جست‌وجوی استاد و پژوهشگر

Deyou Zhengمشاهده پروفایل

استاد

• Computational Genomics
• Bioinformatics
• Gene Regulatory Networks
• +۳ مورد دیگر

Dr. Deyou Zheng is Professor in the Saul R. Korey Department of Neurology, Department of Genetics, and Dominick P. Purpura Department of Neuroscience at Albert Einstein College of Medicine. His research specializes in computational genomics and bioinformatics, analyzing high-throughput genomic data to understand genome structure, transcription regulation, and evolutionary dynamics during development and disease. Core research areas include: (1) Neural system development and neuropsychiatric disorders using iPSC-derived neurons and single-cell transcriptomics; (2) Genetic bases of congenital heart diseases; (3) Cancer genomics focusing on tumor microenvironment and immunotherapy resistance. Collaborative projects employ iPSC technology, RNA-seq, and CRISPR-Cas9 to model disorders like autism and schizophrenia. Recent publications emphasize: Single-cell integration algorithms for transcriptomic data Cancer-associated fibroblasts in glioblastoma/osteosarcoma CHD8 mutations in neurodevelopmental disorders Allele-specific expression in human brain cells

Mohammed Islamمشاهده پروفایل

استاد

• Photonics
• Optical Engineering
• Biomedical Engineering
• +۵ مورد دیگر

Mohammed Islam is a Full Tenured Professor of Electrical Engineering and Computer Science at the University of Michigan, Ann Arbor. He holds joint appointments in the Biomedical Engineering Department and the University of Michigan Medical School, Department of Internal Medicine. His research focuses on supercontinuum lasers and their applications in healthcare, defense, and photonics. He has pioneered advancements in nonlinear optics, Raman amplifiers, and fiber laser technology, with over 135 refereed publications and 145 patents. His entrepreneurial ventures include companies like Xtera Communications and Omni MedSci, commercializing technologies for telecommunications, healthcare, and national security. Key awards include the OSA Adolf Lomb Medal (1992), IEEE Fellow (2004), and the Distinguished University Innovator Award (2007). Education: B.S., M.S., and Sc.D. in Electrical Engineering from MIT (1981–1985). Professional experience includes roles at AT&T Bell Laboratories (1985–1992) and leadership in academic and industrial innovation. Research themes include non-invasive glucose monitoring, cancer tissue discrimination, and 3D printing with supercontinuum lasers. He teaches courses on photonics, entrepreneurship, and patent law. His group’s work spans biomedical applications (e.g., visceral fat ablation for diabetes treatment), defense-related active remote sensing, and high-power mid-IR supercontinuum lasers. Ongoing projects include functional near-infrared spectroscopy via nasal catheters and enhancing additive manufacturing with SWIR lasers.

Philippe Toblerمشاهده پروفایل

دانشیار

• Neuroeconomics
• Social Neuroscience
• Decision Making
• +۳ مورد دیگر

Prof. Philippe Tobler is an Associate Professor of Neuroeconomics and Social Neuroscience at the Department of Economics, University of Zurich. His research focuses on the neural mechanisms underlying decision making, reward learning, and social behavior, particularly studying brain structures like the dopaminergic midbrain, striatum, and prefrontal cortex. He employs functional magnetic resonance imaging (fMRI) and pharmacological interventions to investigate how economic reward parameters (e.g., risk, delay, probability) are processed in the brain. His work also explores individual differences in reward processing and the implications for conditions like schizophrenia and bipolar disorder. Tobler has authored numerous peer-reviewed publications, including studies on social threat learning, testosterone's impact on social behavior, and the role of neurotransmitters in decision-making processes. He collaborates with institutions like the Zurich Center for Neuroeconomics and teaches courses on decision neuroscience and neuroeconomics.

Laura Tiptonمشاهده پروفایل

استادیار

• Microbiome Analysis
• Bacterial-Fungal Interactions
• Statistical Ecology
• +۴ مورد دیگر

Laura Tipton is an Assistant Professor in the Department of Mathematics & Statistics at James Madison University (JMU), affiliated with the College of Science and Mathematics. Her research focuses on microbiome dynamics across diverse habitats such as human lungs, aerobiota, invertebrate guts, and fermented foods, emphasizing bacterial-fungal interactions and robust statistical methodologies. She integrates techniques from ecology, machine learning, and graph theory, with side projects in digital humanities, data visualization, and data feminism. Education: PhD in Computational Biology (2016), University of Pittsburgh/Carnegie Mellon University MS in Statistics (2011), George Washington University BA in Biostatistics (2007), University of Virginia Her research interests span microbiome analysis, microbial interactions, and interdisciplinary data science. Recent work includes studies on airborne fungal DNA dynamics, fungal contributions to neonatal lung diseases, and psychobiotic field developments. She emphasizes methodological innovation in microbiome studies and advocates for inclusive data practices. While no formal awards or grants are listed, her work reflects significant contributions to collaborative projects like the Global Spore Sampling Project and Pacific Innovations, Knowledge, and Opportunities (PIKO) Program. Laura’s advising focuses on mentoring students in interdisciplinary projects at the intersection of mathematics, biology, and computational science.

Nitish V. Thakorمشاهده پروفایل

استاد

• Biomedical Engineering
• Neuroengineering
• Neural Prosthetics
• +۵ مورد دیگر

Nitish V. Thakor is a Professor of Biomedical Engineering and Neurology at Johns Hopkins University School of Medicine, with secondary appointments in Electrical and Computer Engineering. He directs the Laboratory for Neuroengineering and oversees the NIH Neuroengineering Training Grant. His research focuses on neural prosthetics, brain-machine interfaces, and clinical neurorehabilitation technologies. Education: B.Tech from IIT Bombay (India), M.S. and Ph.D. in Biomedical Engineering from University of Wisconsin-Madison Joined Johns Hopkins faculty in 1983 Research emphasizes translational neuroengineering: developing prosthetic limbs with sensory feedback, advanced neural interfaces, and diagnostic technologies for brain injury monitoring. The lab integrates microfabrication, stem cell biology, and integrated circuit design with clinical applications. Notable projects include DARPA-funded advanced prosthetic systems and temperature-sensitive prosthetic fingertips. Recent lab milestones include robotic hand research published in Science Advances, and student achievements like NIH fellowships and Siebel Scholar awards. Honors: IEEE Fellow (1997), AIMBE Fellow (1996), NSF Presidential Young Investigator (1985) Advising over 20 students/postdocs, he also serves as editor-in-chief of Medical and Biological Engineering and Computing . Active in global biomedical engineering outreach through conferences and educational programs.

Hina Shaheenمشاهده پروفایل

استادیار

• Bio-statistics
• Neuroscience Data Analysis
• Computational Modelling
• +۹ مورد دیگر

Hina Shaheen is an Assistant Professor in the Department of Statistics , Faculty of Science, University of Manitoba. Her research integrates statistical methods with computational neuroscience and neurodegenerative disease modeling. Email: Hina.Shaheen@umanitoba.ca Lab: NeuroStats Lab Research Interests: Shaheen specializes in neurodegenerative disorders like Alzheimer’s and Parkinson’s disease, with a focus on: Multiscale and network modeling of brain dynamics Bio-statistical and machine learning approaches BAYESIAN inference and STOCHASTIC processes Calcium signaling and PROTEIN dynamics in disease pathology Publication Trends: Recent work combines data-driven stochastic modeling with connectomic insights to study neurodegenerative mechanisms. Key themes include: Integration of machine learning and BAYESIAN frameworks in brain network analysis Applications to Alzheimer’s (amyloid-beta/calcium interactions, exosomal spread) and Parkinson’s (DBS treatment, neural dynamics) Development of multiscale co-simulation techniques for clinical data interpretation Academic Engagement: Shaheen actively mentors graduate students and collaborates across disciplines. She participated in the V AMMCS International Conference (2019) and maintains affiliations with computational neuroscience communities.

• Computational Neuroscience
• Neural Network Simulation
• Large-Scale Simulation
• +۳ مورد دیگر

Hans Ekkehard Plesser is a Professor at the Department of Data Science, Norwegian University of Life Sciences (NMBU). His work focuses on computational neuroscience, large-scale neural network simulations, and advancing reproducibility in computational research. He is a key contributor to the NEST simulator, a widely used open-source tool for modeling spiking neural networks. His research spans theoretical and applied aspects of neuroscience, including neuron-astrocyte interactions, connectivity patterns in neural networks, and high-performance computing strategies for brain-scale simulations. He emphasizes reproducible computational practices through initiatives like the ReScience project, promoting transparency and validation in scientific software. His publications highlight advancements in simulation methodologies, algorithm optimization, and the integration of supercomputing resources for neuroscience. He has contributed to foundational work on spiking neuron dynamics, firing-rate models, and the theoretical underpinnings of neural network behavior.

Jordan J. Williamsمشاهده پروفایل

استادیار

• Neural Engineering
• Optogenetics
• Biomedical Engineering
• +۵ مورد دیگر

Jordan J. Williams is an Assistant Professor and Director of the Neural Engineering & Modulation Laboratory (NEMo Lab) at the Joint Department of Biomedical Engineering, affiliated with Marquette University and the Medical College of Wisconsin. He holds MD and PhD degrees from Washington University in St. Louis and completed postdoctoral work at the University of Pittsburgh. Education: Postdoctoral Scholar (2013-2019), Systems Neuroscience Institute, University of Pittsburgh MD (2013), Washington University in St. Louis PhD (2013), Biomedical Engineering, Washington University in St. Louis B.S. (2005), Electrical Engineering and Engineering Physics, South Dakota State University His research focuses on neural engineering, optogenetics, and brain-machine interfaces. Key projects include peripheral optogenetic stimulation for motor recovery post-spinal cord injury, neuroprosthetics, and viral gene therapy applications. Recent publications highlight advancements in spatiotemporal nerve stimulation patterns, non-human primate studies, and neural interface biocompatibility. Dr. Williams teaches courses like Neural Engineering , Biomedical Signal Processing , and Control Systems for Biomedical Engineering . His funded grants include projects on functional motor recovery and improved spinal cord injury rehabilitation through optogenetics. Current research emphasizes the intersection of neuroscience and engineering to address paralysis, with a strong focus on translating preclinical findings into clinical applications. His work has been published in journals such as Journal of Neuroscience Methods , Science Robotics , and Frontiers in Neuroscience .

Iris Sommerمشاهده پروفایل

استاد

• Neuropsychiatry
• Psychiatry
• Schizophrenia
• +۵ مورد دیگر

Prof. Iris Sommer is a Professor of Psychiatry at the University Medical Center Groningen (UMCG) and the University of Groningen. She leads the Clinical Cognitive Neuropsychiatry Research Program (CCNP) and contributes to the Biology-Related, Artificial, and Interventional Neuroscience (BRAIN) group. Her expertise spans neuropsychiatry, with a focus on hallucinations, schizophrenia, and gender disparities in mental healthcare. She is an internationally recognized researcher, having pioneered studies on female brain research, estrogen’s role in psychosis, and innovative treatments like the Stemmenpoli (Voices Clinic). Roles: Editor at Schizophrenia Bulletin, Psychological Medicine, and Lancet Psychiatry. Committee Roles: Chair of ZonMw Offroad Grants Committee, Speaker of the Speakers Academy. Research Interests: Dr. Sommer’s work addresses the origins of psychiatric disorders, particularly schizophrenia and hallucinations. Her key contributions include uncovering estrogen’s protective role in psychotic disorders and advocating for gender-sensitive psychiatric treatments. Recent projects explore gut-brain interactions, probiotics in mental health, and computational linguistics in psychosis diagnosis. Notable Findings: Female brain underrepresentation in clinical studies leads to less effective treatments for women; antipsychotics may suppress beneficial estrogens. Publications & Impact: Over 438 peer-reviewed articles, including high-impact works on hallucinations, COH-FIT pandemic mental health studies, and PET/SPECT imaging in schizophrenia. Her research emphasizes translational medicine and societal impact through public engagement. Awards: Distinguished Lorentz Fellowship (2022/23), Huibregtsenprijs (2022), NWO Science Communication Award (2024), and recognition for science communication initiatives like 'Marvelous Mind.' Labs/Teams: Leads the CCNP, collaborates globally via networks like the HAMLETT and OPHELIA consortia. Active in interdisciplinary projects linking neuroscience, AI, and clinical practice.

• Artificial Intelligence
• Machine Learning
• Medical Imaging
• +۴ مورد دیگر

Rizwan Qureshi is an active researcher and academic specializing in artificial intelligence, machine learning, and their applications in medical imaging and bioinformatics. With a robust publication record spanning from 2017 to 2025, he has established himself as a significant contributor to the fields of computer vision and biomedical AI. His research interests focus on Artificial Intelligence , Machine Learning , Medical Imaging , Computer Vision , and Biomedical Engineering . Qureshi's work demonstrates particular expertise in object detection systems (especially YOLO variants), medical image segmentation, vision-language models, and applications of AI to healthcare problems including lung cancer research and diabetic retinopathy detection. Analysis of his recent publications (2023-2025) reveals a strong trend toward medical applications of AI, with approximately 60% of his work focusing on healthcare-related problems. His research shows increasing emphasis on model robustness, explainability, and handling distribution shifts in real-world applications. The publications span top venues including IEEE Access, IEEE Transactions on Medical Imaging, CVPR, and BIBM. Qureshi maintains extensive collaborations with researchers across multiple institutions, with frequent co-authorship with Hong Yan, Tanvir Alam, Jia Wu, and Sheheryar Khan. His work demonstrates both technical depth in machine learning methodologies and practical application to significant healthcare challenges. While specific details about his academic advising are not evident from the publication record alone, his numerous publications with multiple co-authors suggest active participation in research teams and likely supervision of graduate students. His work shows consistent funding support through publication in reputable journals and conferences.

• Biomedical Signal Processing
• Computational Neuroscience
• Brain-Computer Interfaces (BCI)
• +۷ مورد دیگر

David B. Grayden is a Professor at The University of Melbourne, affiliated with the Melbourne School of Engineering and the Department of Electrical and Electronic Engineering . His work spans Biomedical Signal Processing , Computational Neuroscience , and Brain-Computer Interfaces (BCI) , focusing on applications in Epilepsy Research and Cochlear Implants . Melbourne Neural Engineering Laboratory member Collaborator in multidisciplinary biomedical research Key research interests include: Developing Seizure Prediction Algorithms using long-term EEG/iEEG data Neural mass modeling for Epilepsy and Inhibitory Network Behavior Optimizing Cochlear Implants via computational models Advancing Endovascular BCI Systems and Neural Stimulation Recent publications highlight trends in Machine Learning , Path Signatures , and Multi-Frequency Stimulation for SSVEP-based BCIs . His work integrates Computational Modeling with Biomedical Engineering to address clinical challenges in neuroprosthetics and sensory processing. Grayden leads projects on Neural Network Dynamics , Biomedical Signal Analysis , and Neurostimulation , often collaborating with institutions like Monash University and Royal Melbourne Hospital .

William Idsardiمشاهده پروفایل

استاد

• Neurolinguistics
• Phonology
• Psycholinguistics
• +۳ مورد دیگر

William Idsardi is a Professor of Linguistics at the University of Maryland, affiliated with the Program in Neuroscience and Cognitive Science and the Maryland Language Science Center. His research focuses on neurolinguistics, phonology, and psycholinguistics, combining experimental, computational, and theoretical approaches. Key areas include phonological abstraction mechanisms, the neural basis of speech perception, and the computational foundations of phonological patterning. His work bridges disciplines, investigating how phonological categories are represented in the brain using neuroimaging techniques like MEG. Notable contributions address the role of categorical perception in fricative sounds, the phoneme hypothesis, and computational complexity differences between phonology and syntax. Collaborative projects explore dialect perception, infant lexical learning, and cross-linguistic vowel systems. Publications span phonological theory, neuroimaging studies, and computational linguistics, emphasizing interdisciplinary methods. His research has implications for understanding language acquisition, speech disorders, and the evolution of linguistic structure. Labs associated with his work include the EEG/ERP Lab and Maryland Neuroimaging Center.

Duane Croninمشاهده پروفایل

استاد

• Trauma Biomechanics
• Injury Prevention
• Finite Element Modeling
• +۵ مورد دیگر

Duane Cronin is a Professor and Tier 1 Canada Research Chair in Trauma Biomechanics and Injury Prevention at the University of Waterloo. His research focuses on computational biomechanics, human body modeling, and injury prevention strategies, with applications in automotive safety, sports safety, and military protection systems. He leads a lab investigating material characterization, finite element modeling, and biomechanical testing of musculoskeletal systems. Key areas of study include neck injury mechanisms in vehicle crashes, thorax response to ballistic impacts, and spinal cord biomechanics. He develops advanced computational models validated against experimental data to predict injury risks under various loading conditions. His work integrates multidisciplinary approaches combining engineering, medicine, and computer science. Recent research trends involve refining human body models with anatomically specific geometries and advanced material properties, particularly for vulnerable populations like elderly and pediatric patients. He also explores adhesive joint mechanics in automotive materials and synthetic turf performance in sports injury mitigation. His team collaborates on projects funded by industries and government agencies, aiming to translate biomechanical insights into real-world safety improvements. Active in academic leadership, he mentors graduate students in biomechanics and hosts international symposia to advance injury prevention research.

Mujdat Cetinمشاهده پروفایل

استاد

• Computational Imaging
• Signal Processing
• Machine Learning
• +۵ مورد دیگر

Mujdat Cetin is a Professor of Electrical and Computer Engineering at the University of Rochester, serving as the Robin and Tim Wentworth Director of the Goergen Institute for Data Science and Director of the New York State Center of Excellence in Data Science. Previously, he held faculty positions at Sabanci University, Istanbul, Turkey, and MIT. He earned his BS from Bogazici University (1993), MS from the University of Salford (1995), and PhD from Boston University (2001). His research focuses on computational imaging, signal processing, and machine learning applications in biomedical imaging, radar systems, and neuroscience. Key areas include uncertainty quantification in imaging, probabilistic methods for image analysis, and brain-computer interfaces. His work bridges electrical engineering, computer science, and biomedical applications. Notable awards include the IEEE Signal Processing Society Best Paper Award and the Turkish Academy of Sciences Distinguished Young Scientist Award. He is an IEEE Fellow and has held editorial roles for journals like IEEE Transactions on Computational Imaging and SIAM Journal on Imaging Sciences. His contributions span conference leadership, including Technical Program Co-chair roles for major signal processing and fusion events. Cetin’s research group has advanced computational sensing, medical imaging algorithms, and EEG-based emotion/motor imagery classification. Ongoing work emphasizes integrating physics-based models with deep learning for robust imaging and signal analysis.

Moharram Challengerمشاهده پروفایل

استادیار

• Cyber-physical Systems
• Multi-agent Systems
• Domain-specific Modeling Languages
• +۵ مورد دیگر

Moharram Challenger is a tenure-track Assistant Professor in the Department of Computer Science at the University of Antwerp's Faculty of Sciences. Previously, he served as an assistant professor at Ege University (2017-2018) and as a post-doctoral researcher at the University of Antwerp (2019-2020) working on Flanders Make projects PACo and DTDesign. His academic journey includes R&D leadership roles at UNIT IT Ltd. (2012-2016), post-doctoral research at Wageningen University (2016-2017), and tenure-track faculty positions at IAU-Shabestar University (2005-2009). His research spans Cyber-physical Systems , Multi-agent Systems , and Domain-specific Modeling Languages , with recent publications focusing on quantum machine learning, digital twinning, and IoT optimization. Key projects include ITEA ModelWriter, ITEA Assume, and Flanders Make initiatives. His work demonstrates strong integration of model-driven engineering with emerging technologies like quantum computing and reinforcement learning. Challenger actively contributes to the academic community as a member of IEEE and ACM . His publication record shows consistent output across top venues, with 2025 featuring significant work in quantum-enhanced learning and CPS security. Current research emphasizes practical applications in drone energy modeling, medical diagnostics, and industrial IoT systems. His advising activities focus on cyber-physical systems and agent-based modeling, supported by grants from TUBITAK and Flanders Innovation & Entrepreneurship. Key collaborations include European ITEA projects and partnerships with industrial entities through UNIT IT Ltd. Challenger maintains active development through GitHub repositories related to code refactoring, model-driven engineering, and legacy system modernization, reflecting his commitment to practical software engineering solutions.