جستجوی استاد راهنمای دانشگاهی

Nori Jacobyمشاهده پروفایل

استادیار

• Cognitive Psychology
• Neuroscience
• Machine Learning
• +۳ مورد دیگر

Nori Jacoby is an Assistant Professor in the Department of Psychology at Cornell University and a Research Group Leader at the Max Planck Institute for Empirical Aesthetics in Frankfurt. Her research bridges cognitive science, neuroscience, and machine learning to explore how internal representations shape sensory and cognitive abilities, with a focus on universality/diversity in perception and collective behavior. Education: PhD from Hebrew University of Jerusalem (ELSC), postdocs at MIT, UC Berkeley, and Columbia University Lab: Directs the CoCoCo Lab (Cornell Computational Cognition Lab) Funding: NSF-funded postdoctoral program collaborating with UC Davis, CUNY, and Princeton Research interests include: High-dimensional perceptual spaces using adaptive sampling (e.g., Gibbs sampling with people) Cross-cultural studies of music and perception via global experiments Human-AI hybrid systems for collective creativity and decision-making Recent work explores mechanisms of cultural diversity in urban populations, neural correlates of rhythm in stroke patients, and LLM alignment with human sensory judgments. Current projects include large-scale music evolution experiments and NSF-funded studies on collective intelligence. Recruitment: Actively hiring postdocs and PhD students for interdisciplinary work.

Heidi Ploegمشاهده پروفایل

استاد

• Musculoskeletal health
• Human movement
• Biomechanics
• +۶ مورد دیگر

Dr. Heidi Ploeg is a Full Professor in the Department of Mechanical and Materials Engineering at Queen's University, holding the inaugural Chair for Women in Engineering. She leads the Queen's Bone and Joint Biomechanics (Q-BJB) Lab, focused on musculoskeletal system mechanics and orthopaedic implant development. Her research integrates experimental and computational methods across scales from whole-body biomechanics to bone microstructure analysis. Education: BSc, MSc, PhD in Mechanical Engineering (Queen's University) Affiliations: ORS Orthopaedic Implants Section Chair, Editorial Board Member (Medical Engineering & Physics), and multiple professional societies Research interests include bone biomechanics, implant fixation, and medical device evaluation. Key projects involve trabecular bone modeling, dental implant stability, and antibiotic-loaded bone cement properties. She has advised over 50 students and secured grants like NSERC Discovery and CFI John R Evans Funds. Publications span biomechanical testing, finite element analysis, and orthopaedic device evaluation. Awards include the Women’s Leadership Forum Award and AAOS Women’s Health Advisory Board recognition. Her lab emphasizes diversity and inclusion, fostering collaborative training environments through industry partnerships and outreach.

François Rivestمشاهده پروفایل

دانشیار

• Artificial Intelligence Engineering
• Machine Learning Systems
• Computational Neurosciences
• +۳ مورد دیگر

Dr. François Rivest is an Associate Professor at Queen’s University, affiliated with the Department of Biomedical and Molecular Sciences (School of Medicine, Faculty of Health Sciences). He also holds cross-appointments in the School of Computing (Faculty of Arts and Science) and is a member of the Centre for Neuroscience Studies. His research focuses on machine deep reinforcement learning and animal interval timing, aiming to bridge computational neuroscience insights with advanced AI systems. He leads the Natural and Artificial Adaptive Intelligent Systems Laboratory. Education: PhD in Computer Science (Computational Neuroscience/Machine Learning) – Université de Montréal (2010) MSc in Computer Science – McGill University (2002) BSc in Mathematics and Computer Science – McGill University (2000) Research Interests: Dr. Rivest’s work integrates principles of animal learning, particularly reward-based systems and temporal cognition, into machine learning algorithms. Key areas include: Reinforcement learning frameworks inspired by dopamine signaling Drift-diffusion models for interval timing Adaptive representation construction in real-time systems Applications in smart homes, robotics, and neuroscience Publications: Over 20 peer-reviewed articles (2001–2022) span computational neuroscience, reinforcement learning, and machine learning systems. Recent work includes modeling interval timing dynamics and applying reinforcement learning to smart home systems. Lab & Affiliations: As Principal Investigator of the Natural and Artificial Adaptive Intelligent Systems Lab, he explores interdisciplinary AI applications. Collaborations include the Royal Military College of Canada (2010–present) and Queen’s University’s Center for Neuroscience Studies (2011–present).

• Virology
• Genomics
• Viral Evolution
• +۱ مورد دیگر

Anna Gatseva is a Research Fellow in Molecular Biosciences at the University of Glasgow. Her research investigates viral evolution and genome analysis through advanced bioinformatics approaches. She holds a publication record demonstrating expertise in paleovirology and disease mechanisms. Research focuses on viral fossil records in vertebrate genomes, emergence patterns of lentiviruses, and molecular foundations of diseases. Her work utilizes cutting-edge genomic techniques to explore host-pathogen evolutionary relationships across species. Publications show consistent focus on viral genetics and molecular pathology, with recent work examining Huntington's disease mechanisms and vertebrate virus evolution. Collaborative research dominates her publication history, indicating strong interdisciplinary engagement.

• Applied Stochastic Analysis
• Mathematical Ecology
• Interacting Particle Systems
• +۳ مورد دیگر

Michela Ottobre is a Professor of Mathematics at Heriot-Watt University, affiliated with the School of Mathematical & Computer Sciences. She holds editorial roles at Foundations of Data Science and SIAM Review , and is a member of the European Mathematical Society and Edinburgh Mathematical Society. Her research focuses on applied stochastic analysis, mathematical ecology, and multiscale modeling, with applications to rewilding and ecological systems. Education & Career PhD in Mathematics, Imperial College London (2012) Postdoctoral roles at Warwick University and Imperial College London Joined Heriot-Watt as Assistant Professor (2014), promoted to Full Professor (2024) Research Interests Her work integrates stochastic processes, interacting particle systems, and PDEs to model ecological and biological phenomena. Key areas include: Stochastic multiscale models Mathematical ecology and rewilding Numerical methods for SDEs Grants & Awards Leverhulme Research Grant (2020–2023) EPSRC Standard Grant (2025, £550k) for multiscale methods Sir Edmund Whittaker Memorial Prize (2019) Collaborations & Outreach Organized workshops including the 11th International Conference on Stochastic Analysis (2023) and contributed to ecological modeling initiatives. Supervises PhD students in applied stochastic analysis and mathematical ecology.

Hsiang-Yun Wuمشاهده پروفایل

پژوهشگر ارشد

• Information Visualization
• Visual Analytics
• Biological Network Visualization
• +۱۳ مورد دیگر

Hsiang-Yun Wu is a Research Fellow at the Computer Graphics department of Vienna University of Technology (TU Wien), actively contributing to information visualization and visual analytics. Her work spans biological network visualization, graph drawing, schematic network maps, and data physicalization, with a focus on interactive techniques and human-centric design. Projects: ArtVis (2022–2027) , SANE (2024–2027) , SMGV-Esprit (2024–2027) , and HumAlgo (2018–2023) . Affiliations: Member of the Visualization Group at TU Wien. Her recent publications emphasize uncertainty visualization, network physicalization, and dynamic graph representations. Notably, she received the EuroVis 2019 Honorable Mention Award for optimizing stepwise animations. Wu supervises diploma theses in areas like metabolic pathway visualization and semantic-aware character animation. Key research trends include integrating biological data with urban-style schematic maps ( Metabopolis ), physicalization workflows for anatomical education ( Slice and Dice ), and mixed labeling strategies in 3D environments.

• Smart Textiles
• RFID Technology
• Wearable Devices
• +۵ مورد دیگر

Johanna Virkki is an Associate Professor at the Department of Computing Sciences, Faculty of Information Technology and Communication Sciences, Tampere University. Her research focuses on smart textiles, wearable technologies, RFID systems, and their applications in healthcare, assistive communication, and human-computer interaction. She has pioneered projects integrating RFID into clothing and environments for control interfaces, physiological monitoring, and gamified therapies. Key research areas include: Development of e-textiles for AAC (Augmentative and Alternative Communication) RFID-based wearable and furniture interfaces for accessibility Sensor systems for healthcare monitoring and rehabilitation Smart spaces and IoT-enabled environments Her work emphasizes interdisciplinary collaboration, with notable contributions in: Passive RFID sensor platforms for moisture, strain, and physiological signals Co-design approaches involving speech therapists, engineers, and end-users Prototyping wearable devices for children with disabilities and elderly care Recent publications highlight advancements in: Smart furniture and textile-based AAC solutions AI-driven smart spaces and edge-cloud computing Bio-inspired sensors using animal hair and conductive yarns Johanna's research bridges technology and human needs, addressing challenges in healthcare, education, and accessibility through innovative textile and RFID systems.

Holzapfel Gerhard Aمشاهده پروفایل

استاد

• Biomechanics
• Mechanobiology
• Nonlinear Continuum Mechanics
• +۴ مورد دیگر

Gerhard A. Holzapfel is a Full Professor of Biomechanics and Head of the Institute of Biomechanics at Graz University of Technology (Austria) since 2007. He holds adjunct and visiting positions at KTH Royal Institute of Technology (Sweden) and the University of Glasgow (Scotland). His academic journey includes a PhD in Mechanical Engineering from Graz University of Technology, a Habilitation from TU Vienna (1996), and prestigious awards such as the START-Award (1997) and the Warner T. Koiter Medal (2021). His research focuses on constitutive modeling of biosolids, nonlinear continuum mechanics, and medical image processing. Notable contributions include studies on arterial wall mechanics, fibrous tissue behavior, and computational biomechanics. Holzapfel leads interdisciplinary teams exploring mechanobiology, vascular pathologies, and biomaterials, with applications in cardiovascular engineering and disease modeling. Education: PhD in Mechanical Engineering, Graz University of Technology Habilitation, TU Vienna (1996) Research Highlights: Multi-scale modeling of biological tissues Biaxial mechanical testing and microscopy integration Computational fluid-structure interaction (FSI) in vascular systems Biomechanical implications of medical interventions (e.g., stents, angioplasty) Awards: Warner T. Koiter Medal (2021) Corresponding Member, Austrian Academy of Sciences (2012) Erwin Schrödinger Prize (2011) START-Award (1997) Labs & Teams: Leads the Institute of Biomechanics at TU Graz, collaborating with international teams on vascular biomechanics and mechanobiology.

Debra K. Borkovitzمشاهده پروفایل

استاد بالینی

• Mathematics Education
• Teaching Methodologies
• Mastery Grading
• +۳ مورد دیگر

Debra K. Borkovitz is a Clinical Professor of Mathematics and Mathematics Education at Boston University. Her office is located in CDS 425. She is committed to innovative teaching methodologies, including mastery grading and ungrading, and advocates for inclusive educational policies accommodating students with chronic illnesses. Her research and writing focus on mathematics pedagogy, fraction operations, and the integration of technology in education. Dr. Borkovitz’s work emphasizes compassionate approaches to syllabus design and classroom management. She has explored challenges faced by educators and students with health issues, advocating for supportive academic environments. Her contributions include developing resources for fraction education, critiquing educational technologies, and creating engaging geometric visualizations through animations and interactive applets. Her publications span topics such as MOOCs in programming education, chronic illness management in academia, and problem-solving strategies in mathematics. She has also shared insights on adapting teaching practices during personal health challenges and fostering student engagement through creative methods. No scientific awards are listed for Dr. Borkovitz. Her advising and grant activities are not detailed in the available information. She maintains an active blog and has contributed to educational resources, including handouts on syllabus policies and fraction-based learning activities.

Nicholas Ouelletteمشاهده پروفایل

استاد

• Complex Systems
• Fluid Dynamics
• Environmental Engineering
• +۴ مورد دیگر

Nicholas Ouellette is a Professor of Civil and Environmental Engineering at Stanford University, specializing in complex systems far from equilibrium. His research emphasizes dynamical self-organization across disciplines like fluid dynamics, granular media, and collective animal behavior. He holds a Ph.D. in Physics from Cornell University (2006), an M.S. in Physics (2005), and a B.A. in Physics and Computer Science from Swarthmore College (2002). Prior to Stanford, he was on the faculty at Yale University’s Mechanical Engineering and Materials Science department from 2008-2015. He has received teaching awards at both institutions. His work spans experimental and theoretical studies of turbulence, granular erosion, insect swarms, and urban dynamics. Current research includes sediment transport in turbulent flows, collective behavior in bird flocks, and urban street network analysis. He leads the Environmental Complexity Lab and collaborates on projects involving ocean mixing instrumentation and computational modeling of complex systems. Research interests include turbulent flows in fluids, particle transport dynamics, granular bed erosion mechanics, and quantitative analysis of animal collective motion. Techniques employed range from particle tracking velocimetry to machine learning for free-surface reconstruction. Ouellette’s recent work explores interdisciplinary connections between physics and urban systems, such as pedestrian access optimization in suburban layouts and the interplay of multiple environmental stressors in policy modeling. Notable contributions include studies on midge swarm mechanics, jackdaw flock kinematics, and the application of spectral analysis to energy transfer in turbulence. His lab develops advanced measurement systems for oceanographic studies and applies network theory to environmental and urban systems analysis. Ouellette maintains active collaborations across engineering, biology, and policy domains.

Colin Bealeمشاهده پروفایل

استاد

• Spatial ecology
• Conservation science
• African savannah ecosystems
• +۳ مورد دیگر

Professor Colin Beale is a Professor in the Department of Biology at the University of York, leading the York Environmental Sustainability Inst (YESI) Research Theme. His work focuses on spatial ecology and conservation science, particularly in African savannahs and UK ecosystems. He combines field research with statistical methods to study species distributions, climate impacts, and fire ecology. Collaborations include organizations like the Wildlife Conservation Society and Uganda Wildlife Authority. Teaching emphasizes fieldwork and computational skills, including annual tropical ecology expeditions to Tanzania. Current research projects address biodiversity finance, savannah degradation, and illegal wildlife activity reduction. Funded grants include projects on treescapes and rangeland guardianship. Past and present students include Hien Luong, Charlie Le Marquand, and Joris Wiethase. Key projects involve mapping illegal activities in protected areas, analyzing fire regimes, and understanding climate-driven range shifts. His lab includes postdoctoral researchers like Dr Rob Critchlow and Dr Tabitha Kabora. Ongoing work integrates ecological and cultural histories to guide sustainable land use.

• Regenerative Lung Engineering
• Cell-to-Cell Communication Networks
• Systems Biology
• +۵ مورد دیگر

Dr. Micha Sam Brickman Raredon is an Assistant Professor in the Department of Anesthesiology at Yale School of Medicine. He leads the Raredon Laboratory, focused on regenerative lung engineering, systems biology, and bioengineered tissues. His work integrates computational tools like NICHES and Connectome to study cell-cell communication networks in lung tissue. Dr. Raredon holds MD/PhD degrees from Yale and a master's from MIT in Materials Science. His research spans lung vascular networks, fibrosis mechanisms, and translational applications in regenerative medicine. He is affiliated with the Vascular Biology and Therapeutics Program, Program in Translational Biomedicine, and Yale Combined Program in the Biological and Biomedical Sciences (BBS). Education: MD/PhD Yale University (2022/2021), MS Yale Engineering (2020), MPhil Yale (2020), MS MIT (2014), BS Yale & Cambridge (2011). Research Interests: Engineering functional lung tissues, decoding lung microvascular niches, single-cell systems biology, and applying machine learning to tissue regeneration. Key projects include developing algorithms for cell-cell interaction analysis and engineering patient-specific lung tissues. Recent work addresses hypoxia-induced cardiopulmonary damage and fibrotic lung diseases. Publications reflect interdisciplinary focus on lung biology, vascular integrity, and computational methods. Awards include the Draper Fellowship for tissue fabrication innovation and the Yale MD/PhD Thesis Prize. His lab collaborates with leading figures like Drs. Kaminski, Niklason, and Medzhitov. Advising and Grants: Mentors students in translational research. Lab develops ventilator splitting systems for disaster medicine and bioengineered lung models. Active in NIH-funded projects on lung regeneration and fibrosis. Labs/Teams: Raredon Lab at Yale Vascular Biology Program. Collaborations span Yale's Systems Biology, Immunobiology, and Biomedical Engineering departments.

• Biomechanics
• Soft Tissue Mechanics
• Cardiovascular Biomechanics
• +۵ مورد دیگر

Gerhard Holzapfel is a Professor at TU Graz's Department of Biomechanics. His research focuses on biomechanics of soft biological tissues, cardiovascular systems, and advanced material modeling. He leads the Institute of Biomechanics, conducting experimental and computational studies on tissue mechanics, vascular diseases, and medical device design. Education : Details not explicitly provided in source text. Research Interests : Dr. Holzapfel's work spans constitutive modeling of soft tissues, computational fluid dynamics (CFD) in vascular systems, mechanobiology of cells and tissues, and biomaterials. He emphasizes translating biomechanical insights into clinical applications such as endovascular devices and surgical simulations. His studies often integrate microstructural analysis with macroscopic mechanical behavior to understand pathologies like atherosclerosis and aortic dissection. Publications : Recent work highlights advancements in fiber dispersion models for skin mechanics, Bayesian frameworks for material calibration, and CFD-driven evaluations of TEVAR (thoracic endovascular aortic repair). His articles emphasize predictive modeling of tissue behavior under various loading conditions, with applications in cardiology and regenerative medicine. Awards : No specific honors or fellowships mentioned in the provided text. Advising & Grants : No student/advisor relationships or grant details explicitly listed. The Institute of Biomechanics likely supports collaborative projects in biomechanical engineering and medical research. Labs/Teams : Director of TU Graz's Institute of Biomechanics, leading interdisciplinary teams in biomechanics, material science, and computational modeling. Collaborates with clinical partners on vascular biomechanics and surgical device development.

Khurram Nadeemمشاهده پروفایل

دانشیار

• Predictive Modeling
• Wildland Fire Occurrence Prediction
• Spatio-Temporal Processes
• +۴ مورد دیگر

Khurram Nadeem is an Associate Professor of Statistics at the University of Guelph, specializing in predictive modeling of ecological and environmental systems. His research focuses on leveraging big data analytics to address challenges in wildland fire prediction, agricultural sustainability, and statistical bioinformatics. He leads a lab offering graduate research opportunities in these areas and collaborates with organizations like the Canadian Interagency Forest Fire Centre (CIFFC). Education: PhD in Statistics, University of Alberta (2013) MSc in Statistics, University of Karachi (2005) BSc (Honours) in Statistics, University of Karachi (2003) Research Themes: Wildland Fire Prediction: Developing spatiotemporal models to forecast fire occurrences in British Columbia, aiding fire management strategies. Agro-Environmental Science: Integrating big data from precision agriculture and genomics to optimize sustainable farming practices under climate change. Statistical Bioinformatics: Analyzing microbiome data in livestock and crops to improve disease prevention and crop resilience. Media & Partnerships: Featured in University of Guelph news for wildfire research and Food from Thought initiatives. Seeks industry partnerships in forest fire analytics, environmetrics, and quantitative ecology. Advising & Grants: Supervises graduate students in Statistics and Bioinformatics programs. Offers postdoctoral positions in applied statistics for climate-agriculture linkages and microbiome modeling. Labs & Teams: Hosts a multidisciplinary lab focusing on environmental and agricultural data science. Collaborates with the Canadian Forest Service and agricultural stakeholders.

• Hoarding and Collecting Behaviours
• Conspiracy Theory Beliefs
• Psychological Characteristics of Soccer Officials
• +۳ مورد دیگر

Dr. Nick Neave is a Professor of Psychology at Northumbria University, specializing in hoarding behaviors, conspiracy beliefs, and the psychological aspects of soccer officiating. He leads the Hoarding Research Group and chairs the UK Hoarding Partnership. His teaching focuses on hoarding, parapsychology, and hormones & behavior. With a PhD in Neurosciences from Durham University (1995), he has supervised multiple PhD students exploring hoarding, conspiracy theories, and superstition. His research spans digital hoarding’s implications for cybersecurity, workplace culture, and mental health. He has published extensively on topics like prenatal androgen effects on sports performance and trauma’s role in hoarding severity. Education: PhD in Neurosciences, Durham University (1991–1995) Research Interests: Hoarding behaviors (both physical and digital), conspiracy beliefs, superstitious behaviors, and the psychological traits of sports officials. His work bridges clinical psychology, cognitive science, and societal impacts. Grant and Advising Trends: Focus on interdisciplinary grants addressing hoarding’s social and organizational challenges, with notable collaborations on digital data management and public health implications. Currently supervising PhD projects on hoarding behavior mechanisms and conspiracy theory propagation. Labs/Teams: Hoarding Research Group (Northumbria University)