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Nevzat YILDIRIMView profile

Professor

• Hydraulic Engineering
• Fluid Mechanics
• Vortex Dynamics
• +3 more

Prof. Nevzat YILDIRIM is a full-time Professor at Çankaya University's Department of Civil Engineering (since 2016) and previously held professorships at Gazi University (2001-2016) and other institutions. He holds a PhD in Hydraulic Engineering from The University of Iowa (1982), following a MSc from the same university (1978) and a BSc from Istanbul Technical University (1975). His research focuses on hydraulic engineering, particularly intake design, vortex dynamics, and fluid mechanics. He has advised over 14 graduate students on topics like critical submergence analysis and sediment transport. Research interests include optimizing intake systems, analyzing free-surface vortices, and understanding sediment transport mechanisms. His work bridges theoretical fluid dynamics with practical hydraulic engineering solutions. Notable contributions include developing equations for air-core vortex profiles and critical submergence criteria for multi-pipe intakes. Prof. YILDIRIM has over 30 peer-reviewed articles in journals like the KSCE Journal of Civil Engineering and Journal of Hydraulic Engineering . His collaborations with researchers like Kerem Taştan and Fikret Kocabaş highlight interdisciplinary approaches to hydraulic challenges. He has led projects on intake vortex mitigation and sediment impact studies. No specific awards are listed, but his extensive contributions to hydraulic theory and education are evident through his prolific publications and academic leadership roles.

• Computer Vision
• Machine Learning
• Autonomous Driving
• +3 more

Adrien Gaidon is an Adjunct Professor with a focus on Human-Centered Action Recognition and advanced visual representation learning. His current projects include collaborations with MIT on Physical and Functional Inductive Biases for visual systems, while completed works span Robust Machine Learning and Interaction-Aware Control for autonomous vehicles. Research Trends : His 2025 publications emphasize 3D Scene Understanding , Depth Estimation , and Neural Radiance Fields , alongside innovations in Uncertainty-Aware Perception and Self-Supervised Learning . Key subfields include Autonomous Driving , Robotics , and Geometric Learning for dynamic environments. Advising and Grants : No explicit details about students, teams, or grants were found in the provided text.

• Electric Power Distribution
• Load Profile Analysis
• Distribution Systems
• +5 more

Mauricio Salazar Duque serves as a University Researcher in the Department of Electrical Energy Systems within the School of Electrical Engineering at Eindhoven University of Technology (TU/e). His work focuses on modernizing power distribution infrastructure through advanced computational techniques. His research expertise spans critical domains in electrical grid modernization: Electric Power Distribution & Load Profile Analysis Distribution System Optimization & Photovoltaics Integration Community Energy Storage & Reinforcement Learning Applications His publications consistently address UN Sustainable Development Goals related to affordable clean energy and climate action. Recent work demonstrates strong emphasis on data-driven modeling for grid resilience. Analysis of his 2023-2025 publications reveals a strategic shift toward generative AI for load profile synthesis and tensor-based mathematical formulations for multidimensional grid analysis. Key themes include handling PV integration challenges in low-voltage networks and developing visualization techniques for medium-voltage load anomalies. No scientific awards are documented in available records. He contributed to the 2018-2022 project 'Decentrale Optimalisatie en Sturing van Elektriciteitsdistributienetten' as a research member and supervised at least one Master's thesis on transfer learning for medium-voltage network measurements. His research collaborations extend through TU/e's press engagements including National Growth Fund initiatives and mobility systems workshops. Salazar Duque operates within TU/e's Electrical Energy Systems research group, collaborating with Prof. J.G. Slootweg and international partners on smart grid innovation projects.

James BagrowView profile

Associate Professor

• Network Science
• Complex Systems
• Data Science
• +4 more

James Bagrow is an Associate Professor of Mathematics & Statistics at the University of Vermont, affiliated with the Vermont Complex Systems Center. His research focuses on complex systems, network science, and data science, combining mathematical models with large-scale data analysis to understand physical and social systems. He has pioneered methods in network data analysis, including the development of the textbook Working with Network Data (Cambridge University Press, 2024). Bagrow's work spans diverse applications, from human mobility patterns to open-source software dynamics and emergency response modeling. He teaches courses in applied mathematics and data science, including Data Science I/II and Advanced Engineering Mathematics . His interdisciplinary contributions have led to collaborations across computer science, physics, and social sciences, with over 70 peer-reviewed publications. Notable achievements include the FOSS Impact paper award (2021) and a Nature Human Behaviour cover article (2022) on sleep patterns during travel. Bagrow's research emphasizes predictive capabilities in social systems, information flow dynamics, and network visualization. His lab explores computational tools for analyzing complex networks, with applications to urban dynamics, crowd behavior, and disaster response. His recent work bridges symbolic regression and neural networks, aiming to enhance model interpretability and accuracy. Awards: FOSS Impact paper award (2021), Nature Human Behaviour cover article (2022) Grants & Funding: Active in securing NSF and interdisciplinary grants for complex systems research Lab/Team: Vermont Complex Systems Center, fostering collaborations in data-driven science and network analysis

• Robotics
• Computer Vision
• Autonomous Systems
• +3 more

Lucia BERGANTIN is an Enseignant Chercheur (Teaching and Researcher) in the Computer Science department at IMT Atlantique, based at the Brest campus. Her work focuses on robotics, computer vision, and biomimetic systems, particularly leveraging optic flow algorithms for navigation and control in autonomous systems. Her research explores applications in underwater vehicles, aerial robotics, and bio-inspired models derived from insect behavior. Her research interests span robotics control, sensor integration, and autonomous navigation systems. Notably, she investigates optic flow-based odometry for both indoor/outdoor environments and underwater missions, emphasizing real-time performance and reliability across varying trajectories. Lucia’s publications highlight contributions to oscillatory trajectory modeling, biomimetic visual systems, and sensor fusion strategies. Her work often bridges theoretical models with practical implementations in robotics, aiming to enhance autonomous systems’ adaptability and precision in dynamic environments. Her advising and grants are not explicitly detailed in the provided texts, but her department (Computer Science) at IMT Atlantique is part of the Institut Mines-Télécom network, indicating potential collaborative research opportunities. Her research aligns with broader institutional priorities in digital and environmental transitions.

Işılay TekçeView profile

Assistant Professor

• Project/Construction Management
• Performance Studies
• Facility Management
• +5 more

Dr. Işılay Tekçe is an Assistant Professor at Ozyegin University, specializing in Project/Construction Management and Sustainability. Previously, she served as an Assistant Professor at Okan University (2010-2013) and conducted research at Istanbul Technical University's Project Management Center (2000-2010). She holds a PhD from Istanbul Technical University (2010) with a dissertation on multi-criteria performance measurement for construction contractors. Education: B.Sc. in Architecture, Istanbul Technical University (2000) M.Arch in Project and Construction Management, Istanbul Technical University (2002) PhD in Architecture - Building Sciences, Istanbul Technical University (2010) Research focuses on: Performance measurement in construction Sustainability in healthcare and office buildings Occupant satisfaction through BIM and IoT integration Multi-criteria decision-making in facility management Her work includes FP7 projects and publications on green retrofitting, post-occupancy evaluation tools, and acoustic/thermal comfort in buildings. Awards and international recognition highlight her contributions to sustainable construction practices.

Taewon KangView profile

Researcher

• Computer Science
• Artificial Intelligence
• Computer Vision
• +5 more

Taewon Kang is a researcher at Korea University's Department of Computer Science, specializing in artificial intelligence, computer vision, and AI's intersection with digital art. His work includes novel view synthesis, GAN-based image translation, and emotion recognition systems. Key projects: Vender (AI vending machine with emotion analysis), Text2Story (text-guided video narratives), and GLEAN-ID (identity-preserving super-resolution). Collaborated with Prof. Ming-Hsuan Yang at UC Merced (2022–2023) and participated in workshops like ICCV 2019. Research focuses on: Generative AI (diffusion models, GANs) Human-AI interaction (emotion detection, empathy-driven systems) Creative applications of AI in art and education Recent article trends include: 3D priors for single-image synthesis (2024) Score-based stochastic modeling in Hilbert spaces (2023) Interactive AI for real-time translation (2020–2021) Scientific awards: Multiple competition wins (2014–2023) Two Korean patents (2016, 2018) 2017 Intel ISEF Finalist Part of the Temporary Artists team for the Play on AI exhibition (2020–2021), creating AI-driven artworks exploring empathy and connection.

• Virtual Reality
• Computer Graphics
• Human Perception
• +3 more

Niall L. Williams is a Faculty Fellow at the New York University Tandon School of Engineering, part of the Immersive Computing Lab led by Prof. Qi Sun. His research focuses on applied human perception in computer graphics, with particular expertise in natural walking algorithms for virtual reality. He holds a PhD in Computer Science from the University of Maryland, College Park (UMD), where he contributed to computational methods for redirected walking. His undergraduate studies at Davidson College included redirected walking threshold research under Prof. Tabitha Peck. Education: PhD in Computer Science, University of Maryland, College Park (2024) B.S. in Computer Science, Davidson College (High Honors, 2019) Research interests span virtual reality navigation, human perception modeling, and haptic/robotic interfaces. Recent work explores multisensory integration in VR environments and environment compatibility metrics for natural walking systems. Notable awards include Best Paper Honorable Mentions at IEEE VR 2022 and IEEE ISMAR/VR 2021. His open-source library PettingZoo (NeurIPS 2021) is widely used in multi-agent reinforcement learning research. Teaching roles include instructing NYU courses on programming and visualization, along with extensive TA experience at UMD and Davidson. He has also contributed to educational outreach through initiatives like Girls Talk Math. Current affiliations include NVIDIA Research internships and collaborations with Meta Reality Labs. His work bridges computer graphics, robotics, and human-computer interaction to improve immersive experience safety and realism.

• Sub-Riemannian Geometry
• Mathematical Analysis
• Neurogeometry
• +3 more

Giovanna Citti is a Full Professor in the Department of Mathematics at the University of Bologna. Her research focuses on sub-Riemannian geometry, mathematical analysis, and neurogeometry, with a particular emphasis on modeling the functional architecture of the visual and motor cortices. She develops geometric frameworks to understand neural processing in the brain, including models of visual perception and motor control. Her work integrates concepts from differential geometry, partial differential equations (PDEs), and Lie group theory to analyze sub-Riemannian structures. She explores regularity properties of subelliptic PDEs and applies these to biological systems, such as the cortical organization of the visual cortex and motor pathways. Recent efforts include developing brain-inspired neural networks and studying neurogeometric models of stereo vision and 3D perception. Key contributions include sub-Riemannian models of perceptual completion, cortical-based optimal transport frameworks, and analysis of geometric optical illusions. Her research bridges pure mathematics and neuroscience, addressing challenges in both fields through innovative interdisciplinary approaches.

• Genome-Wide Association Studies
• Ultrasonography
• Brain Imaging
• +5 more

Michael Brown is a Researcher at Erasmus MC, actively contributing to interdisciplinary research at the intersection of neuroscience, medical imaging, and genetics. His work primarily focuses on developing and applying advanced ultrasound technologies for brain imaging and conducting large-scale genomic studies. Dr. Brown's research interests span multiple domains including Genome-Wide Association Studies , Ultrasonography , Brain Imaging , and Transducer Engineering . His work demonstrates a strong emphasis on developing innovative imaging techniques that bridge engineering and neuroscience, particularly in the area of functional ultrasound for monitoring brain activity in freely moving subjects. In genetics, he contributes to large consortium efforts examining the genetic basis of heart failure and lipid metabolism. His recent publications reveal a clear trend toward interdisciplinary research that combines engineering, neuroscience, and genetics. Dr. Brown has been particularly active in developing mobile human brain imaging using functional ultrasound technology, which represents a significant advancement in neuroimaging capabilities. His work on four-dimensional computational ultrasound imaging demonstrates technical innovation in visualizing brain hemodynamics. Simultaneously, his contributions to genome-wide association studies show his involvement in large-scale collaborative genetic research spanning multiple populations. Dr. Brown has established significant research collaborations across multiple institutions as evidenced by his participation in major research consortia including the Genes & Health Research Team, The Estonian Biobank Research Team, DBDS Genomic Consortium, and HERMES Consortium. His research has garnered attention across academic and social platforms with mentions in news outlets, blog posts, and substantial engagement on academic social networks.

• Computational Fluid Dynamics
• Microfluidics
• Lattice Boltzmann Methods
• +2 more

Professor Emilie Sauret holds an ARC Future Fellowship at QUT's School of Mechanical, Medical & Process Engineering. With a PhD in Turbulence Modelling from Sorbonne University, she develops computational methods for complex fluid systems. Research focus areas: Physics-informed neural networks for microfluidics Electrohydrodynamic control of fluid interfaces Biomedical applications of computational fluid dynamics Publications showcase interdisciplinary approaches to fluid dynamics, with recent advances in predictive modelling of lung deposition and microfluidic device optimization. Her work bridges fundamental physics with energy and biomedical applications. Leadership roles include council membership in the Australasian Fluid Mechanics Society. She has secured $8M in research funding and collaborates with MIT, NASA JPL, and industry partners.

Gisuk HwangView profile

Associate Professor

• Thermofluid Sciences
• Thermal Management Systems
• Sustainable Energy Systems
• +7 more

Dr. Gisuk Hwang is an Associate Professor in the Department of Mechanical Engineering at Wichita State University (WSU), part of the College of Engineering. He leads the Sustainable Energy Science and Engineering Laboratory (SESEL), focusing on thermofluid sciences to develop sustainable energy systems. His research spans advanced thermal management, energy conversion, and environmental technologies, supported by grants from NSF, NASA, and Sandia National Lab. Dr. Hwang earned his M.S. and Ph.D. in Mechanical Engineering from the University of Michigan, followed by postdoctoral work at Lawrence Berkeley National Laboratory. His expertise includes phase-change heat transfer, additive manufacturing of wicks, and machine learning applications in thermal systems. Research interests include micro/nanostructured systems for energy efficiency, thermal diodes, and sustainable cooling solutions. Key projects involve optimizing capillary evaporators, developing novel wick structures, and enhancing heat transfer in fuel cells and batteries. His team has produced over 50 peer-reviewed publications and graduated numerous Ph.D. and M.S. students. Notable awards include the John A. See Award and NSF grants. Current openings exist for Ph.D. candidates in thermofluid science and engineering. Labs/Teams: SESEL Lab. Collaborative projects focus on additive manufacturing, computational modeling, and experimental validation of thermal systems.

• Renewable Energy
• Chemical Engineering
• Environmental Science
• +3 more

Maulidi Barasa is a Postdoctoral Research Fellow at The Roux Institute, Northeastern University. His research focuses on renewable energy systems, chemical engineering for biofuel production, and fluid dynamics in wind energy applications. He specializes in optimizing biodiesel processes using catalytic transesterification, analyzing wake effects in wind turbine arrays, and modeling atmospheric boundary layer interactions. His work addresses challenges in sustainable energy transition, particularly for Sub-Saharan Africa, emphasizing cost-optimal renewable energy solutions. He has contributed to studies on wind power variability in Kenya and CFD simulations for turbine wake dynamics. Barasa's research integrates numerical analysis, computational fluid dynamics (CFD), and policy frameworks to enhance energy system resilience. His articles highlight advancements in biofuel feedstock utilization, wind farm optimization, and renewable integration strategies. He collaborates on interdisciplinary projects bridging chemical engineering, environmental science, and energy economics. While no formal awards or grants are listed, his publications reflect a strong focus on practical solutions for sustainable energy challenges in developing regions. His current affiliation at The Roux Institute underscores Northeastern University's applied research initiatives in renewable technologies and climate action.

• Design Research
• Human-Centered Design
• Ethnography
• +4 more

Özge Çelikoğlu is an Associate Professor at Istanbul Technical University , Faculty of Architecture , Department of Industrial Product Design . She holds a Ph.D. in Industrial Product Design from the same university, with a research focus on Design Culture and Social Context and Design Methods . Her work bridges ethnographic studies with design innovation. Ph.D., Industrial Product Design (2011-2016), Istanbul Technical University M.Sc., Industrial Product Design (2008-2011), Istanbul Technical University B.Sc., Textile Engineering (2003-2007), Istanbul Technical University Her research emphasizes Design Research through ethnographic lenses, metaphor analysis, and user narratives. Recent publications explore human-centered design , cultural probes , and domestic cleaning practices during pandemics , reflecting her interest in how design interacts with societal and behavioral patterns. From 2020 to 2021, she led the project Metaphor Use in Industrial Product Idea Development: A Study on Campus Life Diversity , integrating metaphor theory into practical design frameworks. Her collaborations span institutions like the University of Pennsylvania and researchers such as K. Krippendorff and M. Hamarat.

Craig Michael RawlingsView profile

Associate Professor

• Social Psychology
• Culture
• Network Analysis
• +3 more

Craig Michael Rawlings is the Fuchsberg-Levine Family Associate Professor of Sociology at Duke University's Trinity College of Arts & Sciences. He holds a D.Phil. in Sociology from the University of California, Santa Barbara (2008). His research focuses on social networks, peer influence processes, and how these dynamics shape attitudes, cultural tastes, and beliefs. Rawlings has held academic roles including Assistant Professor (2018-2023) and Associate Professor (2023-present) at Duke. His research interests span social psychology, cultural sociology, and network analysis. Key projects include studying political polarization's impact on popular culture, the microfoundations of ideological sorting, and mechanisms of cognitive authority in group settings. He collaborates with the National Institutes of Health (NIH) on grants like 'The Impact of Gossip on Children’s Feelings of Belongingness' (2023-2026). Teaching includes courses such as Sociological Inquiry, Advanced Social Network Methods, and Political Methodology. Professional activities include leading Bass Connections projects on social network dynamics in preschoolers (2020-2022). His work integrates computational methods with theoretical frameworks, exemplified in publications like Network Analysis: Integrating Social Network Theory, Method, and Application with R (Cambridge University Press). Notable contributions include analyzing sentiment network dynamics, cultural consecration processes in art prizes, and knowledge flow patterns in multidisciplinary academia. Rawlings maintains external affiliations with Statistical Horizons and the University of British Columbia, furthering his interdisciplinary reach.