جست‌وجوی استاد و پژوهشگر

• Medical Image Analysis
• Video Surveillance Systems
• Pattern Recognition
• +۳ مورد دیگر

Lorenzo Putzu is a Researcher (Assistant Professor) at the University of Cagliari's Department of Computer Science. He holds a PhD in Computer Science from the same institution (2016). His work focuses on pattern recognition techniques applied to medical imaging and video surveillance, including automated diagnosis support systems, security applications, and synthetic data generation for AI training. Since 2017, he has been part of the PRA Lab, contributing to projects like the IMMAGINA initiative for trustworthy AI in surveillance. Education: Bachelor's Degree in Computer Science (2010) Master's Degree in Computer Science (2012) PhD in Computer Science (2016) Research Interests: Medical image analysis for automated diagnosis (e.g., blood cell classification, histopathology) Video surveillance systems using AI (e.g., person re-identification, crowd counting) Synthetic data generation for improving model robustness Federated learning in healthcare applications Adversarial defense mechanisms in computer vision Key Projects: Development of MIRIAMS for multiple sclerosis segmentation Advancing leukocyte classification methods for hematological analysis Pioneering work on federated learning for cell nuclei segmentation Grant & Advising Activities: No explicit grants or advising roles listed Labs/Teams: Active contributor to the PRA Lab, collaborating on interdisciplinary AI projects in healthcare and security.

• Transport Modeling
• Transport Simulation
• Traffic Systems
• +۳ مورد دیگر

Gunnar Flötteröd is an Adjunct Associate Professor at Linköping University's Department of Science and Technology (ITN), affiliated with the Communications and Transport Systems division. He holds a visiting faculty role at BOKU University's Institute of Transport Studies in Austria. His research focuses on transport modeling and simulation, including maritime logistics, pedestrian dynamics, and urban mobility systems. He contributes to the Swedish National Road and Transport Research Institute and teaches on-demand PhD courses in transport modeling at Linköping University. His work bridges model development and real-world applications, covering both demand and supply-side aspects of transport systems. Recent publications address coastal bathymetry estimation using AIS data and multidirectional pedestrian network flows. Flötteröd collaborates with interdisciplinary teams in logistics and communication systems research. No specific grants or advising roles are detailed in the provided materials.

• Artificial Intelligence
• Business Analytics
• Energy Systems Optimization
• +۷ مورد دیگر

Dr. Nishan Mills is a Lecturer in Business Analytics and AI at La Trobe University, Melbourne, Australia. He holds a PhD from the same institution. His research focuses on advancing AI applications across energy systems, healthcare, education, and smart cities. Key areas include explainable AI, generative models, cybersecurity, and net-zero carbon solutions. He collaborates extensively with industry and academia, co-authoring over 30 publications. Dr. Mills’ work spans technical innovations like emotion analysis frameworks (EMOTION AWARE), energy forecasting systems, and AI chatbots for healthcare and education. His research emphasizes ethical AI deployment, human-centric design, and real-world impact. Notable projects include optimizing energy infrastructure, developing mental health chatbots, and designing AI literacy modules for universities. He has contributed to IEEE journals and conferences, focusing on interdisciplinary applications of AI. His work bridges theoretical advancements with practical implementations in sustainability, urban planning, and digital transformation.

Giorgio Fumeraمشاهده پروفایل

دانشیار

• Machine Learning
• Computer Vision
• Video Surveillance
• +۳ مورد دیگر

Giorgio Fumera is an Associate Professor of Computer Engineering at the University of Cagliari. His research focuses on statistical pattern recognition, machine learning, and their applications in video surveillance, particularly in person re-identification, adversarial robustness, and uncertainty quantification. He has authored over 100 papers in leading journals and conferences, and serves as an associate editor for Pattern Recognition and Pattern Analysis and Applications . He is a member of IEEE and IAPR. His work explores cutting-edge topics such as synthetic data for surveillance systems, adversarial training defense mechanisms, and Bayesian inference for crowd counting. Recent contributions include studies on the robustness of machine learning models against adversarial attacks and the application of neural networks in microwave medical imaging. His research also emphasizes practical applications in cybersecurity, medical diagnostics, and ethical AI systems like the IMMAGINA project. Fumera’s publications span domains like ensemble methods, human-in-the-loop systems, and sparse learning. Despite extensive contributions, no specific awards or grants are explicitly mentioned in the provided materials. His research team actively collaborates on interdisciplinary projects, blending computer vision, medical imaging, and trustworthy AI principles.

• Behavioral Economics
• Experimental Economics
• Applied Microeconometrics
• +۵ مورد دیگر

Prof. Dr. Lorenz Fabian Goette is a Professor of Economics at the National University of Singapore. His research focuses on behavioral economics, experimental economics, applied microeconometrics, and environmental economics. He holds a PhD from the University of Zurich and has been a CEPR Research Fellow since 2005 and a CESifo Research Fellow since 2016. His work explores prosocial behavior, decision-making under stress, and the design of behavioral interventions. Notable studies include analyzing blood donation incentives, the impact of social recognition on prosocial actions, and the effectiveness of real-time feedback in resource conservation. Goette’s research bridges theory and practice, addressing issues like environmental policy, public health compliance during pandemics, and the psychological effects of rejection in health contexts. Recent publications investigate how large language models amplify human bias, the role of cognitive biases in health behaviors, and experimental evidence on complementarities between behavioral interventions. His interdisciplinary approach spans experimental economics, health economics, and neuroscience, with applications to policy design and organizational behavior. Education: PhD in Economics, University of Zurich, Switzerland Awards: CEPR Research Fellowship (2005), CESifo Research Fellowship (2016) Key Themes: Prosociality, behavioral nudges, stress effects on decisions, and health policy interventions

• Human Motion Prediction
• Computer Vision
• Multi-person Interaction Analysis
• +۳ مورد دیگر

Dr. Wen Guo is a Researcher at the Department of Health Sciences and Technology (D-HEST) at ETH Zurich, affiliated with the Professorship for Sensory-Motor Systems. Their work focuses on advancing computer vision, robotics, and biomedical engineering through innovative machine learning techniques. Key research interests include human motion prediction, multi-person pose estimation, and gesture generation in complex interactions. Wen Guo has contributed to high-impact projects such as the UVO Challenge 2021, securing first place in both video-based and image-based open-world segmentation categories. Their research emphasizes real-world applications in safety-critical systems, crowd behavior modeling, and human-robot interaction. Notable methodologies include hierarchical transformer dynamical VAEs for motion generation and pose-interacting networks for 3D pose estimation. Academic contributions span from foundational work in motion prediction to applied solutions in computer vision challenges. Their lab integrates interdisciplinary approaches, combining deep learning with biomechanical insights to tackle challenges in healthcare and robotics.

Monica D. Kohlerمشاهده پروفایل

استاد پژوهشی

• Earthquake Engineering
• Seismology
• Structural Health Monitoring
• +۳ مورد دیگر

Monica D. Kohler is a Research Professor of Mechanical and Civil Engineering at the California Institute of Technology (Caltech). She holds a Ph.D. in Civil Engineering from Caltech (1995) and an A.B. in Physics from Harvard University (1988). Her career includes roles as Assistant Research Engineer at UCLA (1998-2011), Visiting Associate at Caltech (2007-11), and Research Assistant Professor at Caltech (2011-17). Research Interests: Dr. Kohler's work bridges earthquake engineering and observational seismology. She develops methods to detect structural damage using seismic arrays, applies tomographic inversion to study urban ground motion, and investigates wave propagation in buildings and geological systems. Her research leverages IoT sensor networks and real-time data for city-scale seismic monitoring. Article Trends: Her recent publications focus on structural health monitoring of high-rises via coda wave interferometry, community seismic networks for urban resilience, and subduction zone dynamics. Key subfields include nonlinear damage identification, tsunami wavefront mapping, and edge computing applications for seismic data. Students & Collaborations: She supervises graduate students at UCLA (Viviana Vela, Gloria Hyun, Esra Zengin) and collaborates with institutions like Caltech, UCLA, and IRIS. Her projects include the Community Seismic Network (CSN) and ShakeAlert earthquake early warning system. Contact: Office at 318 Gates-Thomas Laboratory, Caltech. Email: kohler@caltech.edu .

• Music and Emotions
• Music Perception
• Music Cognition
• +۳ مورد دیگر

Professor Tuomas Eerola is a prominent academic in music cognition at Durham University, holding the title of Professor of Music Cognition in the Department of Music. He has also served as Director of Research (2013-2015, 2021-), Head of Department (2018-2020), and Associate Fellow at the Institute of Advanced Study. His career includes a PhD from the University of Jyväskylä (2003) and postdoctoral research in Europe and the U.S., later becoming a professor there until 2013. His research focuses on music and emotion, perception of musical structure, computational modeling, and open science practices. Notable projects include the Sweet Sorrow (Academy of Finland), Interpersonal Entrainment in Music Performance (AHRC), and collaborations on EU-funded initiatives. He leads the Music & Science Lab and co-directs the MA in Music Psychology program. Eerola has authored over 100 publications, including a 2024 textbook Music and Science: A Guide to Empirical Research . His work emphasizes transparency in research, open data sharing, and reproducibility. He has mentored many academics, including Kai Tuuri and Jonna Vuoskoski, and serves on editorial boards for journals like Psychology of Music .

Tim Brownمشاهده پروفایل

مدرس ارشد

• Charity Fundraising Events
• Events Management
• Virtual and Hybrid Events
• +۵ مورد دیگر

Tim Brown is Head of Division in the Faculty of Science, Business and Enterprise at the University of Chester. He holds a Senior Lecturer rank in Events Management and has over 15 years of academic and industry experience. He leads programs like the BA (Hons) Events Management and contributed to developing MSc programs in Tourism and Fashion Marketing. His research focuses on charity fundraising, virtual/hybrid events, and organizational ambidexterity in charities. He is a Senior Fellow of the HEA and Fellow of the RSA. Education: PhD (2018): University of Chester MBA (2007): University of Liverpool BA (Hons) Performing Arts (1999): De Montfort University PGCE in Higher Education (University of Chester) Research Interests: Tim’s work spans charity fundraising strategies, virtual/hybrid event innovation, event logistics, and sustainability. He has published widely, including textbooks like Virtual Events Management and Events Mismanagement . His recent studies explore organizational ambidexterity in charities and post-pandemic event trends. Awards: Senior Fellow of the Higher Education Academy Fellow of the Royal Society of Arts (FRSA) Professional Activities: Tim chairs the AEME Executive, advises on major events (e.g., Liverpool Sound Concert hospitality), and collaborates with the Institute for Culture and Society. His industry experience includes event director roles and managing high-profile events like MIPIM in Cannes.

Shahar Sukenikمشاهده پروفایل

استادیار

• Protein Biophysics
• Intrinsically Disordered Proteins
• Environmental Stress Biology
• +۴ مورد دیگر

Shahar Sukenik is an Assistant Professor of Chemistry at Syracuse University, affiliated with the College of Arts & Sciences. His research focuses on understanding how proteins interact with their cellular and extracellular environments, particularly under stress conditions such as desiccation. He employs live-cell microscopy, high-throughput experiments, and computational modeling to study intrinsically disordered proteins (IDPs) and their roles in health and disease. Sukenik holds a Ph.D. in Chemistry from the Hebrew University of Jerusalem (2014), with prior degrees from the same institution. His work bridges biophysics, biochemistry, and environmental stress biology, emphasizing how cellular chemistry regulates protein function. Key projects include investigating IDPs’ protective roles during desiccation and their structural dynamics in live cells. Sukenik has received prestigious awards, including the Sloan Research Fellowship (2024–2026) and an NIH NIGMS R35 Award (2020–2025). He leads the Sukenik Lab, collaborating with institutions globally to advance understanding of protein-environment interactions. Recent research highlights include uncovering mechanisms of desiccation tolerance via LEA protein motifs and elucidating how YAP condensates organize transcriptional hubs. His grants include NSF funding for studying functional synergy between IDPs and their environment during desiccation. Sukenik also serves on committees for the Biophysical Society and co-chairs workshops on macromolecular crowding.

• Platform operations
• Crowd-based innovation
• Game theory
• +۲ مورد دیگر

Sidika Candogan is an Assistant Professor in Analytics & Operations at NUS Business School. She holds a PhD in Management Science and Operations from UCL (2022), MRes from UCL (2017), and BS/MS in Industrial Engineering from Middle East Technical University. Her research examines platform operations for crowd-based innovation and new product development, using game-theoretical models, empirical analysis, and NLP techniques to enhance economic value generation. Her publications focus on innovation contest design, team dynamics in crowdsourcing, and product development processes in crowdfunding platforms.

• Cybersecurity
• Machine Learning
• Internet-of-Things (IoT)
• +۵ مورد دیگر

Sejun Song, Ph.D., is a Professor at the School of Computer & Cyber Sciences (SCCS) at Augusta University, Georgia. He has held prior roles including Assistant Professor at Texas A&M University and founding director of the Cisco Test Engineering Center (Cisco-TEC). His research focuses on Cybersecurity, Machine Learning, IoT, and Mobile/Wireless Communications for applications in smart cities, eHealth, transportation, and agriculture. Song holds a Ph.D. in Computer Science and Engineering from the University of Minnesota (2001) and has industry experience at Cisco Systems and Honeywell Research Lab. His work spans funded projects by NSF, DoD, NASA, NIH, and others. Notable contributions include AI-driven cybersecurity solutions, crowd dynamics modeling, and edge computing frameworks for surveillance. Awards include the NASA Summer Fellowship and multiple best paper/video awards at conferences like CCNC and Mobisys. His interdisciplinary projects include smart infrastructure development and technology education for underserved populations. Research Highlights: Deepfake detection using corneal reflections (READFake, MobiDeep) Resilient network systems for IoT and space communications Energy-efficient semantic communication protocols Funding Agencies: NSF, DoD, ONR, AFOSR, NASA, NIH, CDC Awards reflect multiple domains: teaching excellence (Center for Teaching Excellence Scholar), research innovation (Air Force Visiting Fellowship), and applied results (best video/paper awards). Key labs/teams involve Cisco-TEC and collaborations on edge computing, federated networking, and smart city infrastructure. Current research emphasizes trustworthy AI systems, green communication, and pandemic-era crowd safety analytics.

Taro Naraharaمشاهده پروفایل

دانشیار

• Architectural Informatics
• Computational Design
• Artificial Intelligence/Machine Learning
• +۶ مورد دیگر

Taro Narahara is an Associate Professor at the Hillier College of Architecture at NJIT, specializing in AI-driven spatial analysis and computational design. His work bridges architecture with emerging technologies like VR, machine learning, and robotics. He holds a Doctor of Design from Harvard University, an M.S. in Design and Computation from MIT, and a B.S. in Mathematics from Waseda University. His research focuses on applying AI/ML to architectural informatics, including floor plan analysis (published in IEEE TMM and SIGGRAPH), VR-based architectural visualization, and generative design for sustainable housing. He has led NSF-funded projects in computational design and collaborated with biomedical engineers on rehabilitation robotics and gaming interfaces. Notable awards include the 2021 IDR Excellence Award (NII), 2020 Human Communication Award (IEICE), and the 2016 Excellence in Research Award (NJIT). He has held visiting scholar roles at ETH Zurich (ITA) and the University of Tokyo’s Department of Information and Communication Engineering. His teaching includes courses like AI/VR in Architecture (Arch 689-104) and Transformable Places (Arch 463/464). He maintains an active research website at narahara.net , showcasing projects like the Kurashiki Viewer VR system and generative Muqarnas patterns.

Günter Bärwolffمشاهده پروفایل

استاد

• Applied Mathematics
• Numerical Analysis
• Fluid Dynamics
• +۵ مورد دیگر

Günter Bärwolff is a retired Professor of Applied Mathematics at the Department of Mathematics, Technische Universität Berlin. Though retired, he continues to engage in academic activities and research. His work focuses on numerical methods for partial differential equations, computational fluid dynamics, and mathematical modeling of crystal growth and fluid flows. He has authored influential textbooks such as Numerik für Ingenieure, Physiker und Informatiker and Numerik in der Physik, Ingenieurwissenschaft und Informatik , the latter co-authored with Caren Tischendorf. His research interests span applied mathematics, numerical analysis, and their applications in engineering and natural sciences. Key areas include finite volume methods, direct numerical simulation (DNS), control of turbulent flows, and optimization of fluid dynamics problems. He has also contributed to pedestrian dynamics modeling using hybrid macroscopic approaches and cellular automata techniques. Bärwolff has been actively involved in international conferences and collaborations, presenting on topics such as crystal melt modeling with magnetic fields, boundary control of Navier-Stokes equations, and multi-destination crowd simulation. His work bridges theoretical developments with practical applications in areas like semiconductor crystal growth and public transport management. Despite retirement, his research continues to address challenges in computational science and engineering.

Dominik Schreyerمشاهده پروفایل

استاد مدعو

• Sports Management
• Consumer Behavior
• Sports Economics
• +۳ مورد دیگر

apl. Professor Dominik Schreyer is an Adjunct Professor in the Entrepreneurship and Innovation Group at WHU – Otto Beisheim School of Management, and Director of the Center for Sports and Management. His research focuses on sports consumer behavior, future trends in sports, and organizational and individual behavior in sports contexts. He holds a PhD from EBS University (2014) and degrees in Politics, Communications, Business, and Economics from Universities of Düsseldorf, Auckland, and Zeppelin University. His work examines topics such as stadium attendance, no-show behavior, technology’s impact on sports consumption, and global sports trends. His research spans empirical analyses of spectator behavior, including studies on Formula 1 demand, women’s sports attendance, and the influence of celebrity athletes. He has also explored how emerging technologies reshape sports media and fan engagement. His articles frequently address behavioral economics principles applied to sports contexts, such as reward systems reducing no-show rates or the psychological effects of home advantage in Olympic competitions. As Director of the Center for Sports and Management, Schreyer bridges academic research with practical insights into sports management strategies. His interdisciplinary approach combines elements of marketing, economics, and organizational behavior to address contemporary challenges in the sports industry.