جست‌وجوی استاد و پژوهشگر

Fereydoun Hormozdiariمشاهده پروفایل

دانشیار

• Computational Genomics
• Structural Variation Discovery
• Genome Assembly
• +۳ مورد دیگر

Dr. Fereydoun Hormozdiari is an Associate Professor in the Department of Biochemistry and Molecular Medicine at the University of California, Davis School of Medicine. His research focuses on developing computational methods for analyzing genomic data, particularly in structural variation discovery, genome assembly, and disease prediction using omics data. He leads a lab that integrates machine learning and combinatorial algorithms to address challenges in understanding complex disorders like autism and cancer. Key research areas include: Structural variation discovery and genotyping using next-generation sequencing technologies. Development of novel algorithms for de novo genome assembly. Identification of genetic modules and pathways linked to neurological disorders. Prediction of complex disorders through integrated analysis of genomic and transcriptomic data. Recent work includes advancements in early-stage cancer detection using cell-free RNA biomarkers and AI, as well as tools for tumor phylogeny reconstruction and structural variant genotyping. His contributions span over 80 publications in high-impact journals like Nature, Cell, and Genome Research. Lab and team collaborations involve interdisciplinary approaches, combining computational biology with clinical applications. Ongoing projects emphasize translating genomic insights into predictive models for personalized medicine and disease intervention.

• Pharmacoepidemiology
• Epidemiology
• Observational Research
• +۹ مورد دیگر

D.L. (Daniala) Weir is an Assistant Professor at Utrecht University's Science college, specifically within the Pharmacoepidemiology and Clinical Pharmacology department. Her research bridges clinical pharmacology , epidemiology , and applied data science to enhance medication safety for patients with multimorbidity. Education: B.Sc. in Biological Sciences (University of Alberta, 2012) M.Sc. in Epidemiology (University of Alberta, 2014) Ph.D. in Epidemiology (McGill University, 2019) Postdoctoral Fellowship (University of Toronto, 2021) Her work combines causal inference frameworks with machine learning to address clinical challenges using real-world data from Canada, the UK, and the Netherlands. She collaborates across disciplines with biostatisticians , data scientists , and healthcare professionals , emphasizing patient-centered approaches through engagement with patients and caregivers. Key research areas include: Dynamic treatment regimens Medication-related harm prevention Adverse drug event detection mHealth applications for adherence Her publications demonstrate expertise in applied data science methodologies for time-to-event analysis , predictive modeling , and multimorbidity treatment optimization .

Stefano Martinianiمشاهده پروفایل

استادیار

• Computational and Statistical Physics
• Materials Science
• Artificial Intelligence for Science
• +۵ مورد دیگر

Stefano Martiniani is an Assistant Professor of Physics, Chemistry, Mathematics, and Neuroscience at New York University, affiliated with the Center for Soft Matter Research and the Simons Center for Computational Physical Chemistry. His interdisciplinary research explores computational physics of complex systems, including neural circuit theories, non-equilibrium statistical mechanics, and AI-driven materials discovery. He has pioneered methods for analyzing high-dimensional energy landscapes and received prestigious awards like the NSF CAREER Award (2024) and IUPAP Early Career Prize (2023). Education: PhD in Physics (2017), University of Cambridge MPhil in Physics (2013), University of Cambridge BSc in Physics (2012), Imperial College London Research Interests: His work bridges statistical physics and artificial intelligence, focusing on: Engineering disordered materials with tailored spectral properties Quantifying entropy production in active matter Developing open science frameworks like ColabFit for machine learning interatomic potentials Neural circuit models for cortical communication Grants & Collaborations: Funded by NSF, NIH, Chan Zuckerberg Initiative, and Simons Foundation. Leads interdisciplinary teams in computational physics, AI, and materials science. Labs/Initiatives: Core member of NYU's Center for Soft Matter Research; develops software tools like FReSCo and KLIFF-Torch for computational materials science.

• Biomedical Data Computing
• Medical Image Processing
• Image Registration
• +۴ مورد دیگر

Associate Professor Xiu Wang is affiliated with the School of Computer Science at The University of Sydney, where she serves as Associate Director of the Multimedia Lab and a member of the Biomedical & Multimedia Information Technology (BMIT) Research Group. Her research focuses on panoramic data analysis, biomedical computing, image processing, and medical data fusion. Key projects include tumor treatment outcome prediction using deep learning, collaborative learning of multimodal medical imaging, and deformable image registration techniques. She teaches courses such as COMP5214 (Software Development in Java) and supervises graduate students in AI-driven medical diagnostics and imaging. Notable collaborations involve Dr. Hui Cui and Mr. Chaojie Zheng. Her work bridges computer science and healthcare, emphasizing AI applications in oncology, radiology, and neuroimaging. Recent articles highlight advancements in MRI segmentation, PET/CT radiomics, and graph neural networks for disease diagnosis. She actively contributes to interdisciplinary research, integrating computational methods with clinical data for precision medicine.

Alfred Heroمشاهده پروفایل

استاد

• Data Science
• Statistical Machine Learning
• Distributed Optimization
• +۱۰ مورد دیگر

Alfred Hero is the John H. Holland Distinguished University Professor of Electrical Engineering and Computer Science and the R. Jamison and Betty Williams Professor of Engineering at the University of Michigan. He is currently on leave from the University of Michigan as a Program Director in the CISE Directorate at the National Science Foundation. His primary appointment is in the Department of Electrical Engineering and Computer Science (EECS) with secondary appointments in the Department of Biomedical Engineering and the Department of Statistics. He is affiliated with multiple research centers including the UM Center for Computational Medicine and Bioinformatics (CCMB), the UM Graduate Program in Applied and Interdisciplinary Mathematics (AIM), the UM Applied Physics Program, and the Michigan Institute for Data Science (MIDAS). Hero's research focuses on data science, developing theory and algorithms for multimodality data collection, fusion, analysis and visualization using statistical machine learning and distributed optimization. His work has applications in wearable technologies for personalized health and predictive medicine, spatio-temporal networks in biology, climate, and social discourse, anomaly detection, and data analysis for international security. His research group has produced numerous PhD students who have gone on to prominent academic and industry positions. His recent publications show a strong focus on high-dimensional statistical methods, machine learning theory, network analysis, and applications in biomedical domains. The research trends indicate increasing emphasis on multimodal data fusion, robust learning algorithms, and applications to complex systems in biology and security domains. His work bridges theoretical foundations with practical implementations across diverse application areas. Fellow of the Institute of Electrical and Electronics Engineers (IEEE) Fellow of the Society for Industrial and Applied Mathematics (SIAM) Fourier Award in Signal Processing from the IEEE Hero has advised numerous PhD, MS, and undergraduate students who have gone on to successful careers in academia and industry. His research has been supported by various grants, though specific grant details are not provided in the source material. His lab collaborates extensively across disciplines with researchers in statistics, biomedical engineering, and computational medicine. The Hero Research Group maintains active collaborations with institutions worldwide and participates in major conferences in machine learning, signal processing, and data science.

Sergey Timoninمشاهده پروفایل

پژوهشگر ارشد

• Population Health
• Mortality Studies
• Healthcare Access Inequalities
• +۳ مورد دیگر

Dr. Sergey Timonin is a Research Fellow at The Australian National University's School of Demography and the Centre of Epidemiology for Policy and Practice. Previously, he worked at the Higher School of Economics in Moscow and was a visiting researcher at the Max Planck Institute for Demographic Research. He holds a PhD and MSc in Human Geography from Moscow State University. Education: PhD in Human Geography, Moscow State University MSc in Geography, Moscow State University Research Interests: Focuses on population health and mortality, including spatial and socioeconomic inequalities in healthcare access, cause-of-death analysis, and ambient temperature-mortality associations. His current projects examine longevity trends in Australia and suicide risk factors among Aboriginal and Torres Strait Islander youth using nationally linked data. Articles Overview: Recent work addresses climate-related mortality patterns, pandemic impacts on longevity, and cross-national health disparities. Key themes include environmental health, demographic trends, and public health policy implications. Advising & Grants: Engages in collaborative research on mortality fluctuations, health system comparisons, and policy-relevant analyses. His work bridges epidemiology with demographic methods to address global health challenges. Labs/Teams: Active in ANU's interdisciplinary teams focusing on epidemiology, demography, and health equity research.

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.

Richard N. Landersمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Gamification
• +۵ مورد دیگر

Richard N. Landers is the John P. Campbell Distinguished Professor of Industrial-Organizational Psychology at the University of Minnesota, where he leads the TNTLAB (Testing New Technologies in Learning, Assessment and Behavior). His research focuses on applying innovative technologies—including artificial intelligence, gamification, and virtual reality—to enhance psychometric assessment, employee selection, adult learning, and research methodology in organizational contexts. He serves as associate editor for the International Journal of Selection and Assessment and holds editorial roles in several other journals. Research Interests : Integration of AI in workplace assessment, gamification of training systems, virtual reality applications, and psychometric validation of technology-driven methods Key Contributions : Development of the Work-Related Social Media Questionnaire (WSMQ) and the Cambridge Handbook of Technology and Employee Behavior His work has been published in American Psychologist , Journal of Applied Psychology , and Psychological Methods , with interdisciplinary impact in Computers in Human Behavior . He maintains industry connections through Landers Workforce Science LLC and Aon's scientific advisory board, while also creating educational tools like the Web Scraping of Psychological Data tutorial and Online Automated Statistics Tutor . Scientific Recognition : Fellow of three major psychological societies Training : Mentors Ph.D. and undergraduate students in I-O psychology and technology applications

Antony Bhavnaمشاهده پروفایل

استاد

• Deep Learning
• Medical Image Analytics
• Ophthalmic Data Analytics
• +۳ مورد دیگر

Prof. Antony Bhavna is a Professor in the Information Technology discipline at Federation University's Institute of Innovation, Science and Sustainability (IISS). Her research focuses on AI-driven medical image analytics, particularly in ophthalmology, with expertise in deep learning for disease detection and personalized prognosis. She holds a PhD from the University of Iowa and is a Senior Member of IEEE and the Association for Research in Vision & Ophthalmology (ARVO). Her work spans glaucoma diagnosis improvement, OCT image processing, and AI tools for neovascular AMD prediction. Recent projects include AutoML-based glaucoma classification and multi-modal cohort selection systems. She teaches Machine Learning & AI, emphasizing research communication. No formal awards are listed, though her active grants and collaborations with global institutions like the Charchar Lab and the University of Iowa highlight her impactful research. She advises on AI ethics in healthcare and collaborates with clinical partners for translational studies.

Omar Alamمشاهده پروفایل

دانشیار

• Software Engineering
• Model-Driven Software Engineering
• Aspect-Oriented Modelling
• +۳ مورد دیگر

Professor Omar Alam is an Associate Professor in the Department of Computer Science at Trent University. His research focuses on software engineering, particularly Model-Driven Software Engineering, Aspect-Oriented Modelling, and Mining Software Repositories. Prior to Trent, he earned his PhD at McGill University, specializing in Model-Driven Engineering. He has received notable awards such as the ACM SIGSOFT Distinguished Paper Award (2019) and the Merit Award for Excellence in Research (2022). His teaching includes courses like Software Specification (COIS 3030), Software Design and Modeling (COIS 2240), and Software Architecture (COIS 3040). Key grants include the NSERC Discovery Grant (2017-2024) and past fellowships from NSERC and FRQNT. His work spans collaborative modeling, automated grading systems, and empirical studies on developer practices. Research often intersects software development methodologies, tool integration, and socio-technical aspects of computing. His recent publications explore topics like developer workplace communication, transit schedule deviations using real-time data, and three-way domain-specific model differencing. He actively contributes to journals like SoSyM and conferences such as SLE and ICSM. His teaching excellence is recognized through student awards and nominations, reflecting his commitment to pedagogy in computer science education.

• Neuroimaging
• Pain Mechanisms
• Placebo/Nocebo Effects
• +۴ مورد دیگر

Christian Büchel is a Professor in the Department of Neurology and Experimental Neurobiology at the University Medical Center Hamburg-Eppendorf (UKE). He holds a faculty position within the Medical Faculty of Hamburg University. His research focuses on understanding brain mechanisms underlying pain, placebo/nocebo effects, and psychiatric disorders using advanced neuroimaging techniques. He leads studies on brain-body interactions, developmental neuroscience, and translational neurology. Key research areas include structural and functional MRI investigations of pain modulation, addiction, and stress responses. He has contributed to multi-center neuroimaging studies and pioneered methods for spinal cord imaging. His work integrates cognitive neuroscience principles with clinical applications, particularly in chronic pain management and mental health. Büchel's recent studies explore how environmental factors (e.g., urban green spaces) influence brain structure, and he investigates neural correlates of resilience to substance use in adolescents. He collaborates internationally on projects like the IMAGEN study and the ENIGMA consortium, emphasizing reproducibility in neuroimaging research. His publications span over 20 years, with a focus on brain network dynamics, decision-making processes, and translational neuroscience. He actively contributes to developing open-access neuroimaging standards and has authored seminal papers on placebo mechanisms and brain plasticity.

Alaa Ahmedمشاهده پروفایل

استاد

• Neuroeconomics
• Motor Control
• Decision-Making
• +۳ مورد دیگر

Alaa Ahmed is a Professor in the Department of Integrative Physiology at the University of Colorado Boulder. She holds a PhD in Biomedical Engineering from the University of Michigan (2005) and completed postdoctoral training at the University of Michigan Medical School (NIH fellowship) and the University of Cambridge (Whitaker International Fellow). Her research explores the neuroeconomic principles underlying sensorimotor decision-making, integrating neuroscience, economics, and engineering. Notable awards include the NSF CAREER Award and DARPA Young Faculty Award. Her work investigates how the brain optimizes movement costs, effort, and rewards, with implications for aging, neurological disorders, and motor adaptation. Education: PhD, Biomedical Engineering, University of Michigan (2005) Postdoctoral Fellowships: NIH, University of Michigan Medical School; Whitaker International Fellow, University of Cambridge Research Focus: Neuroeconomics of movement control, sensorimotor decision-making, metabolic cost optimization, and aging-related motor adaptations. Dr. Ahmed’s studies highlight how economic utility principles govern movement vigor and learning. Her lab uses interdisciplinary methods to quantify subjective costs (e.g., metabolic, temporal) and their impact on motor behavior. Media features include Forbes, Wired, and PBS. She explores translational applications for rehabilitation and human-machine interfaces.

Christian Bolanderمشاهده پروفایل

استادیار

• Engineering Education
• Aerodynamics
• Flight Mechanics
• +۳ مورد دیگر

Christian Bolander is an Assistant Professor in the Department of Engineering Education at Utah State University. He serves as the director of the Engineering Math Resource Center and Engineering Tutoring Center, focusing on enhancing student learning autonomy. His academic background includes a PhD in Mechanical Engineering (2023) and a BS in Mechanical and Aerospace Engineering (2018), both from Utah State University. His research emphasizes engineering mathematics education and bio-inspired flight design, with a focus on aerodynamics and aircraft control systems. He has received awards such as the Faculty Service Award (2023) and the Tau Beta Pi Fellowship (2019). Teaching responsibilities include courses like Engineering Mechanics Statics and Dynamics. He has mentored graduate student Sydney Perkins in Engineering Education. His extension work involves Engineering & STEM initiatives since 2022. Research spans bio-inspired rotating empennage designs, nonlinear aerodynamic models, and student success programs. His articles highlight contributions to both aerospace innovation and pedagogical strategies. Awards: Faculty Service Award, 2023 Tau Beta Pi Fellowship, 2019 NSF Graduate Research Fellowship Honorable Mention, 2019 Grants and service include roles in academic support and curriculum development. His work integrates engineering education with advanced aerodynamic research, aiming to bridge theoretical and practical learning in STEM fields.

Max Stallerمشاهده پروفایل

استادیار

• Transcriptional Regulation
• Gene Expression
• Intrinsically Disordered Proteins
• +۳ مورد دیگر

Max Staller is an Assistant Professor in the Department of Molecular and Cell Biology at the University of California, Berkeley, affiliated with the College of Letters & Science and the Center for Computational Biology. His lab focuses on understanding how transcriptional activation domains regulate gene expression through interdisciplinary approaches combining experimental, computational, and theoretical methods. Research Interests: Transcriptional regulation mechanisms in development and stress responses Functional analysis of intrinsically disordered protein domains Machine learning applications in protein sequence-function prediction Evolutionary dynamics of transcription factors Grants & Collaborations: Lead investigator on the NSF-funded PlantSynBio project (2021) for identifying transcriptional activation domains across plant species. Collaborates with the Cohen Lab (Washington University) on mutational scanning studies. Labs & Affiliations: Director of the Staller Lab, which integrates high-throughput experiments with computational modeling. Active in the Berkeley Bioscience community and the Center for Computational Biology.

• Electric Vehicles
• Fuzzy Logic
• Blockchain
• +۵ مورد دیگر

Shahid Hussain is an Associate Professor at King Abdullah University of Science and Technology (KAUST) in the Computer, Electrical and Mathematical Sciences and Engineering Division. His research spans multiple domains including electric vehicle infrastructure, blockchain technology, and intelligent systems for IoT applications, with a focus on practical implementations of computational intelligence techniques. Dr. Hussain's research interests include: Electric Vehicles and Smart Grid Integration Fuzzy Logic and Intelligent Decision Systems Blockchain Applications for Security and Privacy Machine Learning for IoT and Healthcare Applications Energy Management Systems Smart City Infrastructure Development His recent publications demonstrate a strong focus on applying hybrid computational approaches to solve complex engineering problems, particularly in transportation systems and healthcare applications. Dr. Hussain has published extensively in IEEE journals, with particular emphasis on innovative approaches to electric vehicle charging infrastructure, secure IoT systems, and blockchain-enabled solutions for real-world challenges. Dr. Hussain maintains active collaborations with researchers globally, particularly with Reyazur Rashid Irshad, Young-Chon Kim, and Subhasis Thakur. His work bridges theoretical advancements with practical implementations, as evidenced by his research on fuzzy integer linear programming for EV charging stations and blockchain-enabled security frameworks for medical IoT systems.