جست‌وجوی استاد و پژوهشگر

Zhenyu Kongمشاهده پروفایل

استاد

• Manufacturing Systems Engineering
• Machine Learning for Manufacturing
• Cyber-Physical Systems
• +۵ مورد دیگر

Zhenyu "James" Kong is the Ralph H. Bogle Professor in the Department of Industrial and Systems Engineering at Virginia Tech's College of Engineering. With over 20 years of academic experience, he has established himself as a leading researcher in manufacturing systems engineering with a focus on smart manufacturing technologies. Dr. Kong received his Ph.D. in Industrial and Systems Engineering from the University of Wisconsin-Madison in 2004, following Master's and Bachelor's degrees in Mechanical Engineering from Harbin Institute of Technology in China. His academic career includes professorial positions at Virginia Tech since 2006 and previously at Oklahoma State University. His research focuses on the intersection of machine learning, cyber-physical systems, and manufacturing engineering. Specifically, he investigates real-time sensing, advanced analytics, and process monitoring/control for smart manufacturing systems. His work on modeling, synthesis, and diagnosis for large and complex manufacturing systems has significantly advanced the field of additive manufacturing quality control, with particular emphasis on applying deep learning techniques to defect detection and process optimization. Dr. Kong's research has been supported by major funding agencies including the Department of Defense, National Science Foundation, Department of Energy, and Office of Naval Research. His publications demonstrate a consistent focus on applying machine learning to solve practical manufacturing challenges, particularly in additive manufacturing quality control and process monitoring. Fellow of Institute of Industrial and Systems Engineers (IISE), 2020 Dean's Award for Excellence in Research, College of Engineering, Virginia Tech, 2019 Multiple Best Paper Awards from IISE Transactions and INFORMS conferences (2015-2020) APM Outstanding Faculty Award, Virginia Tech, 2018 Halliburton Outstanding Faculty Award, Oklahoma State University, 2013 As an educator, Dr. Kong has taught courses including Advanced Topics in Manufacturing Systems Engineering, Sensing and Data Analytics for Complex Systems, and Statistical Quality Control. He leads the SMART Lab at Virginia Tech, where his research group develops innovative solutions for manufacturing challenges using cutting-edge data analytics and machine learning techniques. His research has been featured multiple times in ISE Magazine, highlighting its practical significance and impact on manufacturing industry practices.

Felipe Menanteauمشاهده پروفایل

عضو هیئت علمی

• Cosmology
• Galaxy Clusters
• Dark Energy Survey
• +۶ مورد دیگر

Felipe Menanteau is a Research Associate Professor in the Department of Astronomy at the University of Illinois and a Senior Research Scientist at the National Center for Supercomputing Applications (NCSA). His primary affiliations include collaborations with the Dark Energy Survey (DES), South Pole Telescope (SPT), and Atacama Cosmology Telescope (ACT) projects. His research focuses on cosmology, galaxy clusters, and the Cosmic Microwave Background (CMB). Key areas include weak lensing, CMB lensing, galaxy cluster mass calibration, and the study of large-scale structure. He contributes to major observational efforts such as the SPT-3G polarization measurements and DES galaxy cluster surveys. Recent work emphasizes cosmological constraints from CMB data, interplay between dark matter and baryonic physics, and high-precision measurements of the Hubble constant. His articles explore topics like supernova calibration, polarization foreground modeling, and cross-correlation analyses between surveys. Menanteau has co-authored over 400 publications and collaborates internationally with institutions like Fermilab, NASA, and European observatories. His research bridges observational cosmology with theoretical models to address fundamental questions about structure formation and dark sector physics.

• Machine Learning
• Predictive Analytics
• Time Series Analysis
• +۵ مورد دیگر

Nurilla Avazov is an Associate Professor of Data Science at the Inland School of Business and Social Sciences, Inland Norway University of Applied Sciences. He holds dual PhDs: a PhD in Computer Science (2021) from the University of Auckland and a PhD in Information and Communication Technology (2015) from the University of Agder. His research focuses on machine learning, predictive analytics, time series analysis, wireless communication modeling, IoT systems, e-healthcare solutions, and human activity recognition through advanced signal processing techniques. Dr. Avazov’s academic career includes significant contributions to high-impact refereed journals and conferences. His work spans theoretical developments in algorithm design, practical implementations in sensor networks, and interdisciplinary applications in healthcare and smart environments. He has developed novel trajectory-driven channel models for mm-wave systems and pioneered backscattering-based human activity recognition methods. His expertise combines data science with telecommunications engineering, addressing challenges in non-stationary channel analysis, radar systems for indoor localization, and cybersecurity through wireless signal inference. Current research trends emphasize multimodal sensor fusion, real-time activity tracking, and privacy-aware IoT architectures. Dr. Avazov has advised no formally recorded students in the provided data. His research grants and funded projects are not explicitly detailed here, though his publications indicate sustained external collaboration and funding support. He is affiliated with the Business Analytics research group at his institution.

• Human Genetics
• Neurological Disorders
• Neuroscience
• +۳ مورد دیگر

Dr. Susan Byrne is a Senior Lecturer in Paediatrics and Child Health at the Royal College of Surgeons in Ireland (RCSI), affiliated with FutureNeuro and the Department of Paediatrics. She holds a dual role as a Consultant Paediatric Neurologist at Children's Health Ireland. Her academic qualifications include an MB BAO BCh from Trinity College Dublin (1999–2005), a PhD in Neuroscience (2009–2012), and a Diploma in Statistics (2009–2011). Professional certifications include CCST (2016), MRCPI (2008), and MRCPCH (2013). Her research focuses on neurogenetics, neurological disorders in childhood, and genotype-phenotype correlations. Key areas include epidemiological studies of pediatric movement disorders, pandemic impacts on child development, and genetic mechanisms of neurodegenerative diseases. She contributes to the RCPCH Stroke in Childhood Guidelines and collaborates on initiatives like the CORAL birth cohort study. Dr. Byrne’s work spans over 100 publications, emphasizing pediatric neurology, pandemic-related health effects, and clinical education. She actively participates in FutureNeuro, a research center addressing neurological challenges.

Gary Holnessمشاهده پروفایل

دانشیار

• Machine Learning
• Robotics
• Ensemble Methods
• +۴ مورد دیگر

Gary Holness is an Associate Professor of Computer Science at Clark University, where he directs the Laboratory for Intelligent Perceptual Systems (LIPS). He holds a PhD in Computer Science from the University of Massachusetts Amherst (2008) focusing on machine learning ensembles, robotics, and distributed systems. Research spans: Machine learning ensembles and error diversity Robotic perception and autonomous systems Nonparametric density estimation Human-robot interaction for autism therapy Distributed frameworks for medical alerting Interactive AI with manifold learning His publications show progression from theoretical machine learning to applied systems, with recent work on spectroscopic analysis and kernel methods. Maintains active student research programs in robotics, GPU acceleration, and terrain classification.

• Developmental Psychology
• Clinical Psychology
• Neuroscience
• +۵ مورد دیگر

Dr. Liat Levita is a Reader in Behavioural and Clinical Neuroscience at the University of Sussex's School of Psychology. She leads the Developmental Affective Neuroscience lab, focusing on adolescent development, mental health, and the impact of early life stress using neuroimaging (EEG/fMRI) and psychophysiological methods. Her work bridges basic neuroscience with translational mental health interventions. She holds honorary roles at the University of Sheffield and serves on the editorial board of Journal of Child & Adolescent Trauma . Education: PhD (University of Cambridge), BSc Neuroscience (University of St Andrews) Postdoctoral training: Weill Cornell Medical College, Columbia University, Emory University Research interests include: Adolescent brain development and its vulnerability/resilience mechanisms Neural correlates of threat and reward processing Longitudinal mental health studies during the pandemic (C19PRC Consortium) Recent work emphasizes pandemic's heterogeneous mental health impacts and resilience trajectories, with over 120 peer-reviewed publications. Current grants include an Innovate UK-funded digital mental health intervention (UpliftX).

• Network Analysis
• Social Networks
• Data Mining
• +۶ مورد دیگر

Michele Coscia is an Associate Professor in the Department of Data Science at the IT University of Copenhagen. He also serves as the Head of Programme for the BSc in Data Science. His research focuses on network analysis, social networks, data mining, and their applications in understanding human mobility, complex systems, economic development, and memetics. He has contributed to projects such as the Pioneer Centre for Artificial Intelligence and leads initiatives like ROMNET (Past social network reconstruction from material culture data) and Work2Vec (exploring deep learning in healthcare and work hours analysis). His research interests encompass interdisciplinary network science, including misinformation dynamics, ideological polarization, and the impact of social media systems. He has developed methodologies like the generalized Euclidean measure for multilayer networks and explored cultural data analytics through case studies like Italian music history. His work also addresses real-world challenges, such as quantifying the effects of violence on migration patterns and optimizing network sampling strategies for cost efficiency. Michele Coscia has received the Årets Forskningsmiljø 2022 award, recognizing his contributions to fostering outstanding research environments. He actively engages with media, discussing topics like misinformation and data visualization. As a principal investigator, he oversees projects funded by institutions such as the Villum Foundation and Danish National Research Foundation. His research spans academic collaborations across countries, reflecting his global network and commitment to advancing network theory and its applications.

• Data Privacy
• Mobile Applications
• Web Analytics
• +۴ مورد دیگر

George Prezerakos is a Professor at the Department of Electrical and Computer Engineering, National Technical University of Athens. His work focuses on data privacy, mobile applications, web analytics, and network engineering. He holds the email prezerak@uniwa.gr . Research interests include analyzing the societal impact of digital technologies, predicting human behavior through web data, evaluating market competition policies in telecommunications, and addressing the digital divide exacerbated by economic crises. He has published extensively on topics ranging from secure distributed systems to context-aware service engineering. His research demonstrates a unique blend of technical innovation and socio-economic analysis. For example, his work on predicting election outcomes via Google Trends data bridges computational methods with political science, while studies on mobile app privacy critique modern digital economy practices. He also investigates infrastructure challenges in deploying next-generation networks in complex geographic regions like Greece. Advising and grants: No specific advising or grant details are provided in the text. His contributions are primarily through academic publications and conference presentations. Labs/Teams: Affiliated with the Department's research groups focusing on telecommunications, cybersecurity, and context-aware systems, though specific lab names are not mentioned.

• Gravitational-Wave Astronomy
• Cosmology
• Black Holes
• +۳ مورد دیگر

Maya Fishbach is an Assistant Professor at the Canadian Institute for Theoretical Astrophysics (CITA), University of Toronto. Her research focuses on gravitational-wave astronomy, cosmology, and the astrophysics of compact objects like black holes and neutron stars. She utilizes data from gravitational-wave observatories such as LIGO, Virgo, and KAGRA to study binary systems, stellar evolution, and cosmic phenomena. Her work integrates astrostatistics and computational methods to analyze gravitational-wave signals, constrain cosmological parameters, and explore the origins of compact binaries. Fishbach collaborates on projects involving multi-messenger astronomy, linking gravitational-wave observations with electromagnetic counterparts and theoretical models. Recent research highlights include studies of black hole spin dynamics, hierarchical mergers, and the connection between binary black holes and globular clusters. She contributes to open-source tools like tBilby for gravitational-wave data analysis and actively participates in observational campaigns to detect transient events. Her academic affiliations include the CITA community and collaborations with international gravitational-wave detector networks. Fishbach’s research spans theoretical astrophysics, observational cosmology, and computational methods, making significant contributions to understanding the dynamic universe through gravitational waves.

Vivienne Baldassareمشاهده پروفایل

استادیار

• Astrophysics
• Galactic Dynamics
• Black Hole Physics
• +۳ مورد دیگر

Vivienne Baldassare is an Assistant Professor in the Department of Physics and Astronomy at Washington State University (WSU), part of the College of Arts and Sciences. Her research focuses on detecting and characterizing massive black holes in low-mass galaxies to constrain models of black hole formation and growth. She employs time-domain observations to identify active black holes in dwarf galaxies missed by traditional techniques. Dr. Baldassare holds a PhD in Astronomy & Astrophysics from the University of Michigan (2017) and was previously a NASA Einstein Postdoctoral Fellow at Yale University's Department of Astronomy. She is affiliated with the Institute for Shock Physics at WSU and actively contributes to large-scale surveys such as the Merian Survey and the Young Supernova Experiment (YSE). Her research interests include AGN demographics, galaxy evolution, tidal disruption events, and multiwavelength observational techniques. Key projects involve analyzing variability-selected AGN candidates and studying the interplay between black hole activity and host galaxy properties. Recent work leverages JWST, Chandra, and ground-based facilities to probe nuclear environments in dwarf galaxies. Notable initiatives include the Merian Survey (wide-field imaging of dwarf galaxies) and the YSE Data Release 1, which catalogued 1,975 supernova light curves. She has pioneered methods for detecting AGN via optical variability and X-ray emission in low-mass systems.

Sukanta Boseمشاهده پروفایل

استاد

• Gravitation
• Cosmology
• Black Holes
• +۳ مورد دیگر

Sukanta Bose is a Professor in the Department of Physics and Astronomy at Washington State University , affiliated with the College of Arts and Sciences . His research focuses on Gravitation and Cosmology , particularly the nature of black holes, neutron stars, gravitational-wave detection, and multi-messenger astronomy. He contributes to projects like the Institute for Shock Physics and collaborates with facilities such as Advanced LIGO and Virgo. Research interests include: Gravitational-wave signal analysis and detection Black hole and neutron star dynamics Multi-messenger astronomy methods Gravitational lensing effects on wave signals Recent articles highlight advancements in: Bayesian frameworks for cosmological parameters Machine learning for signal classification Stochastic background search tools Horizon flux modeling in binary black holes No scientific awards are listed. Advising and grant details are not explicitly provided in the text. He is part of collaborative efforts in gravitational-wave astronomy and maintains an active research group.

Sinan Zhongمشاهده پروفایل

استادیار

• Urban Planning
• Sustainable Community Design
• Public Transportation Policy
• +۳ مورد دیگر

Sinan Zhong is an Assistant Professor in the Department of Landscape Architecture & Urban Planning. His research focuses on community environments, urban design, and their impacts on social interactions, health, and mobility. He has conducted studies in diverse locations including El Paso, Texas, Nigeria, and Germany. Key research interests include intergenerational community dynamics, public transportation policy, healthy aging environments, and sustainable urban planning. His work combines qualitative and quantitative methods, addressing challenges such as healthcare deserts, pandemic mobility adaptations, and infrastructure equity. Recent projects involve analyzing transit ridership strategies, pandemic-era park usage patterns, and causal effects of BRT systems. He has contributed to systematic reviews on smartphone transit apps and post-pandemic physical activity trends. His research emphasizes evidence-based solutions for socially inclusive and age-friendly urban spaces. No scientific awards or grant information is explicitly stated in the provided materials. He currently has no listed advisees or students in the given data.

Konstantinos Fokianosمشاهده پروفایل

استاد

• Time Series Analysis
• High-Dimensional Statistics
• Integer-Valued Time Series
• +۲ مورد دیگر

Konstantinos Fokianos is a Professor of Statistics at the University of Cyprus. He completed undergraduate studies in Mathematics at the University of Ioannina and earned his M.A. (1993) and Ph.D. (1996) in Statistics from the University of Maryland, USA. His academic career includes positions at Ohio State University (Visiting Assistant Professor), Lancaster University (2018-2020), and the University of Cyprus where he advanced from Lecturer to full Professor. Professor Fokianos specializes in time series analysis with focus areas including integer-valued time series models, high-dimensional time series, spectral analysis, semiparametric modeling, and isotonic estimation. His methodological research encompasses network autoregression, multivariate count time series, causal inference for health questionnaires, and clustering techniques. Applied work includes epidemiological network analysis, medical prognostics for leukemia, and tourism competition modeling. He has held visiting positions at Ludwig Maximilians University, National Institutes of Health, EPFL, and other institutions. Elected member of the International Statistical Institute since 2005, he serves on editorial boards of Journal of Time Series Analysis and Statistical Modeling, and edits Springer's 'Frontiers in Probability and Statistical Sciences' series.

Joseph Berkovitzمشاهده پروفایل

دانشیار

• Philosophy of Science
• Philosophy of Physics
• Probability Theory
• +۴ مورد دیگر

Joseph Berkovitz is an Associate Professor at Victoria College, University of Toronto. His research focuses on philosophy of science, philosophy of physics, probability theory, philosophy of economics, and metaphysics. He explores causality, probabilities, and properties in quantum mechanics, randomness in classical systems, and subjective probability theories. He has contributed to debates on de Finetti’s probability theory, causal inference, and the conceptual foundations of economics and political philosophy. His work extends to interdisciplinary areas such as the ergodic hierarchy in dynamical systems and retro-causal interpretations of quantum mechanics. He has co-edited special issues on probability and authored influential articles on topics like quantum nonlocality and modal interpretations of quantum mechanics. His teaching and supervision span undergraduate and graduate courses in epistemology, metaphysics, and political philosophy. Berkovitz has published widely in journals like Erkenntnis , Studies in History and Philosophy of Modern Physics , and The Stanford Encyclopedia of Philosophy . His research bridges philosophy of science, physics, and economics, emphasizing foundational questions in probability and causality.

Mikihiro Satoمشاهده پروفایل

استادیار

• Consumer well-being
• Experiential consumption
• Health
• +۶ مورد دیگر

Mikihiro Sato is an Assistant Professor in the Department of Recreation, Sport and Tourism at the University of Illinois Urbana-Champaign, with a secondary appointment at the Center for East Asian and Pacific Studies. His research spans multiple disciplines connecting consumer behavior, sport management, and health outcomes. Dr. Sato's research focuses on: Consumer well-being and experiential consumption Health outcomes related to physical activity and recreation Sport management and fan psychology Life satisfaction and psychological involvement in recreational activities His recent work demonstrates a clear trajectory examining how recreational and sporting activities impact consumer psychology and health outcomes, with particular attention to older adults and community-based physical activity. Dr. Sato's publications reveal strong interdisciplinary connections between marketing, psychology, public health, and recreation management. Dr. Sato has received attention for his research in media outlets, with coverage of his work on: COVID-19 policies' effects on people with disabilities The psychology of fandom and the Tokyo 2020 Olympics The impact of Olympics and mass-sporting events on public health His educational background reflects his interdisciplinary approach: Ph.D. in Business Administration from Temple University M.B.A. and M.S.A. in Sports Administration from Ohio University B.S. in Physical Electronics from Tokyo Institute of Technology