جستجوی استاد راهنمای دانشگاهی

Kenneth Marinoمشاهده پروفایل

استادیار

• Computer Vision
• Natural Language Processing
• Reinforcement Learning
• +۴ مورد دیگر

Dr. Kenneth Marino is a Research Scientist at DeepMind , set to join the University of Utah as an Assistant Professor at the Kahlert School of Computing in Fall 2025. He earned his PhD in Machine Learning from Carnegie Mellon University (funded by NDSEG and NSF GRFP fellowships) and completed his undergraduate studies in Computer Engineering with a minor in Computer Science at Georgia Tech . Dr. Marino's research focuses on the intersection of Computer Vision , Natural Language Processing , and Reinforcement Learning , with emphasis on: Multimodal agents operating on the web, in simulation, and in real-world environments Evaluating AI systems and creating high-impact datasets (e.g., A-OKVQA , OK-VQA ) Incorporating semantic knowledge into end-to-end learning frameworks Embodied reasoning through language-guided planners and neural reporters Language model distillation for agent supervision Human-AI collaboration to improve RL generalization His work has been published in top venues including ICML , NeurIPS , ECCV , CVPR , and ICLR , with recent trends emphasizing: Relational reasoning in LLMs Object-centric world modeling Continual learning for embodied agents Reporter neural networks for agent control Legal AI benchmarking (e.g., BriefMe ) Knowledge graph integration for visual classification Scientific recognition includes: NDSEG Fellowship NSF GRFP Fellowship He has served on the MLD PhD Admissions Committee and as an Area Chair for ECCV 2024 , with prior teaching experience at Columbia University (COMS 6998) and Carnegie Mellon University (16-824, 10-401).

Christopher Andrew Bailمشاهده پروفایل

استاد

• Artificial Intelligence
• Political Polarization
• Social Media
• +۵ مورد دیگر

Christopher Andrew Bail is a Professor of Sociology, Computer Science, Political Science, and Public Policy at Duke University's Trinity College of Arts & Sciences. He directs the Society-Centered AI Initiative and co-founded the Polarization Lab. His research focuses on AI's impact on human behavior, particularly in social media contexts, aiming to mitigate political polarization and design prosocial digital platforms. Bail holds a Ph.D. from Harvard University (2011). His expertise spans computational social science, online political discourse, and AI ethics. Notable contributions include groundbreaking work on social media's role in polarization, interventions to reduce partisan animosity, and the development of AI-driven dialogue platforms. He has authored influential books like Breaking the Social Media Prism , which led to policy changes at Twitter and inspired NextDoor's conflict mediation tools. Recent publications emphasize AI's societal implications, experimental methods to improve online interactions, and consensus-based reforms in machine learning research. His work appears in Science , Nature , and the New York Times , among others. Awards include the Guggenheim Fellowship (2018) and Carnegie Fellowship (2017). Bail's grants include funding from NSF, Templeton Foundation, and others for projects on ideological distance in social media, computational social science training, and AI for intellectual humility. He teaches advanced courses on AI in sociology and interdisciplinary data science. His media engagements span major outlets like CNN, BBC, and NPR, where he discusses digital polarization and tech policy. He co-founded the Summer Institutes in Computational Social Science and advises the NSF's Social, Behavioral, and Economic Sciences Directorate. Current initiatives include the Trinity Social AI Initiative and Duke’s Interdisciplinary Data Science Program.

Tiffany Calvertمشاهده پروفایل

دانشیار

• Digital Art
• Contemporary Painting
• Artificial Intelligence in Art
• +۳ مورد دیگر

Tiffany Calvert is an Associate Professor and Chair of the MFA in Visual Art program at Washington University in St. Louis’s Sam Fox School of Design & Visual Arts. Her work merges traditional painting techniques like fresco and oil with digital technologies such as AI-driven image generation (StyleGAN) and 3D modeling. She explores themes of algorithmic aesthetics, historical art recontextualization, and the intersection of art and capitalism. Education: MFA in Visual Art, Mason Gross School of the Arts, Rutgers University (2005) BA in Studio Art, Oberlin College (1998) Research Interests: Calvert investigates how artificial intelligence and data manipulation reshape painting’s legacy. Her Machine Vision series employs machine learning trained on historical still lifes, creating hybrid works that critique economic speculation (e.g., tulip mania) and digital reproduction’s impact on artistic value. Her practice bridges gendered art histories and contested boundaries between human and algorithmic creativity. Awards & Grants: Great Meadows Foundation Professional Development Grant (2024) University of Louisville Inaugural Creative Works Award (2023) Pollock-Krasner Foundation Grant (2010) Geraldine R. Dodge Fellowship (2010) Advising & Labs: As MFA Director, she oversees WashU’s graduate visual art program. Her studio practice incorporates advanced digital fabrication tools and interdisciplinary collaborations. Upcoming projects include a 2024 solo exhibition at KMAC Museum exploring AI-driven “adversarial nature” themes. Exhibition Highlights: Recent shows include Living Arrangements (Kathryn Markel Fine Arts, 2023) and Adversarial Nature (Tinney Contemporary, 2023). Her work has been featured in Hyperallergic, Evergreen Review, and Majuscule magazine.

• Surgical Computing
• Simulation Science
• Virtual and Mixed Reality in Medicine
• +۶ مورد دیگر

Professor Fernando Bello holds the position of Professor of Surgical Computing and Simulation Science at Imperial College London's Department of Surgery and Cancer (Faculty of Medicine). He leads the Centre for Engagement and Simulation Science and directs the SiMMS research group, focusing on medical simulation and modeling. His career includes a PhD from Imperial College (1996), postdoctoral work at Guy's Hospital and the University of Kent, and roles as Lecturer in Electronic Engineering before rejoining Imperial in 2000. Education: PhD in Biomedical Systems, Imperial College London (1996) Postdoctoral Research Fellow at Guy's Hospital (1996-1998) Lecturer in Electronic Engineering at University of Kent (1998) Research Interests: Bello’s work bridges medicine, education, and technology. Key areas include virtual/mixed reality in surgical training, haptic feedback systems for medical simulations, and patient-specific surgical modeling. He pioneers innovations like robotic clinical examination tools and AI-driven surgical training platforms. His research emphasizes improving clinical education through immersive technologies and enhancing patient engagement via 3D imaging and VR. Publications Trends: Recent work focuses on surgical simulation validation (e.g., fracture models, anorectal exam tools), haptic interfaces for prosthetics and teleoperation, and VR applications in patient care. His articles highlight cross-disciplinary collaboration between engineering, computer science, and medicine. Affiliations & Leadership: Academic Co-director of Imperial’s MSc in Surgical Innovation, and collaborator with the Robotics Forum and Artificial Intelligence Network. He actively develops simulation-based training programs globally. Labs & Teams: Directs the SiMMS group, which specializes in modeling clinical processes and developing advanced simulators for surgical training. His team also explores distributed simulation for healthcare system optimization.

• Conducting Polymers
• Nanomaterials
• Electrofluidics
• +۵ مورد دیگر

Prof. Peter Innis is an Associate Professor at the University of Wollongong (UOW), affiliated with the Intelligent Polymer Research Institute (IPRI) and the Australian National Fabrication Facility (ANFF). He joined UOW in 1996 as an Associate Research Fellow after earning his PhD from the University of Technology Sydney (UTS). His research focuses on conducting polymers, electrofluidics, graphene composites, and advanced textile-based technologies. He has secured over $50 million in ARC grants since 1999 and currently leads the ANFF Materials Node, coordinating fabrication services nationwide. Prof. Innis has held two ARC Fellowships and is a Chief Investigator in the ARC Centre of Excellence for Electromaterials Science (ACES). His expertise spans electrochemical characterization, photoelectron transfer processes, and nanomaterial integration into devices. Recent work emphasizes electrofluidic separation technologies and wearable electrochemical sensors. Research interests include: conducting polymers, electrofluidics, graphene composites, 3D-printed materials, and textile electronics. He has pioneered innovations in textile-based microfluidics and electroosmotic pumps. His leadership roles include Associate Director of IPRI and Associate Dean (Research) at UOW's Australian Institute for Innovative Materials (AIIM). **Awards**: Australian Post-Doctoral Fellowship (1999), Queen Elizabeth II Fellowship (2003). **Grants**: 14 ARC grants, 2 ARC Centres of Excellence, and an NHMRC Development grant. His research teams focus on electrofluidic devices and sensors (EDS), combining 3D printing, advanced fibres, and textile architectures. **Labs/Teams**: IPRI, ANFF Materials Node, ACES CoE. Current projects involve neutron radiation shielding via additive manufacturing and electrofluidic cell culture integration.

Yue Wangمشاهده پروفایل

استاد

• Cooperative Control
• Human-Robot Collaboration
• Cyber-Physical Systems
• +۳ مورد دیگر

Dr. Yue Wang is a Professor and the Warren H. Owen - Duke Energy Professor of Engineering at Clemson University's Department of Mechanical Engineering, where she directs the I2R laboratory. She serves as an NSF program director and holds IEEE Senior Member and ASME Fellow distinctions. Her research focuses on cooperative control, human-robot collaboration, cyber-physical systems, and multi-agent systems, supported by NSF, AFOSR, NASA, and others. Dr. Wang earned her BS from Shanghai University (2005), MS and PhD from Worcester Polytechnic Institute (2008, 2011), and completed a postdoc at the University of Notre Dame (2011-2012). Her work emphasizes trust models, human-in-the-loop systems, and safety-critical applications like autonomous vehicles and manufacturing automation. Key contributions include formal verification frameworks, Bayesian trust models, and risk-aware decision-making algorithms. Awards: ASME Fellow (202?), IEEE Senior Member (202?). Funding: NSF, AFOSR, ARO, NASA EPSCoR, Clemson University. Active in IEEE committees, including leadership in the Manufacturing Automation and Robotic Control technical committee. Labs/Teams: I2R Laboratory (focusing on intelligent and integrated robotics systems).

Hudson Smithمشاهده پروفایل

استادیار

• Machine Learning
• Medical Imaging
• Quantum Physics
• +۵ مورد دیگر

Hudson Smith is an Assistant Professor in the Department of Mathematical and Statistical Sciences at Clemson University, College of Science. His research focuses on integrating domain knowledge with machine learning to address data-constrained problems in healthcare, forensics, and physics. He holds a PhD in theoretical atomic physics from Ohio State University, combining first-principles approaches with data-driven methods. Key areas of research include medical imaging analysis (e.g., ultrasound quality assessment), forensic decomposition modeling (geoFOR database collaboration), and AI detection of coordinated disinformation campaigns. His work bridges theoretical physics (quantum systems, cold atoms) with applied machine learning in healthcare and social media analysis. Publications highlight contributions to AI in trauma care, forensic science, and social media disinformation detection. Active collaborations span forensic science, biomedical informatics, and quantum physics. GitHub repositories showcase contributions to visualization tools (e.g., Schrödinger equation solvers, Voronoi-based image stylization).

• Fluid Dynamics
• Ocean Modelling
• Computational Mechanics
• +۶ مورد دیگر

Dr. Elnaz Naghibi is a Senior Lecturer in Mechanical Engineering at the University of East London, affiliated with the Research Institute of Architecture, Computing & Engineering. Her work bridges fluid dynamics, computational mechanics, and interdisciplinary engineering applications. Research Interests: Her primary research spans turbulent flows, ocean-atmosphere interactions, and geophysical fluid dynamics, with applied focus on reduced-order modeling, machine learning for jet flow analysis, and continuum robotics. Key themes include: Advanced numerical methods for ocean/climate systems (e.g., Southern Ocean jet dynamics) Data-driven approaches in aeroacoustics and high-Reynolds flows Nonlinear dynamics in materials and mechanical systems Publication Trends: Recent works emphasize machine learning integration in fluid dynamics (2022–2024), building on earlier foundations in spectral methods (2018–2019) and continuum robotics (2017–2020). Dominant fields include computational fluid dynamics (7/11 papers), geophysics (4/11), and robotics (3/11), reflecting strong cross-disciplinary collaboration.

Ehsan Esfahaniمشاهده پروفایل

دانشیار

• Artificial Intelligence in Engineering
• Human-Machine Interaction
• Robotics
• +۴ مورد دیگر

Ehsan Esfahani is an Associate Professor and Director of Graduate Studies in the Department of Mechanical and Aerospace Engineering at the University at Buffalo's School of Engineering and Applied Sciences. He is affiliated with the Stephen Still Institute for Sustainable Transportation and Logistics. His research focuses on AI-driven robotics, human-machine interaction, and bio-mechatronics systems. Education: PhD in Mechanical Engineering, University of California, Riverside (2012) MS in Electrical Engineering, University of California, Riverside (2012) MS in Mechanical Engineering, University of Toledo (2007) BS in Mechanical Engineering, Isfahan University of Technology (2004) Research Interests: Brain-computer interfaces for CAD/robotic systems Human-robot collaboration and neuroergonomics Bio-inspired robotics and tactile sensing Swarm intelligence and multi-agent systems Variable stiffness actuators for safe manipulation Key Contributions: Esfahani's work bridges AI with physical systems, emphasizing real-time human-in-the-loop control. Recent trends in his publications focus on scalable swarm robotics, human-swarm interaction dynamics, and adaptive gripper designs for confined environments. His neurophysiological approaches assess cognitive load in collaborative tasks, enhancing system safety and efficiency. Awards: American Power Public Associations DEED Scholarship (2012) UC Riverside Dissertation Year Fellowship (2011–2012) Lung-Wen Tsai Memorial Scholarship (2010) Advising & Labs: Directs the HILS Lab (Human-Inspired Learning Systems), exploring human-centered robotics. Active in grants focusing on AI-driven factories, cognitive modeling in surgery, and variable stiffness mechanisms. Collaborates on projects like SHaSTA (Human-Swarm Team Simulator) and MyoTrack rehabilitation systems. Labs & Teams: HILS Lab: Human-AI collaboration frameworks Stephen Still Institute: Transportation logistics and sustainability

• Formal Logic
• Cybersecurity
• Social Engineering
• +۷ مورد دیگر

Andreas Brännström is a postdoctoral fellow at the Department of Computing Science , Umeå University, Sweden. His research focuses on formal logic-based methods for modeling and verifying manipulation, deception, and influence in communication , with applications in cybersecurity and social engineering. He employs frameworks such as Answer Set Programming, Formal Argumentation, and Description Logic to analyze mental states, belief change, and dialogue strategies in autonomous systems. His work intersects artificial intelligence , computational ethics , and human-agent interaction . Key research themes include: Formal verification of deceptive communication Computational empathy modeling Trust-based argumentation systems Behavior change interventions for autism Human-aware planning in hybrid AI Cross-cultural affective knowledge representation Recent publications analyze manipulation dialogues , critical friend agents , and emotion-aware planning using formal methods. The research contributes to responsible AI and trustworthy human-agent collaboration . Current projects include strategic argumentation frameworks (2020-2024) and collaborative mixed-reality tools for autism support. He is affiliated with the Formal Methods for Trustworthy Hybrid Intelligence research group and contributes to Responsible Artificial Intelligence initiatives.

Farah Kandahمشاهده پروفایل

دانشیار

• Cybersecurity
• Internet of Things (IoT)
• Blockchain
• +۳ مورد دیگر

Farah Kandah is an Associate Professor in the Department of Computer Science and Software Engineering at Auburn University. Her research focuses on cybersecurity, IoT security, blockchain, trust management, and machine learning applications in networked systems. She leads initiatives in ethical hacking and quantum computing education, and has been awarded a $116K NSF grant to develop quantum computing curricula. Education: Ph.D. Computer Science, North Dakota State University M.S. Computer Science, University of Jordan B.S. Computer Science, The Hashemite University Research Highlights: Dr. Kandah's work addresses IoT security challenges through behavioral trust models, blockchain-based architectures, and machine learning-driven intrusion detection systems. She has pioneered hybrid testbeds like XiveNet and contributed to frameworks like Zero Trust+ and B2-C2 for scalable IoT security. Her research integrates hardware-software co-design principles to enhance resilience against advanced cyber threats. Grants & Awards: Recipient of a National Science Foundation grant (2023) for quantum education programs. Auburn's Cybersecurity programs under her contribution hold three National Centers of Academic Excellence designations (Cyber Research, Cyber Defense, Cyber Operations). Advising & Outreach: Advises the Auburn Ethical Hacking Club, which competes in national cyber competitions. Active in mentoring students through initiatives like the Computing Research Association's Outstanding Researcher Awards. Lab & Collaborations: Involved with the Center for Artificial Intelligence and Cybersecurity Engineering at Auburn. Research spans smart cities, connected vehicles, and secure SDN architectures.

Nick Nikiforakisمشاهده پروفایل

دانشیار

• Web Security
• Software Security
• Cybersecurity
• +۳ مورد دیگر

Nick Nikiforakis is an Associate Professor in the Department of Computer Science at Stony Brook University, with an affiliation to the National Security Institute. His research focuses on web security, privacy, software security, and intrusion detection, with particular emphasis on analyzing online ecosystems, domain squatting, honeypot deployment, and client-side defense mechanisms. He completed his PhD in Computer Science at KU Leuven (Belgium), and holds an MSc in Parallel and Distributed Systems and a BSc in Computer Science from the University of Crete, Greece. His work has been funded by NSF and ONR grants, including projects addressing vulnerability scanning, social engineering defenses, and mobile browser security. Nikiforakis' awards include a Distinguished Paper Award at NDSS 2017 and a Best Paper Award at ISC 2014. He teaches courses CSE 508 (Computer Security), CSE 509 (Advanced Topics in Security), and CSE 361 (Data Structures and Algorithms). His research explores cutting-edge threats like blockchain naming system abuse, cryptocurrency scams, and adversarial AI-driven misinformation campaigns.

Sascha-Dominik Dov Bachmannمشاهده پروفایل

استاد

• Hybrid Warfare
• Lawfare
• International Human Rights Law
• +۷ مورد دیگر

Professor Sascha-Dominik Dov Bachmann is a distinguished academic and former military officer specializing in international law and security studies. He currently serves as Professor in Law at the Canberra Law School and holds an Extraordinary Reader (Docent) in War Studies at the Swedish Defence University. Additional roles include Research Fellow at Stellenbosch University’s Faculty of Military Science and Fellow at NATO SHAPE for Hybrid War and Lawfare in the Asia-Pacific region until 2025. His operational military experience spans the Balkans and U.S. Marine Corps exchange programs, and he has worked across the U.S., Middle East, South Africa, and Europe over 20 years. LL.D (Doctor of Laws) - University of Johannesburg LL.M (Magister Legum) - Stellenbosch University State Exam (LL.B/LL.M equivalent) - Ludwig Maximilians Universität Munich Postgraduate Certificate in Learning and Teaching - University of Portsmouth His research bridges Hybrid Warfare , Lawfare , Cyber Threats , and International Human Rights Law . Key projects focus on countering disinformation, quantifying military readiness, and hybrid threats in the Asia-Pacific. His interdisciplinary work is cited by NATO and defense agencies, influencing policies on critical infrastructure protection, economic coercion, and cognitive warfare. Recent publications analyze China’s Arctic ambitions, AUKUS implications, and legal frameworks for countering hybrid threats. Professor Bachmann has secured funding from NATO , South African Department of Defence , and U.S. Department of Defense . He mentors HDR students on topics like human rights norms in Islamic traditions and renewable energy legislation in the Gulf , contributing to policy debates through outlets like Pacific Affairs and Australian Outlook .

Terence Broadمشاهده پروفایل

مدرس ارشد

• Generative AI
• Computational Creativity
• Artistic Applications of Machine Learning
• +۵ مورد دیگر

Terence Broad is a Senior Lecturer at the Creative Computing Institute, University of the Arts London, and Acting Course Leader of the MSc Applied Machine Learning for Creatives. He is currently completing a PhD at Goldsmiths, University of London. His work bridges art and technology, focusing on generative AI, computational creativity, and the use of machine learning as artistic materials. His research has been exhibited globally at venues like The Whitney Museum of American Art and SIGGRAPH conferences. Education: MSci Creative Computing from Goldsmiths, University of London (2012–2016). Research interests include expressive manipulation of deep generative models, exploring the latent possibilities of 'black-box' systems, and ethical considerations in AI art. He has pioneered methods like 'Network Bending' for creative model customization. Key achievements include winning the ICCV Computer Vision Art Gallery Grand Prize (2019) and serving on the SIGGRAPH jury (2021). His work is part of Geneva's contemporary art collection and has been featured in media like The Independent and Vox. Professional activities include organizing conferences like IGGI 2020 and reviewing for journals like Leonardo and ACM Transactions on Image Processing. He actively participates in exhibitions, artist talks, and academic workshops.

Scott Noklebyمشاهده پروفایل

استاد

• Robotics Engineering
• Mechatronics Systems
• Automation Technologies
• +۷ مورد دیگر

Dr. Scott Nokleby is an Associate Dean, Academic and Professor in the Department of Automotive and Mechatronics Engineering at the University of Ontario Institute of Technology. He holds a PhD in Mechanical Engineering from the University of Victoria (2003), and has over two decades of academic leadership and research experience. His primary roles include academic administration and advancing robotics and mechatronics research. Education: PhD (Mechanical Engineering, UVic, 2003), MASc (Mechanical Engineering, UVic, 1999), BEng (Mechanical Engineering with Co-op, UVic, 1997). Research interests focus on advanced robotics topics including parallel manipulators, mobile-manipulator systems, kinematic redundancy analysis, and autonomous systems. His work emphasizes practical applications such as radiation mapping robots, perching drones, and robotic hazard management. Notable contributions include optimal design methodologies for mechanisms and control systems for human-robot interaction. Publications reflect expertise in robotics systems, mechatronics, and nuclear engineering applications. Recent work explores multi-robot task allocation, autonomous navigation, and advanced control algorithms. Awards: Fellow of ASME (2022) Fellow of CSME (2016) CSME Best Paper Award (2014) UOIT Research Excellence Award (2008) CSME I.W. Smith Award (2007) Teaches graduate courses in advanced robotics, mobile robotic systems, and mechanism design. Active in academic administration, he bridges teaching innovation with engineering education through projects like tablet computing integration in design courses. Labs/Teams: Leads robotics research initiatives focused on autonomous systems development, with collaborations spanning nuclear safety, mining automation, and aerospace applications.