جست‌وجوی استاد و پژوهشگر

Iain D. Couzinمشاهده پروفایل

استاد

• Collective Behavior
• Animal Behavior
• Evolutionary Biology
• +۳ مورد دیگر

Prof. Iain D. Couzin is Director of the Max Planck Institute of Animal Behavior and holds a Professorship in Biodiversity and Collective Behavior at the University of Konstanz. He co-leads the German Research Foundation (DFG) Excellence Cluster “Centre for the Advanced Study of Collective Behaviour” and previously served as a full Professor in Princeton University’s Department of Ecology and Evolutionary Biology. His research focuses on uncovering the principles of collective behavior across biological scales, from neural networks to animal swarms and human societies. Research interests span experimental and theoretical approaches, leveraging cutting-edge technologies like AI-driven behavioral analysis and virtual reality for animals. These methods enable studies on coordination mechanisms in systems such as fish schools, locust swarms, and primate groups, with applications to robotics and social sciences. Key awards include the Leibniz Prize (Germany’s highest research honor), Royal Society Fellowship, and multiple citations as a Highly Cited Researcher. His leadership roles include directing interdisciplinary teams at the Max Planck Institute and the Konstanz Excellence Cluster, fostering collaborations across physics, computer science, and biology. Awards: Royal Society Fellowship (2025), Leibniz Prize (2022), Fyssen Prize (2024), Lagrange Prize (2019) Labs/Teams: Collective Behavior Lab (Max Planck Institute), Centre for the Advanced Study of Collective Behaviour (DFG Cluster)

Felipe Thomazمشاهده پروفایل

دانشیار

• Marketing Strategy
• Digital Marketing
• AI Ethics in Business
• +۶ مورد دیگر

Felipe Thomaz is an Associate Professor of Marketing at Saïd Business School, University of Oxford, and Deputy Director of the Oxford Future of Marketing Initiative. He holds a PhD in Marketing from the University of Pittsburgh and previously taught at the University of South Carolina. His research focuses on marketing strategy, AI ethics, illicit markets, and ESG integration, with notable contributions to frameworks like Ad Net Zero for net-zero advertising emissions. He collaborates with UN agencies, NGOs, and tech companies to address global sustainability goals and wildlife trafficking networks. Education: PhD in Marketing (University of Pittsburgh), MSc in Marketing & Finance (University of Pittsburgh), BSc in Animal Sciences (University of Florida). Research interests include digital marketing channels, brand performance via social networks, AI-driven marketing strategies, and conservation science linked to wildlife trade. His work bridges academia and industry, resulting in spinouts and IP transfers from Saïd Business School. Key projects include: Ad Net Zero: Global standard for reducing advertising emissions UN collaboration on wildlife trafficking through dark web analysis UNESCO partnerships on eliminating stereotypes in advertising His interdisciplinary approach spans marketing, mathematics, and conservation science, with publications in top journals like Journal of Marketing and Conservation Science and Practice .

• Machine Learning
• Computer Vision
• Biomedical Data Science
• +۳ مورد دیگر

René Vidal is the Rachleff & Penn Integrates Knowledge (PIK) University Professor at the University of Pennsylvania and Full Professor at Johns Hopkins University, with appointments spanning multiple departments including Electrical and Systems Engineering, Radiology, Computer and Information Science, and Statistics and Data Science. He serves as Director of the Center for Innovation in Data Engineering and Science (IDEAS) at UPenn and directs the NSF-Simons Collaboration on the Mathematical Foundations of Deep Learning. Education: PhD in Electrical Engineering and Computer Sciences from UC Berkeley (2003) Former Positions: Assistant and Associate Professor at Johns Hopkins University (2004–2015) Current Affiliations: Amazon Scholar, Affiliated Chief Scientist at NORCE Dr. Vidal’s research spans the mathematics of deep learning , sparse/low-rank representations , and trustworthy AI , with applications in computer vision and biomedical data science. His work has been recognized with prestigious honors including the IEEE Edward J. McCluskey Technical Achievement Award and Sloan Fellowship. Scientific awards include: 2021: IEEE Edward J. McCluskey Technical Achievement Award 2017: Jean D’Alembert Fellowship 2012: J.K. Aggarwal Prize 2009: ONR Young Investigator and Sloan Fellowship His lab has advised numerous PhD and MSc students, including Kyle Poe, Steven Kan, and alumni like Chong You (now at UC Berkeley) and Colin Lea (Oculus Research). He leads teams in optimization theory, adversarial robustness, and biomedical image analysis.

• Software Engineering
• Reverse Engineering
• Program Understanding
• +۷ مورد دیگر

Ken Wong is an Associate Professor in the Department of Computing Science at the University of Alberta's Faculty of Science. He also serves as Associate Chair within the same department. Holding a PhD in Computer Science from the University of Victoria (1999), his research focuses on software engineering challenges such as reverse engineering, program understanding, and software visualization. He emphasizes improving software evolution through tools like architecture recovery and root cause analysis, with applications in web/mobile platforms and diverse system understanding. Teaching highlights include developing Massive Open Online Courses (MOOCs) via Coursera, including the 'Software Product Management Specialization' and courses on Agile practices, client needs analysis, and software metrics. His recent publications (2023–2025) span AI-driven healthcare innovations (e.g., medical imaging, photoacoustic tomography) and advanced computer vision techniques (e.g., diffusion models, video inpainting). Notable collaborations include EVAREST studies on heart failure management and lung transplantation outcomes. His work bridges software engineering theory and practical applications in healthcare technology, with contributions to federated learning frameworks (e.g., FedLPPA) and AI-augmented clinical decision support systems. Research also extends to autonomous driving (DriveGPT4-V2) and 3D human avatar generation (DreamAvatar), showcasing interdisciplinary impact.

Andreas Malikopoulosمشاهده پروفایل

استاد

• Cyber-Physical Systems
• Transportation Systems
• Control Theory
• +۴ مورد دیگر

Andreas Malikopoulos is a Professor at Cornell University's School of Civil & Environmental Engineering and Director of the Information and Decision Science Lab (IDS Lab). Previously, he held roles as the Terri Connor Kelly and John Kelly Career Development Professor at the University of Delaware (UD) and founding Director of UD's Sociotechnical Systems Center. He also served as the Alvin M. Weinberg Fellow at Oak Ridge National Laboratory (ORNL), Deputy Director of ORNL's Urban Dynamics Institute, and Senior Researcher at General Motors R&D. His research focuses on cyber-physical systems (CPS), stochastic control, and learning-driven approaches for optimizing energy efficiency and sustainable mobility in smart cities and transportation systems. Education: PhD (Mechanical Engineering, University of Michigan, 2008), M.S. (Mechanical Engineering, University of Michigan, 2004), Diploma (National Technical University of Athens, 2000). Research Interests: Analysis and control of CPS, stochastic scheduling, game theory, and mechanism design applied to emerging mobility systems (e.g., autonomous vehicles, electric vehicles). He emphasizes integrating learning and control for socially optimal solutions in transportation networks. Awards: IEEE ITS Young Researcher Award (2019), UD’s Outstanding Junior Faculty Award (2020), Alvin M. Weinberg Fellowship (2010), and recognition as a NAS Kavli Frontiers of Science Scholar (2012). He is an IEEE Senior Member, ASME Fellow, and serves on editorial boards of leading journals. Teaching: Focuses on optimal decision-making, control theory, and emerging mobility systems. Courses include stochastic optimal control and game theory at Cornell. Labs: Leads the IDS Lab, which develops scalable frameworks for CPS and smart city applications. Current projects include coordinated routing for mixed-traffic systems and AI-driven recommendations for autonomous vehicles.

• Moral Psychology
• Cognitive Development
• Artificial Intelligence Ethics
• +۳ مورد دیگر

Sydney Levine is a former Postdoctoral Associate at the MIT Media Lab, where she collaborated with Iyad Rahwan (MIT Media Lab), Joshua Tenenbaum (MIT Brain and Cognitive Sciences), and Fiery Cushman (Harvard). Her research focuses on moral learning in adults, children, and machines, integrating cognitive development, moral psychology, and AI ethics. She holds a PhD in Psychology from Rutgers University, advised by Alan Leslie, with a dissertation on moral rules and representations. Her work bridges philosophy, cognitive science, and artificial intelligence, addressing questions like how moral norms are acquired and applied across contexts. She has collaborated with scholars from Georgetown Law, Rutgers Philosophy, and the University of Pittsburgh’s History and Philosophy of Science department. Key contributions include studies on AI-generated art attribution (iScience, 2020) and public perceptions of blame in automated systems (Nature Human Behavior, 2019). Her research emphasizes translating human moral reasoning into computational frameworks for ethical AI.

Mahsa Ghasemiمشاهده پروفایل

استادیار

• Reinforcement Learning
• Control Theory
• Active Perception
• +۳ مورد دیگر

Mahsa Ghasemi is an Assistant Professor in the Elmore Family School of Electrical and Computer Engineering at Purdue University, leading the AKADEMI Group. Her research focuses on theoretical advancements in trustworthy sequential decision-making for autonomous systems, emphasizing human-aware collaboration and adaptation to dynamic environments. She is affiliated with the Institute for Control, Optimization and Networks (ICON). Education: PhD in Electrical and Computer Engineering from The University of Texas at Austin (2021), MSE in Mechanical Engineering (2017), and BSc in Mechanical Engineering from Sharif University of Technology (2014). Research Interests: Reinforcement learning, control theory, active perception, multi-agent systems, robotics, and online learning. Applications span disaster response, healthcare, and autonomous systems design. Key methodological directions include compositional learning, human-AI collaboration, and adaptive decision-making under uncertainty. Teaching: Courses include Reinforcement Learning Theory (ECE 59500), Introduction to Reinforcement Learning (ECE 49595), and Python for Data Science (ECE 20875). Awards: Finalist for Student Best Paper Award at the 2018 American Control Conference (ACC). Students: Current advisees include Maheed H. Ahmed, Jayanth Bhargav, and Somtochukwu Oguchienti. Past members include Lai Wei and Juan Sebastian Mateo Ruiz Bulla. Service: Editorial roles at ICRA, ICCPS, and IFAC workshops. Reviewer for top conferences (NeurIPS, ICML) and journals (Automatica, IEEE TAC). Labs/Teams: Leads the AKADEMI Group, focusing on algorithmic and theoretical research in autonomous decision-making systems.

Ioana Jivetمشاهده پروفایل

استاد پژوهشی

• Learning Analytics
• Educational Technology
• Artificial Intelligence in Education
• +۵ مورد دیگر

Ioana Jivet is a Research Professor and Head of the Learning Analytics Research Professorship at FernUniversität in Hagen, Germany. She leads interdisciplinary research focused on leveraging learning analytics to enhance educational practices through data-driven insights. Her role in the CATALPA Graduate School involves collaboration across disciplines to translate research into actionable educational strategies. Educational Background: PhD in Learning Analytics from Open Universiteit Nederland (2021) Postdoc at TU Delft (2019–2021) Research roles at DIPF (2021–2024) and studiumdigitale (2021–2024) Research Interests: Self-regulated learning mechanisms and feedback systems Cultural and ethical dimensions of learning analytics adoption Design of human-centered learning dashboards Privacy concerns in educational technology AI-driven educational decision support systems Her work emphasizes practical applications, such as developing adaptive feedback tools and investigating cross-cultural usage patterns of learning analytics platforms. Professional Contributions: Secretary of the Society for Learning Analytics Research (SoLAR) General Chair for the 2024 European Conference on Technology Enhanced Learning (EC-TEL) Co-editor of Springer volumes on technology-enhanced learning Lab & Teams: Active in the Learning Analytics research group at FernUniversität, focusing on translational research between academic theory and classroom practice.

Manoj Karkeeمشاهده پروفایل

استاد

• AI in Agriculture
• Agricultural Robotics
• Precision Agriculture
• +۳ مورد دیگر

Dr. Manoj Karkee is the Norman R. and Sharon R. Scott Professor of Agriculture and Life Sciences at Cornell University's Department of Biological and Environmental Engineering. He leads the #AgRobotics Lab, focusing on AI, robotics, and automation for precision agriculture. His research includes robotic systems for crop monitoring, harvesting, and sustainable farming practices. Education: PhD in Agricultural Engineering and Human-Computer Interaction, Iowa State University (2009) ME in Remote Sensing and GIS, Asian Institute of Technology (2005) BE in Computer Engineering, Tribhuvan University (2002) Associate Degree in Civil Engineering, Tribhuvan University (1997) Research Interests: AI-driven robotic solutions for fruit harvesting and crop management Soft robotics for orchard operations Autonomous crop monitoring with sensor integration Modular robotic systems for small-scale and urban farming Awards: 2020 Rain Bird Engineering Concept of the Year 2019 Pioneer in AI and IoT (Connected World) CIGR Next Generation Leader (2015) Advising & Collaboration: Dr. Karkee leads a multidisciplinary lab collaborating with industry partners and global institutions to translate research into scalable technologies. He previously directed the Washington State University Center for Precision and Automated Agricultural Systems. Labs/Teams: The #AgRobotics Lab at Cornell develops AI and robotics solutions for labor-intensive agricultural tasks, emphasizing precision, sustainability, and economic viability.

• Sensor technology
• Electrical measurement technology
• Robotics
• +۲ مورد دیگر

Hubert Zangl is a Professor at the University of Klagenfurt and Head of the Institute for Intelligent System Technologies . He serves as Chairman of the Information Technology Curricular Commission and participates in the Faculty Conference of the Faculty of Technical Sciences. Key research areas include: Sensor technology Electrical measurement technology Robotics Signal processing Electronics Recent research trends focus on: High-fidelity FMCW radar simulation frameworks Energy-efficient sensor systems Printed electronics for structural health monitoring Uncertainty propagation in measurement science Modular robotics with secure transducer identification Capacitive tactile sensing for robotic grasping Contact: Hubert.Zangl@aau.at

Young-Jin Chaمشاهده پروفایل

استاد

• Deep Learning
• Structural Health Monitoring (SHM)
• Autonomous UAVs
• +۵ مورد دیگر

Dr. Young-Jin Cha is a tenured full Professor in the Department of Civil Engineering at the University of Manitoba, affiliated with the Price Faculty of Engineering. He holds a PhD from Texas A&M University and has postdoctoral experience at MIT. His research focuses on deep learning-based structural health monitoring (SHM), autonomous UAVs for infrastructure inspection, and smart transportation systems, with over 100 peer-reviewed publications and $1.2M in grants. He is a Fellow of ASCE and has received notable awards including the 2021 Merit Award and 2022 International Association of Advanced Materials Scientist Award. His work has been cited over 9,200 times globally. Research interests include automated SHM with UAVs, nonlinear system identification, unsupervised deep learning for damage detection, and sustainable infrastructure design. He serves as an editor for journals like Structural Control & Health Monitoring and Engineering Reports . His lab, the Laboratory for Infrastructure Science and Technology (LIST), develops advanced technologies for infrastructure resilience. Key achievements include pioneering deep learning-based SHM with UAVs, top-cited papers in civil engineering journals, and leadership in organizing international conferences. He actively seeks graduate students for research in AI-driven infrastructure solutions.

Ryo Suzukiمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Augmented Reality (AR)
• Virtual Reality (VR)
• +۵ مورد دیگر

Ryo Suzuki is an Assistant Professor at the ATLAS Institute within the University of Colorado Boulder's Computer Science department. His research focuses on innovative intersections of Human-Computer Interaction (HCI), Augmented Reality (AR), and robotics. He explores systems that blend AI, haptics, and shape-changing interfaces to create enriched user experiences. Key areas of investigation include embedding interactivity into static educational materials (e.g., textbooks), developing AI-driven AR tools for procedural instruction, and creating shape-changing robotics for tactile feedback. His work often emphasizes practical applications in education, remote collaboration, and creative industries. Recent projects include MapStory (LLM-driven map animation), RealityEffects (3D volumetric video augmentation), and HoloDevice (holographic cross-device collaboration).

Hedvig Kjellströmمشاهده پروفایل

استاد

• Computer Vision
• Human Behavior Analysis
• Animal Behavior Understanding
• +۲ مورد دیگر

Hedvig Kjellströmeröm is Professor at KTH Royal Institute of Technology and affiliated with the Max Planck Institute for Intelligent Systems. Her research develops methods for interpreting human and animal behavior through computer vision, with applications in computational aesthetics, communicative behavior analysis, and embodied AI. She serves as Editor-in-Chief for CVIU and was Program Chair for CVPR 2025.

Jie Xuمشاهده پروفایل

پژوهشگر

• Polymer Electronics
• Flexible Electronics
• Sustainable Materials
• +۴ مورد دیگر

Jie Xu is a Scientist at Argonne National Laboratory and a CASE Affiliated Scientist at the University of Chicago, Pritzker School of Molecular Engineering . Her research focuses on engineering durable, scalable, and sustainable polymer semiconductors for skin-like electronics and autonomous material discovery. Education : PhD in Chemistry (Nanjing University), Postdoctoral Fellow (Stanford University) Her research bridges polymer physics , self-driving laboratories , and AI-guided material synthesis to address challenges in stretchable electronics, recyclable polymers, and energy-efficient manufacturing. She pioneered polymer circuits that remain conductive under extreme deformation and developed the first roll-to-roll mass-production method for stretchable semiconductors. Her 15 most recent articles highlight advancements in AI-driven polymer discovery , biodegradable electronics , and multi-modal energy dissipation . Key themes include autonomous experimentation , hydrogen-bonded polymer systems , and machine learning for conjugated polymers , with applications in wearable medical sensors , soft robotics , and human-computer interfaces . Scientific accolades include the Materials Research Society Postdoctoral Award , MIT Technology Review’s Innovators Under 35 , and recognition as a Scialog Fellow . She serves on editorial boards for APL Machine Learning and Flexible Electronics , and her team at Argonne includes postdocs and students working on self-driving labs and degradable polymers .

• AI Ethics
• Computational Creativity
• Philosophy of Technology
• +۴ مورد دیگر

Alice C Helliwell is an Assistant Professor in Philosophy at Northeastern University London, specializing in AI art and computational creativity. Her research addresses philosophical questions about machine creativity, AI ethics, and the aesthetics of AI-generated art. She holds a PhD from the University of Kent and has held roles including Interim Director of the Doctoral Research School at NU London (2023-24). Her current projects include a Visiting Fellowship at Friedrich-Alexander-Universität exploring AI responsibility frameworks. Education includes: PhD in History and Philosophy of Art (University of Kent) MA in History and Philosophy of Art (University of Kent, Paris) PGCert in Occupational Psychology (Birkbeck, University of London) MA(Hons) in Philosophy and Psychology (University of Edinburgh) Her research spans: Philosophy of technology Creativity theory Applied AI ethics Landscape of AI ethics in creative industries Recent publications focus on AI alignment problems, cluster accounts of art, and Wittgensteinian analyses of AI governance. She co-edited volumes on Wittgenstein and AI (2024) and authored key works linking Darwinian creativity models to computational systems. Awards include the Paris Scholarship and Vice Chancellor’s Scholarship. Professional roles include Associate Editor at AI & Society (2024–present) and Trustee of the British Society of Aesthetics. Teaching focuses on AI/data ethics and aesthetics at NU London, with supervision of dissertations in AI art, technology ethics, and aesthetics. She holds Fellowship of Advance HE (2024).