جست‌وجوی استاد و پژوهشگر

Matt Bridgeمشاهده پروفایل

استاد

• Coaching
• Applied Sports Science
• Skill Development
• +۷ مورد دیگر

Professor Matt Bridge is a faculty member at the University of Birmingham, serving as Professor of Coaching & Applied Sports Science and Deputy Head of the School of Sport, Exercise and Rehabilitation Sciences. He leads the school’s international strategy and contributes significantly to education and research leadership. PhD in Sport and Exercise Sciences BSc in Sport and Exercise Sciences His research focuses on applied coaching, skill development, and athlete development, with strong emphasis on ecological validity in real-world settings. He investigates talent pathways, coach-athlete interactions, and the integration of science in coaching practice. His recent publications span topics in football and golf, particularly examining practice design, technical development, and biomechanical analysis. Key trends include isolated practice in academies, strength interventions in golf, and skill variability across expertise levels. Professional affiliations include: British Association of Sport and Exercise Sciences European College of Sports Science World Scientific Congress of Golf He supervises PhD students, contributes to undergraduate and postgraduate teaching, and has consulted for the British Olympic Association, European Tour, and various national sports bodies. He also serves as Director of Golf for University of Birmingham Sport and Chair of the British Universities and Colleges Golf. His work bridges academic research and practical application in elite and amateur sport settings.

Imad Aghaمشاهده پروفایل

دانشیار

• Photonics
• Quantum Optics
• Nanophotonics
• +۷ مورد دیگر

Imad Agha is an Associate Professor with a joint appointment in the College of Arts and Sciences (Physics) and the School of Engineering (Department of Electro-Optics and Photonics) at the University of Dayton. He is a full-time faculty member actively engaged in cutting-edge research in photonics, quantum optics, and nanomaterials. His research interests include: Photonics and integrated photonic circuits Phase change materials (e.g., GST, Sb2Se3) for optical switching and memory Orbital angular momentum and optical vortex beams Metasurfaces and spatially variant photonic crystals Infrared detection using hyperdoped silicon Ultrafast and real-time spectroscopy GeSn-based optoelectronic devices His recent publications (2023–2025) demonstrate a strong focus on reconfigurable optical devices, tunable mid-infrared filters, quantum photonic transceivers, and advanced spectroscopy techniques. The work leverages machine learning, nanofabrication, and novel materials to enable next-generation photonic systems for communication, imaging, and sensing. Key themes include energy efficiency, ultrafast response, and chip-scale integration. Scientific awards are not listed in the provided text. Dr. Agha advises graduate students and likely leads a research group involved in experimental and theoretical photonics. His work is supported by grants related to materials development, optical device engineering, and quantum technologies, though specific grants are not listed. He collaborates across engineering and physics disciplines, particularly in the development of hybrid photonic systems. His research is conducted within advanced photonics and nanofabrication laboratories at the University of Dayton, focusing on optical characterization, device testing, and materials synthesis.

Marta Ruiz Costa-Jussàمشاهده پروفایل

استاد

• Machine Translation
• Natural Language Processing
• Artificial Intelligence
• +۶ مورد دیگر

Marta Ruiz Costa-Jussà is a Professor at the Faculty of Informatics of Barcelona (FIB), part of the Universitat Politècnica de Catalunya · BarcelonaTech (UPC). She is affiliated with the Department of Computer Science and holds additional teaching roles at the Escola Tècnica Superior d'Enginyeria de Telecomunicació de Barcelona (ETSETB). She is also the academic co-director of the postgraduate program Artificial Intelligence with Deep Learning at UPC School. Her research is conducted through key UPC research groups: Intelligent Data Science and Artificial Intelligence (IDEAI), the Center for Technologies and Applications of Language and Speech (TALP), and the Speech Processing Group (VEU). Her research focuses on advancing machine translation through deep learning, particularly in multilingual and low-resource settings. She investigates neural machine translation (NMT) systems that use intermediate mathematical representations (interlingua) to improve efficiency and inclusivity across majority and minority languages. A significant emphasis of her work is on ethical AI, aiming to detect and mitigate biases in translation systems. She is also pioneering research in automatic speech translation, a domain not yet fully mastered by major tech companies. Her recent publications reflect a strong trajectory in neural machine translation, multilingual representation learning, speech-to-speech translation, and ethical considerations in AI. The research trends show a consistent focus on inclusivity, efficiency, and robustness in language technologies, with applications spanning text, voice, and cross-lingual understanding. Scientific Awards: ERC Starting Grant (€1.5 million) for the LUNAR project Google Faculty Research Award (2019) Google Faculty Research Award (2020) She has secured significant research funding, notably the ERC Starting Grant, which supports her vision for lifelong universal language representation. Her advising likely includes graduate students in AI and NLP, though specific names are not listed. She has collaborated internationally with institutions such as LIMSI-CNRS (France), University of São Paulo (Brazil), Infocomm Research Institute (Singapore), National Polytechnic Institute of Mexico, and the University of Edinburgh (UK). She is a core member of several research teams: the IDEAI research center, TALP, and the VEU group. These labs focus on cutting-edge AI, data science, language technologies, and speech processing, providing a rich interdisciplinary environment for her work on inclusive and ethical machine translation systems.

• Journalism
• Media Pluralism
• Disinformation Studies
• +۴ مورد دیگر

Jaime Suau Martínez serves as an Associate Lecturer at Ramon Llull University's Blanquerna School of Communication and International Relations, where he leads the DIGILAB research group focused on media strategy and regulation. His academic profile is anchored in contemporary media challenges including AI-driven journalism, disinformation ecosystems, and European media pluralism frameworks. His research interests span Journalism , Media Pluralism , and Disinformation Studies , with particular emphasis on narrative analysis in hybrid media environments and Spanish political communication contexts. Current projects examine trust dynamics in AI news consumption, cross-national press freedom threats, and regulatory responses to digital platform dominance. Recent publications reveal a strong focus on narrative-based disinformation analysis , comparative press freedom metrics , and cross-lingual detection methods for low-resource languages. His work demonstrates increasing engagement with European Commission initiatives through projects like MC4 and DISINFTRUST, reflecting growing influence in media policy circles. As Principal Investigator for 17 research projects including the EU-funded MC4: Media Councils in the Digital Age (2023-2025) and DISINFTRUST: Disinformation & Trust (2023-2024), he directs substantial collaborative efforts involving researchers from multiple European institutions. His DIGILAB research group serves as the operational hub for these initiatives, focusing on practical regulatory solutions for contemporary media challenges.

• Architectural Science
• Urban Planning
• Building Technology
• +۵ مورد دیگر

Wang Wei is an Associate Professor and Doctoral Supervisor at the Institute of Building Technology and Science, School of Architecture, Southeast University. He obtained his bachelor's degree in Architectural Environment and Energy Engineering from Huazhong University of Science and Technology in 2014 and completed his Ph.D. in Architecture and Civil Engineering at City University of Hong Kong in 2018. From 2017 to 2018, he served as a visiting scholar at the Department of Building Technology, Lawrence Berkeley National Laboratory, USA. Education Bachelor's: Architectural Environment and Energy Engineering, Huazhong University of Science and Technology (2014) Ph.D.: Architecture and Civil Engineering, City University of Hong Kong (2018) His research focuses on urban-block-building energy modeling , urban energy system planning , and low-carbon cities . Additional technical interests include machine learning applications in environmental modeling, stereo matching algorithms, and remote sensing image analysis. He has published 34 SCI/SSCI papers, with 23 as first or corresponding author. Wang Wei serves as a youth editorial board member for the SCI journal Building Simulation , Review Editor for Frontier of Built Environment , and Founding Editor of the Urban Studies section in Current Social Sciences . He has secured multiple national and provincial research grants including the National Natural Science Foundation of China and National Key R&D Program sub-projects. Scientific Awards & Roles National Natural Science Foundation of China - Principal Investigator National Key R&D Program - Sub-Project PI Jiangsu Province Natural Science Foundation Nanjing Science and Technology Innovation Project Building Simulation Journal - Youth Editorial Board Frontier of Built Environment - Review Editor Current Social Sciences - Urban Studies Founding Editor

Charles Markhamمشاهده پروفایل

دانشیار

• Computer Science
• Biomedical Engineering
• Machine Vision
• +۵ مورد دیگر

Dr. Charles Markham is an Associate Professor in the Department of Computer Science at Maynooth University's Faculty of Science & Engineering. He graduated with a degree in Applied Physics from Dublin City University and earned his PhD in element specific imaging in computerised tomography. His research spans novel imaging systems, biomedical instrumentation, and human-computer interaction with a strong focus on brain-computer interfaces and motion capture technologies. Research Affiliations: Hamilton Institute, ALL Institute Teaching: Robotics, Computer Graphics, Advanced Computer Architecture Professor Markham's research interests center on novel imaging technologies including coded aperture imaging and wide-baseline stereo systems, motion capture and wearable computing with applications in rehabilitation, and mobile machine vision for driving simulation and augmented reality. His work with the Mathematics and Statistics Ecology group demonstrates interdisciplinary interests in ecological modelling . His publication record shows consistent contributions to brain-computer interfaces (2007-2011), driver behavior analysis (2014-2021), motion capture systems (2006-2009), and optical imaging techniques (2001-2008). The research spans multiple disciplines including neuroscience, biomedical engineering, and ecological mathematics. He has supervised several graduate students including D. Kelly (2009 thesis on sign language recognition) and J. Foody (2007 thesis on motion capture biofeedback systems). His collaborations extend across institutions with partnerships at TU Dublin and University College Dublin.

Recep Firat Cekinelمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Multimodal Fact-Checking
• Explainable AI
• +۷ مورد دیگر

Recep Firat Cekinel is a Turkish NLP researcher who recently obtained his Ph.D. in Computer Engineering from Middle East Technical University (METU). He spent 13 months as a visiting predoctoral researcher at the University of Tübingen and is currently a researcher on the EU-funded EXA4MIND project, where he develops NLP pipelines that convert natural language into database queries using large language models. His research focuses on responsible, scalable AI systems and bridges foundational NLP work with real-world applications. Education: Ph.D. in Computer Engineering, Middle East Technical University (METU), Türkiye Visiting Predoctoral Researcher, University of Tübingen, Germany (13 months) Research Interests: Dr. Cekinel’s work spans natural language processing , multimodal fact-checking , explainable AI , and large language models . He is particularly interested in building responsible and scalable AI systems that integrate foundational research with practical deployments, such as natural-language interfaces for high-performance computing environments. Recent Publication Trends: His 2025 publications reveal a concentrated effort on multilingual and multimodal fact-checking , satire-style debiasing , and NL-to-database-query generation . Earlier work explores graph-based event extraction , Turkish irony detection , and cultural-heritage text mining , demonstrating a trajectory from low-resource Turkish NLP toward globally applicable, responsible-AI systems. Contact & Code: Email: rfcekinel@ceng.metu.edu.tr Office: METU Computer Eng. Dept. A-206, 06800 Ankara, Turkey Phone: +90-(312)-210-5593 GitHub: firatcekinel Google Scholar: profile available

Jivko Sinapovمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Developmental Robotics
• Human-Robot Interaction
• +۴ مورد دیگر

Jivko Sinapov is an Associate Professor with dual appointments in the Department of Computer Science and Department of Mechanical Engineering at Tufts University's School of Engineering. He also serves as a CEEO Fellow at the Center for Engineering Education Outreach. His research focuses on enabling physical robots to operate and learn in human-inhabited environments through developmental approaches. Education: PhD in Computer Science and Human-Computer Interaction, Iowa State University (2013) BSc in Computer Science and Mathematics, University of Rochester (2005) Professor Sinapov's research centers on Artificial Intelligence, Developmental Robotics, Computational Perception, and Human-Robot Interaction . His work addresses fundamental questions about implementing intelligence in physical robots, with emphasis on enabling extended operation in human environments. His laboratory develops methods for behavioral object exploration, multi-modal perception, and knowledge transfer between robots, with applications ranging from educational robotics to space exploration. Current research directions include neurosymbolic approaches for handling novelty in open worlds, multimodal object property learning, and augmented reality interfaces for improved human-robot collaboration. Scientific Awards and Recognition: Winner of the Verizon 100K 5G EdTech Challenge (Spring 2019) for AR-based robotics education NSF CAREER Award: "Learning and Sharing Transferable Grounded Object Knowledge for Collaborative Robots" (2023) CEEO Fellow at the Center for Engineering Education Outreach Professor Sinapov actively mentors graduate students in the Multimodal Learning, Interaction, and Perception (MLIP) Lab, currently advising five PhD students across Computer Science and Mechanical Engineering departments. His research has been supported by significant grants including his NSF CAREER award. He has co-organized prominent symposia including the AAAI Spring Symposium on "Interactive Multi-Sensory Perception for Embodied Agents" (2017) and the AAAI Fall Symposium on "AI for Human-Robot Interaction" (2019). He directs the Multimodal Learning, Interaction, and Perception (MLIP) Lab , which develops cognitive robotics systems capable of learning through environmental interaction. The lab's research spans robot learning, computational perception, and human-robot interaction, with applications in education, space technology, and collaborative robotics systems operating in complex human environments.

Deniz Yuretمشاهده پروفایل

استاد

• Natural Language Processing
• Machine Learning
• Artificial Intelligence
• +۳ مورد دیگر

Deniz Yuret is a Professor in the Department of Computer Engineering at Koç University , Istanbul, and the founding director of the KUIS AI Center . Previously, he spent 12 years at the MIT AI Lab and co-founded Inquira, Inc. His research focuses on Natural Language Processing and Machine Learning , with significant contributions in dependency parsing , language modeling , grounded language learning , and character-level NLP . He has pioneered frameworks like Knet , a deep learning library in Julia, and AutoGrad.jl for automatic differentiation. Deniz's academic work spans neural architectures for language-robot interaction, transfer learning in low-resource NMT, and context embeddings for grammatical category acquisition. His recent publications emphasize transformer models , multimodal systems , and efficient language modeling . He has supervised multiple graduate students, including Emre Can Açıkgöz (PhD, UIUC), Onur Kuru (M.S. 2016), Saman Zia (M.S. 2016), and Osman Baskaya (M.S. 2015). His projects include the TUBITAK 1001 (2016-2018) and ReGROUND (2015-2018) in collaboration with international institutions.

Tarik Kelestemurمشاهده پروفایل

پژوهشگر

• Robotics
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Tarik Kelestemur is a roboticist specializing in autonomous systems, with affiliations including Boston Dynamics AI Institute and Northeastern University. His work bridges robotics, artificial intelligence, and computer engineering, focusing on tactile manipulation, 3D semantic understanding, and policy learning frameworks. His research interests include: Robotics Artificial Intelligence Machine Learning Computer Engineering Autonomous Systems Human-Robot Interaction Recent publications highlight advancements in diffusion policies, vision foundation models, and 3D relational object graphs. Tarik received an Outstanding Paper Award Finalist at CoRL 2024 and contributes to open-source robotics projects like point_cloud_proc and icub_arm_imitator .

Michael Ryooمشاهده پروفایل

دانشیار

• Deep Learning
• Computer Vision
• Robotics
• +۳ مورد دیگر

Michael Ryoo serves as a SUNY Empire Innovation Associate Professor in the Department of Computer Science at Stony Brook University while concurrently working as a Research Scientist with Google Brain's "Robotics at Google" team. Previously, he held positions as an Assistant Professor at Indiana University Bloomington and a Staff Researcher at NASA's Jet Propulsion Laboratory. His academic background includes a Ph.D. from the University of Texas at Austin (2008) and a B.S. from Korea Advanced Institute of Science and Technology (KAIST) in 2004. Ryoo's research centers on deep learning and computer vision with specific focus on convolutional neural network (CNN) models for video semantic understanding. His work bridges visual perception and robotic action through applications in robot perception, robot learning, and human-robot interaction. Key innovations involve developing efficient architectures for processing multimodal data and translating visual understanding into robotic control systems. Analysis of his 15 most recent publications reveals strong emphasis on multimodal AI integration, particularly vision-language models applied to robotics. His 2025 work shows significant advancement in token-efficient video representation, motion-controllable diffusion models, and zero-shot learning frameworks specifically designed for robotic control systems. The research trajectory demonstrates consistent focus on making video understanding more accessible and applicable to real-world robotic scenarios. Scientific awards: No awards were mentioned in the provided source material. Regarding academic advising, the source text does not list any students or mentoring activities. Similarly, no grant funding information is provided, though his dual academic-industry role suggests substantial research support. His Google Brain affiliation likely involves industry-sponsored research initiatives. Ryoo maintains active laboratory affiliations through Stony Brook's AI Innovation Institute and Google's Robotics team. His prior work at NASA JPL indicates experience with space robotics systems, while his current Google role focuses on large-scale robot learning infrastructure. The LAM SIMULATOR project represents his current focus on advancing data generation techniques for training large action models.

Luca Fanucciمشاهده پروفایل

استاد

• Integrated Circuit Design
• Embedded Systems
• System-Level Design
• +۷ مورد دیگر

Professor Luca Fanucci is a Full Professor of Electronics at the Department of Information Engineering , University of Pisa. He serves as Rector's Delegate for Inclusion of Students with Disabilities and leads research in integrated circuits, embedded systems, and assistive technologies . Institutional roles include membership in the National University Conference of Delegates for Disability (CNUDD) and leadership in the PhD program in Information Engineering. Born: Montecatini Terme (1965) Education: Laurea in Electronic Engineering (1992), PhD in Information Engineering (1996), University of Pisa Professional Journey: ESA research (1992-1996), CNR researcher (1996-2004), University of Pisa faculty (2004-present) His research focuses on: System-level design of integrated circuits and embedded systems Hardware-software co-design for low power consumption Spacecraft and satellite communication systems Medical devices and telemonitoring platforms Assistive technologies for disabilities Recent publications highlight AI in space applications and telemedicine systems . Key projects include the Ingeniars spin-off for satellite communications and the AsTech National Laboratory for assistive technologies. Scientific Recognition : IEEE Fellow (2019) 40+ patents H-index 34 (5000+ citations) He coordinates international conferences (DATE, HiPEAC, Spacewire) and serves as Associate Editor for Technology and Disability and Microprocessors and Microsystems journals.

Nitin J Sanketمشاهده پروفایل

استادیار

• Robotics
• Autonomous Systems
• Computer Vision
• +۸ مورد دیگر

Nitin J Sanket is an Assistant Professor in the Robotics Engineering Department at Worcester Polytechnic Institute, where he leads the Perception and Autonomous Robotics Group (PeAR) founded in 2022. His research focuses on advancing autonomy for tiny mobile robots through bio-inspired approaches that enable on-board sensing and computation without external infrastructure. Ph.D. in Computer Science from University of Maryland, College Park (2021) M.S. in Robotics from University of Pennsylvania (2016) B.E. in Electronics and Communication from M. S. Ramaiah Institute of Technology, Bangalore, India (2013) Professor Sanket's research centers on four interconnected thrusts: Active perception (using movement to simplify perception problems), Interactive perception (selectively interacting with the environment), Novel perception (using data statistics like neural network uncertainty), and Novel sensing (employing sensors like event cameras). His work targets extreme resource-constrained robots, exemplified by the world's first RoboBeeHive prototype – hummingbird-sized nano-quadrotors capable of pollination with all sensing and computation performed on-board. His lab's 'Minimal-AI' philosophy emphasizes efficiency, using perception-action synergy to solve complex problems with minimal computational resources. His recent publications reveal a strong focus on efficient vision algorithms for tiny robots, with papers in Science Robotics (featured on the cover), IEEE ICRA, IROS, and CVPR. Key themes include uncertainty modeling for resource-constrained systems, event-based vision, and bio-inspired navigation. His work frequently bridges theoretical innovation with practical implementation on real hardware. Larry S. Davis Award for Best Computer Science PhD Thesis at University of Maryland (2021) MDPI Drones 2021 PhD Thesis Award Brin Family Prize (2018) Science Robotics cover feature (2023) Professor Sanket actively mentors 19 students (3 PhD, 6 Masters, 10 undergraduates) and recently secured a $705K NSF grant (September 2025) for bio-inspired sound navigation in tiny robots. His lab emphasizes hands-on experience with real hardware systems rather than pure simulation. His research on bat-inspired drones for search and rescue operations has received extensive media coverage from Associated Press, Washington Post, NPR, and other major outlets, demonstrating the real-world relevance of his work. The Perception and Autonomous Robotics Group (PeAR) provides students with opportunities to work on cutting-edge problems in nano-drone development, bio-inspired navigation, and minimal-AI approaches, preparing them for careers at the forefront of robotics innovation.

Laxima Niure Kandelمشاهده پروفایل

استادیار

• Wireless Security
• Wireless Sensing and Localization
• UAV Detection
• +۴ مورد دیگر

Dr. Laxima Niure Kandel is an Assistant Professor in the Department of Computer, Electrical, and Software Engineering at Embry–Riddle Aeronautical University. Her research spans wireless security, UAV detection, and cybersecurity, with a strong focus on AI-driven solutions for aviation and IoT systems. Her core research interests include: Wireless sensing and localization Machine learning applications in cybersecurity GPS spoofing detection for aviation RF fingerprinting for device authentication Adversarial resilience in deep learning models Recent publications (2025) demonstrate a dominant focus on transformer-based security models, UAV protection systems, and explainable AI. Over 80% of her latest work involves deep learning techniques applied to real-world threats like GPS spoofing, ADS-B attacks, and adversarial patches in autonomous vehicles.

Robert Kelley Bradleyمشاهده پروفایل

استادیار

• Nanomaterials
• Polymer Engineering
• Materials Science
• +۳ مورد دیگر

Dr. Robert Kelley Bradley serves as Assistant Professor in the Department of Industrial and Systems Engineering at Lamar University, with additional experience as a Visiting Faculty Member at Oak Ridge National Laboratory (ORNL) through the DOE Visiting Faculty Program in 2021. His educational background includes a Ph.D. in Physical Chemistry from Rice University (2000), where he completed his thesis "Large Scale Production of Single Wall Carbon Nanotubes" under Nobel laureate Prof. Richard Smalley, and a B.A. in Biochemistry from Beloit College (1996). Dr. Bradley's research program centers on Nanomaterials and Entrepreneurship, with significant projects in thermoplastic creep behavior, drug delivery microstructures, silicone ferroelectrets, and single-wall carbon nanotube production. His work integrates materials science with industrial engineering to solve practical problems in corrosion prevention, extreme-environment applications, and manufacturing processes. Recent publications demonstrate strong activity in polymer engineering and nanomaterial characterization. His publication record shows consistent output since 1998, with recent emphasis (2021-2025) on thermoplastic composites, creep modeling, and nanomaterial applications. The research spans Materials Science, Polymer Engineering, and Nanotechnology, with practical focus on industrial implementation and educational innovation. Dr. Bradley actively mentors undergraduate researchers through Lamar University's SURF program and has secured substantial research funding: CMMS Research Grant Competition (2023): $99,572 for thermoplastic composite pipe support pads TARC Research Pitch (2023): $10,000 for multi-medium robots with smart skin CICE Grant (2021): $4,000 for single-wall carbon nanotube research Multiple SURF awards ($1,000 each) from 2020-2025 for undergraduate projects His collaborative projects involve Prairie View A&M, West Texas A&M, and Texas A&M universities, focusing on interdisciplinary applications including space technologies and environmental materials. Dr. Bradley also contributes to engineering education through online degree programs and hands-on manufacturing curriculum development.