, In-Hyun Park, and James Jeanne. No awards are explicitly listed, but her contributions span multiple high-impact journals including Nature and Cell Stem Cell.

Jodie Plumertمشاهده پروفایل

استاد

• Developmental Science
• Developmental Psychopathology
• Perceptual-Motor Development
• +۵ مورد دیگر

Jodie Plumert is a Professor at the University of Iowa, holding the Russell B. Day and Florence D. Day Chair. She is affiliated with the Department of Psychological and Brain Sciences and leads the Hank Virtual Environments Laboratory (Perceiving, Acting, & Thinking Lab). Her research spans developmental science, cognitive psychology, and clinical science, with a focus on perceptual-motor development, childhood injury prevention, and parent-child communication. Plumert's research explores how children and adults perceive and act in virtual environments, examining risk-taking behaviors, spatial memory, and executive function. She investigates developmental disorders through studies on ADHD symptoms and their impact on movement and decision-making. Her work integrates technology like virtual reality to model human-agent interactions and assess perception-action tuning. Her publications reveal consistent application of VR to study developmental psychopathology and cognitive control. Key themes include road-crossing safety, motor timing, and collaborative behavior in virtual settings. Her laboratory addresses temperament and learning mechanisms in applied contexts. Plumert earned her Ph.D. from the University of Minnesota in 1990. She maintains dual office and lab addresses at the Psychological and Brain Sciences Building (PBSB) in Iowa City, IA, with active phone lines at both locations.

Dora Hermes Millerمشاهده پروفایل

دانشیار

• Neuroscience
• Biomedical Engineering
• Neurology
• +۷ مورد دیگر

Dora Hermes Miller is an Associate Professor of Biomedical Engineering and holds Senior Associate Consultant II-Research roles in the Departments of Physiology & Biomedical Engineering, Radiology, and Neurology at Mayo Clinic. Her research focuses on human systems neuroscience, integrating multimodal imaging and computational modeling to understand neural signals in neurological and neuropsychiatric diseases. She collaborates with clinicians to develop therapeutic neuromodulation technologies and neuroprosthetics. Education includes a PhD from Utrecht University (Brain Center Rudolf Magnus) and postdoctoral fellowships at Stanford University, New York University, and UMC Utrecht. Her work emphasizes reproducible research practices, with contributions to neuroimaging standards like BIDS-iEEG and open source tools for electrode localization. Research interests span multimodal imaging integration, network dynamics via electrical stimulation, neural oscillations, and translational applications of brain-machine interfaces. Her lab explores how electrical stimulation modulates human connectomes, with implications for epilepsy treatment and psychiatric conditions. Collaborative efforts bridge clinical neurology, neurosurgery, and computational neuroscience. Awards and recognitions are not explicitly listed in the provided text. Her work has advanced understanding of somatotopic motor representations, limbic circuit modulation, and cortical stimulation effects, with over 70 peer-reviewed publications in journals like NeuroImage and Brain. Current projects include developing closed-loop neuromodulation systems, optimizing ECoG/MEG-fMRI integration, and advancing ethical brain-computer interface applications. She leads the Mayo Clinic NeuroEngineering Lab and participates in collaborative initiatives to standardize neuroelectrophysiological data sharing.

Reza Abiriمشاهده پروفایل

استادیار

• Robotics
• Artificial Intelligence
• Brain Machine Interfaces
• +۶ مورد دیگر

Dr. Reza Abiri is an Assistant Professor in the Department of Electrical, Computer and Biomedical Engineering at the University of Rhode Island's College of Engineering. His research focuses on translational neurorobotics, combining biosignal control systems with AI-enabled medical robotics to address neurorehabilitation challenges. He leads the Translational Neurorobotics Laboratory (TN Lab), established in Fall 2021 with NSF CAREER 2025 funding. Education: Postdoctoral Fellow, University of California, San Francisco and UC Berkeley (2021) Ph.D., Mechanical Engineering, University of Tennessee (2017) M.Sc., Mechanical Engineering, Amirkabir University of Technology, Iran (2011) B.Sc., Mechanical Engineering, K.N. Toosi University of Technology, Iran (2009) Dr. Abiri's research spans multiple disciplines including robotics, artificial intelligence, brain-machine interfaces, and biomedical engineering. His work addresses critical challenges in decoding neural activity for motor control, developing novel actuation mechanisms, and enhancing neurorehabilitation technologies through advanced signal processing and AI integration. Recent publications demonstrate a strong focus on brain-computer interfaces, attention training, and robotic rehabilitation systems. Key topics include EEG signal analysis, shared autonomy algorithms, multimodal AI frameworks, and magnetic actuation technologies. These works reveal a consistent pattern of innovation in connecting neural signals with robotic control systems. Scientific Recognition: NSF CAREER Award (2025) Dr. Abiri's TN Lab develops computational methods to overcome translational barriers in neurorehabilitation and motor control restoration. The lab's work integrates machine learning with biosignal processing to create advanced human-machine interaction systems, particularly focusing on noninvasive neural interfaces and their practical applications in healthcare robotics.

• Neuroimaging
• Neuroinformatics
• MRI-based morphometric analysis
• +۷ مورد دیگر

David N. Kennedy is a Professor at UMass Chan Medical School, affiliated with the T.H. Chan School of Medicine. He holds appointments in the Departments of Psychiatry and Behavioral Sciences, Radiology, NeuroNexus Institute, and Eunice Kennedy Shriver Center. He also contributes to the MD/PhD Program and Neuroscience Department at the Morningside Graduate School of Biomedical Sciences. PhD in Nuclear Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States Dr. Kennedy is a leading expert in neuroimaging and neuroinformatics, with foundational contributions to MRI-based morphometric analysis, functional MRI, and diffusion tensor imaging. His research focuses on developing neuroinformatics tools and resources, including the Internet Brain Volumetric Database and the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC). He co-founded the Center for Morphometric Analysis at Massachusetts General Hospital and has been instrumental in advancing data sharing, reproducibility, and standardization in neuroscience. His recent publications emphasize FAIR data principles, neuroimaging data models, open-source tools like DataLad and HeuDiConv, and collaborative frameworks for neuroscience. These works reflect a strong trajectory toward enhancing data interoperability, transparency, and community-driven standards in neuroimaging research. Community liaison for the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) Co-PI of the morphometry Biomedical Informatics Research Network (mBIRN) Founding editor of the journal Neuroinformatics Dr. Kennedy has not listed specific grants or advising roles in the provided text but plays a central role in major neuroinformatics initiatives. He has no listed scientific awards in the provided materials. He is a key figure in the development and dissemination of neuroimaging informatics resources, contributing to national and international efforts to standardize and share neuroscience data through platforms like NITRC and mBIRN.

• Medical Imaging
• Neuroimaging
• MRI Reconstruction
• +۲ مورد دیگر

Stefan Sunaert is a Professor at KU Leuven's Faculty of Medicine within the Department of Imaging & Pathology. He serves as Head of Radiology and Head of the Division of Medical Imaging (Divisie Medische Beeldvorming), while also holding membership in the LBI - KU Leuven Brain Institute. His institutional roles include senior academic staff positions on the Council of the Faculty of Medicine, Council of the Department of Imaging & Pathology, and Board of the Department of Imaging & Pathology. His research focuses on advanced neuroimaging applications, particularly in MRI reconstruction, brain connectivity analysis, and clinical translation across neurology, oncology, and psychiatry. Key methodologies include diffusion MRI, functional MRI, and multimodal imaging integration for studying conditions ranging from brain tumors to neurodegenerative diseases and psychiatric disorders. Analysis of his 2025 publications reveals a strong emphasis on translational neuroimaging, with recurring themes in brain network analysis (structural/functional connectivity), radiation therapy effects on neural systems, and advanced MRI techniques for clinical applications. His work spans diverse populations including glioma patients, aging adults, children with cerebral palsy, and early Alzheimer's cases. As active promotor or co-promotor on ten major research projects (2023-2029), he leads investigations into neurosurgical planning with dynamic MRI, epilepsy imaging, diabetes-related brain changes, pediatric brain tumor radiotherapy, and neurocognitive decline prediction. These projects demonstrate significant grant acquisition capacity and interdisciplinary collaboration. He leads the Translational MRI unit at UZ Herestraat 49 (box 7003, Leuven) and teaches medical imaging courses including 'Medical Imaging for Physiotherapists' and multiple problem-solving modules in radiology. His ORCID profile (0000-0002-1177-4680) documents extensive publication output in high-impact journals.

• Translational Genomics
• Statistical Genetics
• Computational Genomics
• +۴ مورد دیگر

Eleftheria Zeggini serves as Director of the Institute of Translational Genomics at Helmholtz Munich and holds the Liesel Beckmann Distinguished Professorship and Chair of Translational Genomics at the Technical University of Munich (TUM) School of Medicine. Her research leverages big data in genetics and genomics to translate genomic insights into disease mechanisms, advancing precision medicine through robust statistical and computational approaches integrating multi-omics data, electronic health records, and diverse population studies. Her educational background includes a PhD in Immunogenetics of Juvenile Arthritis from the University of Manchester School of Medicine (2003) and a Bachelor of Science (Hons) in Biochemistry from the University of Manchester Institute of Science and Technology (1999). Prior appointments include Group Leader at the Wellcome Sanger Institute (2008-2018) and Wellcome Research Career Development Fellow at the University of Oxford (2006-2008). Zeggini's research spans translational genomics, statistical genetics, and computational biology with emphasis on genetic architecture of complex diseases. Her team develops tools for multi-omics integration to dissect sequence variation in human health, focusing on osteoarthritis, type 2 diabetes, and cardiometabolic disorders. Recent work prioritizes health equity through tissue-specific multi-ancestry genomic studies and electronic health record integration, driving discovery of novel therapeutic targets and disease mechanisms. Analysis of her 15 most recent publications reveals dominant themes in osteoarthritis genomics (6 articles), type 2 diabetes heterogeneity (3 articles), and multi-ancestry genomic equity (3 articles). Her work consistently employs whole-genome sequencing, causal inference methods, and large-scale biobank analyses across diverse populations, with strong translational focus on precision medicine applications. Major scientific recognition includes: Elected Member of Academia Europaea (2024) Greek Excellence Award (2024) National Representative to the EMBL Council (2022) Elected Fellow of the Academy of Medical Sciences, UK (2020) Argo Award for Distinguished Greeks Abroad (2020) Honorary Senior Fellow, University of Cambridge (2018) Honorary Professor, University of Bristol (2018) Zeggini actively mentors early-career researchers while promoting diversity and inclusion in science. Her leadership in major consortia like UK Biobank analyses and ENABLE program demonstrates sustained grant acquisition capability. Current research direction focuses on developing computational frameworks for next-generation translational genomics, with particular emphasis on addressing health disparities through equitable genomic data representation. She directs Helmholtz Munich's Institute of Translational Genomics, which houses a multidisciplinary team of computational biologists, geneticists, and clinicians developing statistical tools for big data integration. The institute serves as a hub for precision medicine innovation, collaborating with TUM's medical faculty and international networks to accelerate genomic discoveries into clinical applications.

Lauren N. Rossمشاهده پروفایل

استاد

• Causal Explanation
• Philosophy of Science
• Neuroscience
• +۵ مورد دیگر

Lauren N. Ross is a Professor and Chancellor's Fellow in the Department of Logic and Philosophy of Science at the University of California, Irvine . She holds a Ph.D. in History and Philosophy of Science from the University of Pittsburgh, an M.A. in Bioethics from the University of Pittsburgh, and an M.D. from UC Irvine. Her research is supported by prestigious awards including the NSF CAREER award , John Templeton Foundation Grant , and Humboldt Experienced Researcher Fellowship . Education: Ph.D., History and Philosophy of Science, University of Pittsburgh M.A., Bioethics, University of Pittsburgh M.D., University of California, Irvine Research Focus: Explanation and causation in biology, neuroscience, and medicine Interdisciplinary analysis of causal structures and mechanisms Causal diversity in scientific reasoning Scientific Awards: NSF CAREER Award John Templeton Foundation Grant Humboldt Experienced Researcher Fellowship Her recent publications emphasize distinctions between mechanism and cascade models, causal constraints , and topological vs. causal explanation in neuroscience. She explores how these concepts shape understanding of brain function, psychiatric genetics, and social structural causes. Her work bridges philosophy of science with empirical neuroscience to refine causal reasoning frameworks. Key presentations include Human Brain Project Summit 2023 , Giere Distinguished Lecture 2022 , and international workshops in France, the Netherlands, and Canada. She serves as a peer reviewer for journals like Nature Reviews Neuroscience and Stanford Encyclopedia of Philosophy .

Mike Nichollsمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Laterality
• Spatial Attention
• +۱۲ مورد دیگر

Professor Mike Nicholls is a full-time faculty member at Flinders University, holding a Strategic Professorship in Psychology within the College of Education, Psychology and Social Work. He is Director of the Brain and Cognition Laboratory and currently serves as Dean of Research for his college. Previously, he was a professor at the University of Melbourne for 17 years. His educational background includes a BArchSt from the University of Adelaide (1985–1987), a BA (Hons) in Psychology from the University of Adelaide (1998), and a PhD in Experimental Psychology from King’s College, Cambridge (1990–1993), funded by a Cambridge Commonwealth Trust scholarship. Mike Nicholls’ research is centered on cognitive neuroscience, particularly the study of behavioral and perceptual asymmetries related to brain lateralization. His work investigates handedness, spatial attention in clinical and healthy populations, language, facial expression perception, and the role of eye movements. He explores how attention is controlled by the brain across sensory modalities and spatial dimensions. His recent publications reveal a strong focus on how social context influences perception, body image, facial judgments, and attentional processes, often employing neuroimaging and psychophysical methods. His 15 most recent articles (2023–1996) span topics including inattentional blindness, social modulation of visual perception, reinforcement learning in visual cortex, and attentional distortions in spatial cognition. These works reflect a consistent interest in the neural and cognitive underpinnings of lateralized behavior and attention, with applications in both healthy and clinical populations. Scientific Awards: Outstanding Academic Mentor Award, Australian Psychological Society (2020) Mike Nicholls has supervised numerous research students and PhD candidates, with advising interests in laterality, attention, and cognitive neuroscience. He has secured substantial research funding, including multiple ARC Discovery and Linkage Grants, with recent projects focusing on decision aids in complex environments, augmented reality for defense, and attentional asymmetries in navigation. He has also held editorial roles in journals such as Laterality and the Quarterly Journal of Experimental Psychology , and currently serves on the ARC's Medical Research Advisory Group. He leads the Brain and Cognition Laboratory at Flinders University, a research team dedicated to understanding cognitive processes and their neural representations, particularly in the context of brain asymmetry and attentional control.

Shusen Puمشاهده پروفایل

استادیار

• Computational Neuroscience
• Mathematical Biology
• Mathematical Statistics
• +۷ مورد دیگر

Dr. Shusen Pu is an Assistant Professor in the Department of Mathematics and Statistics at the University of West Florida (UWF) , within the Hal Marcus College of Science and Engineering . He joined UWF in 2022 after serving as a Lecturer at Vanderbilt University. His academic journey includes a Ph.D. in Applied Mathematics from Case Western Reserve University (2020), advised by Dr. Peter J. Thomas, and postdoctoral research with Dr. Christos Constantinidis. Dr. Pu's educational background includes: Ph.D. in Applied Mathematics, Case Western Reserve University B.S. in Mathematics and Statistics, Beijing Normal University His research spans computational neuroscience , mathematical statistics , data analytics , and deep learning . He investigates neural network models, working memory, stochastic processes in biological systems, and generalized statistical distributions. He collaborates with biologists to analyze experimental data and integrates deep learning into neuroscience applications. His work aims to bridge microscopic neural activities with macroscopic behaviors. His recent publications (2024–2018) reflect a strong focus on both neuroscience modeling and statistical distribution theory . Articles in journals like Nature Communications , Entropy , and Biological Cybernetics demonstrate expertise in prefrontal neuronal dynamics, neural noise modeling, and novel distribution generators. The consistency in topics indicates a dual research thrust: understanding brain function through computational models and advancing statistical tools for real-world data analysis. Scientific contributions include: Published in high-impact journals such as Nature Communications , Neural Computation , Eneuro , and Biological Cybernetics Reviewer for multidisciplinary journals including iScience (Cell Press) Active participant and presenter at international conferences in Canada, China, and the USA Organizer of academic conference sessions and workshops Dr. Pu is deeply involved in academic mentoring and teaching. He advises students in capstone projects integrating mathematical modeling, data science, and statistical analysis. He teaches courses such as Analytic Geometry and Calculus, Linear Algebra, Deep Learning, and Mathematical Statistics. He emphasizes problem-solving methodology, collaborative learning, and real-world applications. He leads the Computational Statistics and Data Analytics (CSDA) Lab , hosting weekly lab meetings and Python/data science tutorials, fostering a collaborative research environment. His lab and team activities include: Weekly lab meetings (Fridays 9:00–10:00, Building 4, Room 212) Weekly Python and Data Science Tutorials (Fridays 10:00–11:00, same location) Supervision of capstone projects in data science and mathematical modeling Active research in neural connectivity inference and statistical distribution development