جست‌وجوی استاد و پژوهشگر

• Cognitive Science
• Psychology
• Computational Modeling
• +۶ مورد دیگر

Andrew Perfors is a Professor of Psychology at the University of Melbourne, leading the Computational Cognitive Science Lab and directing the Complex Human Data Hub. His research focuses on quantitative approaches to higher-order cognition, including concepts, language, decision-making, and misinformation dynamics. He holds a PhD from MIT and degrees from Stanford University. Education: PhD in Brain & Cognitive Sciences, Massachusetts Institute of Technology (2008) MA in Linguistics, Stanford University (2000) Bachelor of Science in Symbolic Systems, Stanford University (1999) Research Interests: He investigates computational models of cognition, cultural and social evolution, and the spread of misinformation. Recent work emphasizes the cognitive mechanisms underlying inductive reasoning, sampling assumptions, and trust in information. Key Projects: Understanding Information and Trust: From the Individual to the Population (2018–2025) Bridging the Meaning Gap: Computational Approach to Semantic Variation (2023–2027) Awards: Recipient of multiple best paper awards for contributions to cognitive science and computational linguistics. Labs & Groups: Leads the Complex Human Data Hub and co-leads the Computational Cognitive Science Lab, focusing on interdisciplinary research in human behavior and data science.

Mark D. Grossمشاهده پروفایل

استاد

• Design Methods
• Modular Robotics
• Computational Design
• +۵ مورد دیگر

Mark D. Gross is a Professor of Computer Science and Director of the ATLAS Institute at the University of Colorado Boulder, where he leads an interdisciplinary hub for creativity and invention. His academic journey began at MIT with BS and PhD degrees, followed by faculty roles at Carnegie Mellon University (2004-2013), University of Washington Seattle (1999-2004), and CU-Boulder (1990-1999, 2014-present). As co-founder of Modular Robotics Incorporated and Blank Slate Systems LLC, he bridges academia and entrepreneurship. Education: BS and PhD in Computer Science from MIT Gross’ research spans design methods, modular robotics, computational design tools, and tangible interaction. He pioneered sketch recognition software like 'The Electronic Cocktail Napkin' and explores physical computing through projects such as shape-changing interfaces, interactive construction kits, and augmented reality systems. His work integrates IoT, digital fabrication, and educational technology. Recent publications highlight innovations in AR/VR collaboration, shape-changing robotics, and interactive fabrication. Key themes include climate communication through data physicalization, AI-driven creative systems, and soft robotics for dynamic interfaces. Despite no explicit awards listed, his career demonstrates sustained impact through ACM conference leadership (Creativity and Cognition 2009, TEI 2011) and industry partnerships. Gross’ prior industry experience includes positions at Atari Cambridge Research and Logo Computer Systems. His lab at ATLAS fosters radical creativity through projects like PaperMech, DynaBlock, and WearAir, emphasizing hands-on learning and cross-disciplinary experimentation.

Irina Rishمشاهده پروفایل

استاد

• Machine Learning
• Neural Scaling Laws
• Emergent Behaviors in AI
• +۱۳ مورد دیگر

Irina Rish is a Full Professor at the Université de Montréal and a core academic member of Mila – Quebec Artificial Intelligence Institute, where she leads the Autonomous AI Lab. She holds a Canada Excellence Research Chair (CERC) and a CIFAR AI Chair, reflecting her leadership in foundational AI research. Her work is supported by major initiatives, including the U.S. Department of Energy’s INCITE project on Summit and Frontier supercomputers. PhD in AI, University of California, Irvine MSc in AI, University of California, Irvine MSc in Applied Mathematics, Moscow Gubkin Institute Her research focuses on machine learning, neural scaling laws, emergent behaviors in foundation models, continual learning, robustness, and neuroscience-inspired AI . She explores how AI systems can become more general, flexible, and aligned with human cognition. Her recent work investigates training dynamics in large language models, efficient pruning techniques, and the development of time-series foundation models. The analysis of her recent publications reveals a strong focus on scaling behaviors, continual adaptation, and robustness in AI systems . Her work spans theoretical understanding of training dynamics (e.g., zero-sum learning), practical optimization methods, and applications in climate modeling and mental health. She emphasizes open science, leading open-source projects and co-founding Nolano.ai to build efficient, compressed foundation models. Canada Excellence Research Chair (CERC) CIFAR AI Chair IBM Eminence & Excellence Award (2018) IBM Outstanding Innovation Award (2018) IBM Outstanding Technical Achievement Award (2017) IBM Research Accomplishment Award (2009) Irina Rish advises a large group of PhD and Master’s students across Université de Montréal, McGill, and Concordia. She leads major research grants and collaborates internationally on HPC-based AI research. She is also the co-founder and CSO of Nolano.ai, driving innovation in efficient AI systems. She leads the Autonomous AI Lab, which focuses on building large-scale foundation models, understanding neural scaling laws, and developing bio-inspired learning systems. She actively organizes reading groups on scaling, continual learning, and out-of-distribution generalization, fostering a collaborative research environment.

Stéphane Doncieuxمشاهده پروفایل

استاد

• Cognitive Robotics
• Developmental Robotics
• Evolutionary Robotics
• +۱۶ مورد دیگر

Stéphane Doncieux is a University Professor in Computer Science at Sorbonne University, where he is affiliated with the Institute of Intelligent Systems and Robotics (ISIR), a joint research laboratory with CNRS. Since January 2024, he has served as Director of ISIR, following a term as Deputy Director from 2019 to 2023. He leads the ASIMOV research team and is based at the Pierre and Marie Curie Campus in Paris. His primary research interests lie in cognitive and developmental robotics, with a strong focus on open-ended learning, evolutionary algorithms, and adaptive systems. He investigates how robots can autonomously learn diverse skills through mechanisms such as novelty search, quality-diversity optimization, and intrinsic motivation. His work bridges theoretical foundations in artificial life and practical applications in robotic manipulation, perception, and control. The recent publications highlight a consistent trend in advancing robotic learning under sparse rewards and in open-ended environments. Key themes include quality-diversity optimization for grasping, state representation learning, sim-to-real transfer, and the development of behavioral repertoires. These works are published in high-impact journals such as IEEE Transactions on Robotics, Evolutionary Computation, and Frontiers in Robotics and AI. Coordinator, DREAM FET H2020 project (2015–2018) Principal Investigator, ANR projects on Creative Adaptation by Evolution, Learning Movement Skills, and Grasping with Multimodal Feedback Involved in European initiatives including VeriDREAM and HumanE-AI-Net He has supervised numerous PhD and Master’s students, including Leni Le Goff, Giuseppe Paolo, Alban Laflaquière, and Achkan Salehi, often in collaboration with leading researchers like Olivier Sigaud and Jean-Baptiste Mouret. He teaches computer science and robotics at both undergraduate and graduate levels at Sorbonne University. Doncieux has been instrumental in shaping research directions in evolutionary and developmental robotics, notably through his leadership in the IEEE Task Force on Evo-Devo-Robotics and his editorial contributions. His lab, ASIMOV, fosters interdisciplinary research integrating computer science, neuroscience, and engineering to create more autonomous and intelligent robotic systems.

James C. Geeمشاهده پروفایل

استاد

• Biomedical Image Analysis
• Medical Imaging Computing
• Image Segmentation
• +۵ مورد دیگر

James C. Gee is a Professor of Radiologic Science in Radiology at the University of Pennsylvania's Perelman School of Medicine. He serves as Director of the Penn Image Computing and Science Laboratory and Co-Director of the Translational Biomedical Imaging Center , with affiliations in Bioengineering and Applied Mathematics graduate groups. His research focuses on biomedical image analysis, specialization in segmentation, registration, and morphometry applied to neurodegenerative diseases and multi-organ systems. Education : B.S. in Computer Science/Electrical Engineering (University of Washington, 1987), Ph.D. in Computer and Information Science (University of Pennsylvania, 1996) Research : Quantitative medical imaging methods, brain connectomics, neurodegeneration mapping, and translational imaging technologies Publications : 15+ recent works on AI-driven image analysis for Alzheimer's disease, cardiac amyloidosis, and radiomics applications Leadership : Directs MSE-DS Online Degree Program, co-chairs Radiology DCOAP Committee, and founded RISE (Radiology Initiative to Support Inclusive Excellence) His laboratory develops advanced computational tools like ITK-SNAP for biomedical imaging, with applications in both in vivo clinical imaging and ex vivo histology . The work spans cross-disciplinary collaborations in computer science, neuroscience, and clinical medicine.

William Wadsworthمشاهده پروفایل

استاد

• Photonics
• Optical Fibres
• Photonic Crystal Fibres
• +۵ مورد دیگر

William Wadsworth is Professor of Physics at the University of Bath, affiliated with the Centre for Photonics and Photonic Materials. His research focuses on photonic crystal fibres (PCFs) and hollow-core fibre technologies, with applications spanning quantum information, medical imaging, and fundamental metrology. Research Expertise Professor Wadsworth designs and fabricates microstructured optical fibres enabling unprecedented light control. His work centers on: Development of hollow-core anti-resonant fibres for deep ultraviolet guidance Supercontinuum generation across UV-to-infrared spectra Medical applications including UV light therapies and malaria diagnostics Quantum optical systems using alkali-metal vapours in fibres Research Impact His recent publications (2024-2025) demonstrate cutting-edge advances in hollow-core fibre technology for deep-UV applications and medical diagnostics. Key trends include resonance-free supercontinuum generation, integration of AI with photonics for malaria detection, and novel fibre designs enabling quantum applications. These innovations directly support UN Sustainable Development Goals in health and clean energy. Grants and Supervision Professor Wadsworth leads 24 research projects including: U-Care (2021-2026): Deep Ultraviolet Light Therapies (EPSRC) International Collaboration Awards (2020-2023): Clean Air (Royal Society) Plasmon-Enhanced Alkali-metal Vapours (2017): Quantum optical applications He has supervised 18 doctoral students and currently accepts new PhD candidates in photonics and fibre optics. Research Environment As core faculty in Bath's Centre for Photonics and Photonic Materials, he collaborates internationally with institutions in quantum optics, air pollution analysis, and medical instrumentation, maintaining active partnerships across Europe and Asia.

Christof Lutterothمشاهده پروفایل

استاد

• Human-Computer Interaction
• Virtual Reality
• Eye-Gaze Interaction
• +۵ مورد دیگر

Christof Lutteroth is a Professor in the Department of Computer Science at the University of Bath and Director of the REal and Virtual Environments Augmentation Labs (REVEAL). His work focuses on Human-Computer Interaction (HCI) with emphasis on eye-gaze interaction and virtual reality (VR), particularly for health, exercise, and learning applications. He leads multiple research projects funded by organizations like EPSRC, The British Academy, and The Royal Society. Research Interests include developing gaze-controlled interfaces, immersive VR systems, and adaptive UI/UX for fitness and cognitive training. He explores affective design tools, emotion recognition in VR exergaming, and biometric data analysis for health applications. Recent Publications highlight advancements in gaze-based text entry, emotion measurement in VR, AI-driven UI development, and cross-European XR innovation networks. His work spans from foundational HCI methodologies to applied projects in rehabilitation and immersive learning. Grants include EPSRC IAA, British Academy, and Royal Society funding for projects like TapGazer, Hyper-immersive XR, and Affective Design Tools for VR. He collaborates with institutions across Europe through the EMIL project. Laboratory : REVEAL Lab at the University of Bath drives research in immersive technologies, motion analysis, and augmentation of human interaction with digital environments.

• Medical Imaging
• Machine Learning
• Radiology
• +۳ مورد دیگر

Sumit Chopra is an Associate Professor at the Grossman School of Medicine , affiliated with the Department of Radiology at New York University. His work focuses on integrating machine learning and artificial intelligence with medical imaging to enhance diagnostic accuracy and clinical decision-making. Research interests include: Deep learning applications in prostate cancer imaging and MRI reconstruction Development of open-access medical imaging datasets (e.g., FastMRI Prostate) Improving biopsy decision strategies via representation learning AI-driven Alzheimer's disease risk prediction using electronic health records Advancements in radiologic assessment for pancreatic cystic lesions Email: Sumit.Chopra@nyulangone.org

• Magnetic Resonance Imaging (MRI)
• Functional MRI (fMRI)
• Biomedical Imaging Physics
• +۶ مورد دیگر

Dr. Gary Glover is a Professor of Radiology (Radiological Sciences Lab) at Stanford University , with courtesy appointments in Psychology and Electrical Engineering. His work focuses on the physics and mathematics of MRI, particularly rapid scanning methods using spiral k-space trajectories for functional brain imaging and multimodal neuroimaging (fMRI/EEG/fPET/fNIRS) combined with neuromodulation techniques like TMS and transcranial ultrasound. Academic Appointments: Radiology, Psychology, Electrical Engineering Professional Affiliations: Bio-X, Stanford Cancer Institute, Wu Tsai Neurosciences Institute Research Interests include: Development of blood oxygen level-dependent (BOLD) and viscoelastic contrast in MRI Functional MR Elastography for brain activation mapping Optimization of MR-ARFI for transcranial ultrasound guidance Automated spinal cord segmentation (EPISeg) using machine learning Scientific Awards : National Academy of Engineering (2013) Gold Medal, ISMRM (2000) Steinmetz Award, General Electric (1985) Lauterbur Lecture, ISMRM (2018) Recent Publications analyze: Fast fMRI sampling and spurious signal correction Dissociated patterns in default mode network anti-correlations Neural correlates of collaborative behavior in triadic fMRI Salience network contributions to depression pathophysiology

• Automated Transportation Systems
• Connected Vehicles
• Electric Vehicles
• +۳ مورد دیگر

Dr. Xiaopeng Li is the Harvey D. Spangler Professor in the Department of Civil and Environmental Engineering at the University of Wisconsin-Madison, with an affiliation in the Department of Electrical and Computer Engineering. He leads the USDOT Rural Autonomous Vehicle Program and previously directed the National Institute for Congestion Reduction. He earned his B.S. in Civil Engineering from Tsinghua University (2006), M.S. in Civil Engineering (2007), M.S. in Applied Mathematics (2010), and Ph.D. in Civil Engineering (2011) from the University of Illinois at Urbana-Champaign. His research focuses on modeling and field experiments for connected, electric, and automated vehicles (CAVs), infrastructure systems analysis, and interdependent network modeling. He has pioneered physics-enhanced machine learning frameworks for vehicle control and developed simulation tools for CAV deployment. His 2025-2024 publications highlight advancements in Connected vehicle trajectory modeling Energy consumption optimization Edge computing for autonomous operations Residual learning control systems Equity analysis in AV deployment Communication technologies for V2X Awards include: TRB Best Paper Award (2025) NSF CAREER (2015) ASCE Fellow (2024) IEEE Senior Member (2022) Multiple institution-specific fellowships He has advised 15+ graduate students, secured $35M+ in grants from NSF, USDOT, and industry partners, and chairs the IEEE ITSS Emerging Transportation Technology Testing committee. His work addresses real-world AV implementation, safety validation, and sustainable transportation systems.

Kristian J. Hammondمشاهده پروفایل

استاد

• Artificial Intelligence
• Natural Language Generation
• Narrative Generation
• +۷ مورد دیگر

Kristian J. Hammond is the Bill and Cathy Osborn Professor of Computer Science at Northwestern University's McCormick School of Engineering. He directs both the Master of Science in Artificial Intelligence Program and the Center for Advancing Safety of Machine Intelligence (CASMI). His research focuses on artificial intelligence, natural language generation, narrative generation, conversational interfaces, and ethical AI applications across domains like law, education, and journalism. Hammond co-founded Narrative Science, leveraging AI for automated journalism from data. Education: PhD, MS, and BA in Philosophy (all from Yale University). His work spans technical innovation and societal impact, with notable contributions to AI transparency, bias mitigation, and machine learning ethics. Hammond has authored influential articles on AI governance, conversational systems, and the future of work in an automated economy. His leadership roles emphasize interdisciplinary collaboration between computer science, business, and humanities. Research highlights include developing AI systems that enhance human capabilities, exploring ethical frameworks for machine intelligence, and advancing AI safety through initiatives like CASMI. He frequently engages in public discourse via TEDx talks and commentaries on AI's societal implications, emphasizing the need for human-centered technology design.

Sonny Phamمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Computer Vision
• Data Mining
• +۳ مورد دیگر

Associate Professor Sonny Pham leads research in artificial intelligence at Curtin University's School of EECMS. His work balances theoretical foundations with practical applications in computer vision, data mining, and deep learning. As head of the IAMAI research group, he collaborates with industry partners on security systems, healthcare AI, and sustainable technologies. His research explores: Computationally efficient deep learning architectures Compressed sensing for high-dimensional data Robust statistical methods for real-world problems Applications in computer vision and industrial automation Recent publications demonstrate a focus on medical imaging interpretation and efficient neural networks, with applications spanning radiology report generation, semantic segmentation for autonomous systems, and cybersecurity. His team's work consistently bridges theoretical AI advancements with industrial applications. Honors include: Multiple WANMA Awards (2021-2024) for industry-impactful research INCITE Award for social impact technology (2024) IEEE Young Author Best Paper Award (2010) Over $5M in competitive research funding including MRFF and DFAT grants He leads the IAMAI research group with 12+ graduate students and coordinates Curtin's Master of Artificial Intelligence program. Industry collaborations include Alcoa Australia, iCetana, and HyprFire.

• AI-based feedback
• Computational thinking education
• Game-based learning
• +۷ مورد دیگر

Dr. Jingyun Wang is an Assistant Professor in the Department of Computer Science at Durham University. Previously, she held an Assistant Professor position at Kyushu University, Japan. Her primary affiliations include the Centre for Neurodiversity & Development and the Artificial Intelligence and Human Systems Group (AIHS), as well as the Pedagogical Innovation in Computer Science Group (PICS). She is a Fellow of the Higher Education Academy and has led or contributed to research projects funded by JSPS, JST, NICT, Innovate UK, and industry partners. Her research focuses on AI-driven educational technologies, including AI-based feedback systems, computational thinking education, game-based learning, and ontology techniques. She actively contributes to editorial boards (e.g., Computers & Education: Artificial Intelligence ) and serves as a conference chair for AIED, ICCE, and LTLE. Current research includes adaptive learning systems for mathematics education, serious games for cybersecurity training, and visualization tools for e-learning. Her scientific contributions span over 50 peer-reviewed publications, with recent work emphasizing learning analytics, multimodal systems, and digital health interventions. She advises multiple PhD students and mentors in professional recognition pathways. Key projects include developing the BETTER speech training system, the MEMORABLE cybersecurity game framework, and ontology-based language learning platforms.

Rathna Ramanathanمشاهده پروفایل

استاد

• Communication Design
• Typography
• Intercultural Communication
• +۵ مورد دیگر

Dr. Rathna Ramanathan is a leading academic and practitioner in intercultural communication and alternative publishing. Currently serving as Provost of Central Saint Martins and UAL Executive Dean for Global Affairs , she has previously held deanships at Central Saint Martins and the Royal College of Art. Based in London but originally from Chennai, India, her work bridges South Asian and global design practices. University of Reading - PhD in Typography and Graphic Communication Central Saint Martins - MA in Communication Design University of Madras - BA Fine Art Her research focuses on intercultural communication and alternative publishing in the Global South, examining how marginalized voices can be amplified through design. She explores the tension between tangible/intangible heritages and contemporary design, and investigates how form, media, and content interact in addressing social/political issues. Recent publications highlight her design research trends in decolonial publishing, critical typography, and intercultural book design. As a design educator , she emphasizes listening, cross-cultural learning, and sustainable practices. Her supervision includes postgraduate research students working on topics like female printers in India, exhibition design, and architectural lettering. Key scientific collaborations include major projects with Tara Books (international design awards), British Council-funded initiatives (Crafting Futures, Going Global Partnership), and the Murty Classical Library of India (Harvard University Press partnership). She consults on Indic typeface design with Adobe and Monotype. Her design lab at Central Saint Martins (M9Design) works with international networks of editors, translators, and type designers. Current team projects focus on digital/print transitions, bilingual typography, and preserving endangered typographic practices through innovative publishing formats.

Matthew Holdenمشاهده پروفایل

دانشیار

• Surgical Data Science
• Machine Learning
• Computer-Assisted Surgery
• +۳ مورد دیگر

Matthew Holden is an Associate Professor in the School of Computer Science at Carleton University. He holds a PhD (2018) and MSc (2014) from Queen's University and a BScH (2012) from Western University. His research focuses on Surgical Data Science, applying machine learning to surgical time-series data from operating rooms and simulations to improve patient outcomes and surgical training. Key areas include real-time decision support, performance assessment, and surgical efficiency through domain-knowledge integration. Research interests emphasize machine learning for surgical workflows, skill assessment via sensor data (e.g., motion tracking, EEG), and computer-assisted interventions. Notable work includes automated proficiency evaluation in cataract surgery, ultrasound-guided procedures, and neurosurgical training. His contributions span medical robotics, surgical education, and clinical decision support systems. Publications highlight advancements in surgical workflow anticipation, tool detection, and skill metrics across domains like ophthalmology, emergency medicine, and neurology. Holden advocates for interdisciplinary approaches combining computational methods with clinical expertise to enhance healthcare delivery.