جست‌وجوی استاد و پژوهشگر

Sarah Annunziatoمشاهده پروفایل

دانشیار

• Italian Children’s Literature
• Media Studies
• History of Childhood in Italy
• +۴ مورد دیگر

Sarah Annunziato is an Associate Professor of Italian and Director of both the Undergraduate Program in Italian and the Italian Language Program (1000-2000 level courses) at the University of Virginia. She holds a Ph.D. from Johns Hopkins University and a B.A. from Smith College. Her research focuses on children’s literature, media, and trauma representation, with a particular emphasis on Italian and U.S. texts. She also investigates language pedagogy, including game-based learning and the role of streaming media in language acquisition. Her teaching spans graduate courses like Dante’s Inferno on Film and undergraduate courses such as Elementary Italian and Small Screen Italy . She has advised MA theses on topics ranging from Italian literature to comparative cinema. Annunziato has received multiple grants, including funding for a tutoring clinic and curriculum development for healthcare-focused Italian courses. Her publications include Clic! L’italiano col telecomando (2024) and articles on topics like colonialism in Emilio Salgari’s works and Dante’s influence on American TV. She actively serves as an editor for La Vendemmia and contributes to initiatives like the Moons and Bonfires archive of Italian-American history.

Anna Peronaمشاهده پروفایل

پژوهشگر ارشد

• Plasma Physics
• Magnetic Reconnection
• Fusion Energy
• +۴ مورد دیگر

Anna Perona is a Research Fellow at the University of Warwick's Department of Physics, affiliated with the Physics Centre for Fusion, Space and Astrophysics. Her research focuses on plasma physics phenomena, including magnetic reconnection and energetic particle behavior in fusion and space plasmas. She has conducted postdoctoral work at leading institutions like JET (Culham) and CEA (Cadarache), investigating fast ion dynamics and plasma stability. Her current work emphasizes electron acceleration during magnetic reconnection events, supported by a custom numerical tool analyzing 3D magnetic field effects on electron trajectories. Collaborations include projects with Julia Branke on visualizing plasma dynamics. No awards are explicitly stated, but her work contributes to advancing fusion energy and space plasma understanding. Education & Experience: Postdoctoral Research Fellow at University of Warwick Research stages at JET (Tokamak disruptions) and CEA (fusion physics) Research Interests: Numerical modeling of energetic electrons and ions in magnetized plasmas Magnetic reconnection dynamics and its impact on particle acceleration Development of 3D plasma simulation tools Advising & Grants: No formal advisees listed Collaborations with institutions like JET and CEA Labs & Teams: Part of the Physics Centre for Fusion, Space and Astrophysics at Warwick Contributions to the HAGIS code for energetic ion studies

Wouter Roosمشاهده پروفایل

استاد

• Biophysics
• Biochemistry & Molecular Biology
• Nanoscience & Nanotechnology
• +۵ مورد دیگر

Prof. Wouter Roos is a Professor at the University of Groningen's Faculty of Science and Engineering, affiliated with the Molecular Biophysics department at the Zernike Institute for Advanced Materials. His research focuses on viral dynamics, membrane assemblies, and protein mechanics, utilizing advanced techniques like High Speed Atomic Force Microscopy (HS-AFM) and optical tweezers. Education: Studied Physics at the Universiteit van Amsterdam, earned a PhD from the Universität Heidelberg under Joachim Spatz. Conducted postdoctoral research at Max-Planck-Institut, Institut Curie, and Vrije Universiteit before joining Groningen in 2015. Research Interests: Physical Virology (viral material properties and dynamics), membrane biophysics (synthetic cells and lipid interactions), and molecular motor systems. His work bridges physics, chemistry, and biology to understand nanoscale biological processes. Recent Article Trends: Studies on hybrid membranes for synthetic cells, leukemic cell mechanics, and antibiotic-membrane interactions highlight his interdisciplinary approach. Key techniques include HS-AFM and single-particle tracking. Awards: Received a VIDI grant and multiple national/international grants. His lab leads the oLife Co-Fund consortium and participates in the MOSBRI research infrastructure. Grants & Leadership: Coordinates the oLife Fellowship Programme and chairs the Molecular Biophysics Lab. Active in steering committees for EU-funded initiatives. Labs/Teams: Heads the Molecular Biophysics Lab, focusing on viral dynamics and membrane systems. Collaborates globally on projects like ESCRT-III polymerization and antibiotic mechanisms.

Daniele Loiaconoمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Medical Imaging
• +۶ مورد دیگر

Daniele Loiacono is an Associate Professor at Politecnico di Milano's Department of Electronics, Information, and Bioengineering (DEIB), affiliated with the Artificial Intelligence and Robotics Lab (AIRLab). His research focuses on interdisciplinary applications of Artificial Intelligence, Machine Learning, and Deep Learning in medical imaging, radiation therapy, and procedural content generation for games. He leads projects in synthetic image generation for radiotherapy quality assurance, automated treatment planning, and bias analysis in medical AI systems. Key research areas include medical image synthesis using GANs, radiation therapy optimization, and algorithmic game design. His contributions span clinical applications such as total marrow irradiation (TMI) planning and lymph-node segmentation, alongside innovations in shader generation and interactive evolutionary tools for game development. Loiacono collaborates on multi-center studies to validate AI-driven workflows in healthcare and has pioneered methods combining lean Six Sigma with machine learning for treatment process improvement. His work bridges clinical medicine and computer science, addressing challenges in radiation oncology, anatomical imaging, and procedural content automation. The AIRLab serves as a hub for his research, integrating AI advancements into real-world medical and engineering solutions.

• Chinese Bronze Age
• Shang Dynasty
• Ancient East Asian History
• +۴ مورد دیگر

Roderick B. Campbell is a Professor of East Asian Archaeology and History at the Institute for the Study of the Ancient World (ISAW) within New York University. His research focuses on the Chinese Bronze Age, particularly the Anyang period (ca. 1250-1050 BCE), exploring themes such as violence in early complex polities, historiography, visual culture, and ancient economies. He holds a dual PhD from Harvard University in Anthropology (Archaeology) and East Asian Languages and Civilizations (Chinese History). Professor Campbell has held post-doctoral positions at ISAW (NYU), Brown University’s Joukowsky Institute, and Merton College (Oxford University). He has secured grants and fellowships from organizations including the Canadian Social Sciences and Research Council, Luce-ACLS, the Chiang Ching-kuo Foundation, and the Wenner Gren Foundation. His fieldwork involves collaborative archaeological projects in China focusing on reconstructing Shang political economy, with a current emphasis on zooarchaeology and bone-working practices. He serves on NYU’s PhD Admissions Committee and has authored or edited works such as Violence, Kinship and the Early Chinese State (2018) and Archaeology of the Chinese Bronze Age (2014). His research spans interdisciplinary topics including Shang ontology, early Chinese economies, and comparative studies of complex societies. Campbell’s work bridges archaeological material analysis with historical interpretation to illuminate the socio-political dynamics of ancient East Asia.

Sonia Mayoralمشاهده پروفایل

استادیار

• Glial Cell Biology
• Myelin
• Neuron-Glia Interactions
• +۳ مورد دیگر

Sonia Mayoral is the Robert J. and Nancy D. Carney Assistant Professor of Neuroscience at Brown University. Her research focuses on studying cell-cell interactions in the brain, particularly the development and function of oligodendrocytes – glial cells critical for myelin formation. She explores how these cells contribute to myelination, remyelination processes, and their roles in neurological disorders like multiple sclerosis. Her work integrates cellular neuroscience, immunology, and drug screening methodologies. Research interests include glial cell biology, neuron-glial interactions, and the molecular mechanisms governing myelin repair. She investigates how environmental cues and signaling pathways regulate oligodendrocyte differentiation and function. Notable projects involve developing high-throughput screening platforms for MS therapeutics and studying sex-specific responses to neurodegenerative challenges. Her lab’s recent work includes clinical trials (Re-WRAP) evaluating Bazedoxifene for remyelination in women, and fundamental studies on regulatory T cell roles in myelin regeneration. She also examines how mechanical stimulation and epigenetic changes influence oligodendrocyte behavior. Her research bridges basic science and translational efforts, aiming to advance treatments for myelin-related disorders. Dr. Mayoral’s lab is active at Brown University, with a dedicated website detailing ongoing projects and collaborations. While no specific grants or students are listed here, her work reflects a strong focus on interdisciplinary approaches to neurodegenerative disease mechanisms.

Bernhard Rumpeمشاهده پروفایل

استاد

• Software Engineering
• Model-Based Software Engineering (MBSE)
• Domain-Specific Languages (DSLs)
• +۱۶ مورد دیگر

Bernhard Rumpe is a Professor and Chair of Software Engineering at the Department of Computer Science 3, RWTH Aachen University, Germany. He leads a research group focused on model-based software engineering, domain-specific languages, and digital twins, with strong industrial collaborations and applications in embedded systems, AI, IoT, and autonomous vehicles. His research centers on improving software development through model-driven engineering, generative techniques, and formal modeling using UML, SysML, and the MontiCore language workbench. Key interests include digital twins, variability modeling, model composition, and the integration of cyber-physical systems with information systems. The recent publications highlight a consistent focus on model-driven digitalization, language workbenches, and system integration. Trends show increasing emphasis on digital twins in manufacturing and societal systems, formal verification of model transformations, and educational applications of model-driven low-code platforms. His work bridges theoretical foundations with industrial applicability. Keynote Speaker, OOPSLE 2025 General Chair, GPCE 2023 Session Chair, MODELS 2020 Program Committee Member, SLE, GPCE, ICSE, ECMFA He advises master’s and doctoral students and leads a vibrant research team that has successfully executed over 100 research projects. His group develops foundational tools like MontiCore and applies them in industrial contexts, contributing to software quality and developer efficiency. No formal grants are listed, but sustained project funding is evident. He is involved in several research labs and teams centered around the Software Engineering Chair at RWTH Aachen, focusing on language workbenches, model-driven development, and digital twin systems. The team actively contributes to open research through publications, tools, and industrial partnerships.

Larry Heckمشاهده پروفایل

استاد

• Machine Learning
• Deep Learning
• Natural Language Processing
• +۵ مورد دیگر

Larry Heck is a Professor at the Georgia Institute of Technology with joint appointments in the School of Electrical and Computer Engineering and the School of Interactive Computing. He holds the Rhesa S. Farmer Advanced Computing Concepts Chair and is a Georgia Research Alliance Eminent Scholar. His research focuses on machine learning, deep learning, natural language processing, conversational systems, and speech/speaker recognition. He directs the AI Virtual Assistant (AVA) Lab, advancing next-generation AI assistants. Dr. Heck has held leadership roles in industry, including at Microsoft, Google, Samsung, and Viv Labs, and has over 50 U.S. patents. Education: BSEE from Texas Tech University (1986) MSEE and PhD in Electrical Engineering from Georgia Tech (1991) Research Interests: Dr. Heck’s work bridges machine learning and human-centric AI, with emphasis on conversational systems, multimodal interaction, and real-world applications. His AVA Lab develops AI assistants that integrate visual, auditory, and contextual cues for natural interaction. Recent projects include multimodal sensor integration, dialogue systems for caregiving networks, and embodied AI for avatar animation. Awards: IEEE Fellow (2020) Academy of Distinguished Engineering Alumni, Georgia Tech (2017) Distinguished Engineer Award, Texas Tech University (2017) Advising & Grants: While primarily focused on industry collaboration, Dr. Heck mentors students through Georgia Tech’s interdisciplinary programs. His research is funded by government agencies and corporate partnerships, including the NSA and DARPA. Labs & Teams: The AVA Lab collaborates with academia and industry to create AI systems that understand context, gestures, and environment. Current initiatives include multimodal dialogue datasets (e.g., OKCV, SensorQA) and reinforcement learning frameworks for real-time systems.

Annie Mahtaniمشاهده پروفایل

استاد

• Electroacoustic Music
• Acousmatic Composition
• Multichannel Audio
• +۶ مورد دیگر

Professor Annie Mahtani is a Professor of Electroacoustic Composition and Practice at the University of Birmingham's Department of Music. She holds a BMus (Hons), MA, MPhil, and PhD from the University of Birmingham and Birmingham City University. Her work focuses on electroacoustic music, acousmatic composition, multichannel audio, spatialisation, and field recordings, with significant contributions to site-specific installations and cross-disciplinary collaborations. She co-directs the SOUNDkitchen collective and serves on key boards such as the British ElectroAcoustic Network (BEAN) and the British Section of ISCM. Her research explores the sonic identity of environmental sounds, large-scale multichannel composition, and ambisonic audio techniques. As a performer with BEAST (Birmingham Electroacoustic Sound Theatre), she develops live acousmatic performances and soundwalks. Recent projects include Becoming Tree (an immersive audio retelling of a literary work) and Minimum Monument , performed at Birmingham Hippodrome. She actively collaborates with dance and theatre companies like Rosie Kay Dance Company. Professor Mahtani teaches undergraduate and postgraduate modules in electroacoustic composition and is involved in admissions and curriculum leadership. Her works have been performed globally in festivals like Klang! Électroacoustique and Sound + Environment, showcasing her innovative contributions to contemporary music and sound art.

• Robotics
• Artificial Intelligence
• Space Robotics
• +۵ مورد دیگر

M.Sc. Maximilian Mühlbauer is a researcher at the Chair of Sensor-Based Robot Systems and Intelligent Assistance Systems at Technische Universität München (TUM), part of the Faculty of Computer Science. His work focuses on robotics, artificial intelligence, and space robotics, particularly in areas like in-orbit manufacturing, virtual fixtures, and human-robot interaction. He contributes to projects such as the ACOR initiative and the AI-In-Orbit-Factory, exploring fault-tolerant processes and adaptive robotic systems for space applications. Research Interests: Maximilian’s research emphasizes AI-driven robotics , space robotics , and control systems . He develops methodologies for virtual fixtures , reconfigurable robotic systems , and teleoperation with shared control . His work integrates probabilistic models and machine learning for resilient systems in challenging environments like space. Publications: His recent work spans topics from in-orbit manufacturing and force-sensitive space manipulators to multi-modal haptic teleoperation , reflecting a focus on practical robotic applications in aerospace and industry. Grants/Advising: Maximilian oversees available theses on topics like mixture of experts fixture learning and virtual fixture adaptation , inviting collaboration on AI-driven robotics projects. He collaborates with Prof. Alin Albu-Schäffer and contributes to TUM’s research initiatives in autonomous systems. Labs: He is part of the Sensor-Based Robot Systems lab, advancing robotics for human-centric and space-oriented applications.

Yelda Turkanمشاهده پروفایل

دانشیار

• Computer Vision
• Machine Learning
• Lidar Applications
• +۷ مورد دیگر

Dr. Yelda Turkan is an Associate Professor in the School of Civil and Construction Engineering at Oregon State University, where she leads research in automation, computer vision, and machine learning for sustainable infrastructure. She holds a PhD from the University of Waterloo and dual BS degrees in Civil Engineering and Geomatics Engineering from Istanbul Technical University. Her work focuses on leveraging lidar, digital twins, and BIM to improve construction operations and decision-making in the built environment. She has secured over $4M in grants from NSF, FHWA, and other agencies, and currently leads the NSF Convergence Accelerator-funded 'Deep Reality' project for AI-driven infrastructure management. Education: Ph.D., Civil Engineering, University of Waterloo, 2012 M.S., Engineering Informatics & Remote Sensing, Istanbul Technical University, 2006 B.S., Civil Engineering (double major in Geomatics Engineering), Istanbul Technical University, 2005/2003 Professional Roles: Vice President, International Association for Automation and Robotics in Construction (IAARC) Chair, ASCE Computing Division Education Committee Associate Editor, ASCE OPEN Journal Her research emphasizes automation in construction quality control, infrastructure inspection via drones and lidar, and immersive education tools using VR/AR. Recent projects include automated curb ramp compliance analysis, wildfire impact modeling, and digital twin development for timber structures. She has published over 80 peer-reviewed articles and actively promotes computing integration in civil engineering education and professional practice.

• Applied Linguistics
• World Englishes
• TESOL (Teaching English to Speakers of Other Languages)
• +۶ مورد دیگر

Associate Professor Sunny-Boy Ahmar Mahboob is a distinguished linguist at the University of Sydney, where he serves as Degree Coordinator for the Master of Crosscultural and Applied Linguistics program within the Department of Linguistics, Faculty of Arts and Social Sciences. With extensive experience in applied linguistics and language education, Dr. Mahboob has established himself as a leading expert in World Englishes, TESOL, and language variation research, both nationally and internationally. Dr. Mahboob's educational background includes: BA from Karachi MA from Karachi MA from Indiana University MEd from Sydney PhD from Indiana University (2003) Dr. Mahboob's primary research focuses on language variation in global contexts, with particular attention to World Englishes, the NNEST (Non-Native English Speaking Teachers) movement, language policy, and decolonial approaches to linguistics. His work critically examines how language policies and practices affect educational outcomes and social justice, especially in postcolonial contexts like Pakistan and the Middle East. He pioneered 'appliable linguistics' - an approach that bridges theoretical linguistics with practical applications in education and policy, emphasizing the need for linguistic theories to address real-world problems. His recent publications reveal a strong trajectory toward decolonial linguistics, with increasing focus on subaltern perspectives, environmental connections to language diversity, and critical examinations of colonial legacies in language education. Dr. Mahboob's work consistently addresses power dynamics in language teaching and the need for more inclusive approaches that value linguistic diversity across educational contexts from primary schools to universities. Dr. Mahboob has received numerous prestigious awards: 2019: Australia's Research Field Leader in English Language and Literature (The Australian's Research magazine) 2012: Fellow of the National Talent Pool; President's Programme for Highly Qualified Overseas Pakistanis 2006: Faculty of Arts and Social Sciences Teaching Award, University of Sydney 2005: Teaching Initiative Award and Fellow of the Association of Pacific Rim Universities 2004: ECU Research and Creativity Award 2002: 'Distinguished President Award' from INTESOL, Indianapolis As an academic mentor, Dr. Mahboob supervises research students including Ruohong CAO (Developing Mandarin Learning Materials for Young Learners in Australia through Positive Discourse Analysis) and Tracy GAO (Evaluating Chinese Language Textbooks: A Sociosemiotic Perspective). His editorial work includes serving as Editor of TESOL Quarterly (2014-2017) and Associate Editor for multiple linguistics journals. Dr. Mahboob has secured significant research funding for projects including the SLATE (Scaffolding Literacy in Academic and Tertiary Environments) project and indigenous language funding initiatives in Australia. Dr. Mahboob founded and leads the International Free Linguistics Conference series, which has become an important platform for critical and alternative approaches to linguistics. His 'SLATE project' focuses on genre-based pedagogy for academic writing, and he actively collaborates with researchers across multiple continents through the World Englishes research network. His recent work increasingly explores the connections between language diversity and environmental sustainability, positioning linguistic ecology as a critical component of broader ecological concerns.

• Innovative Materials
• Support to SMEs
• Sensory Design
• +۴ مورد دیگر

Beatrice Lerma is an Associate Professor at the Polytechnic University of Turin , affiliated with the Department of Architecture and Design and serving as Deputy Coordinator of the Doctoral School of Design and Technology: People, Environment, Systems . Research focuses on Innovative Materials , Sensory Design , and Design for Cultural Heritage Key skills in Environmental Engineering , Industrial Design , and Circular Economy Her recent work explores the intersection of Artificial Intelligence and Material Innovation , particularly in sustainable polymer systems and transparent wood technology. She leads the BIOMAPS (2025-2028) and AI-TRANSPWOOD (2024-2026) projects. 2025: AI applications in biobased materials 2024: Cultural heritage signage solutions 2024: Circular material taxonomic frameworks Scientific recognitions include ADI Design Index Selection Award (2015) and Young & Design (2013). She supervises PhD candidates Noemi Emidi and Eva Vanessa Bruno , and serves on the OFFICINA Scientific Committee since 2014.

Vatsal Sharanمشاهده پروفایل

استادیار

• Machine Learning
• Theoretical Computer Science
• Statistics
• +۶ مورد دیگر

Vatsal Sharan is an Assistant Professor in the Thomas Lord Department of Computer Science at the University of Southern California's Viterbi School of Engineering. He maintains affiliations with the Theory Group, Machine Learning Center, and the Center for AI in Society at USC. Education: Ph.D. in Computer Science from Stanford University, advised by Greg Valiant Postdoctoral research at MIT, hosted by Ankur Moitra Vatsal Sharan's research centers on the theoretical foundations of machine learning, positioned at the intersection of machine learning, theoretical computer science, and statistics. His work investigates fundamental limits for solving learning and estimation tasks under computational and information-theoretic constraints, with the goal of developing practical algorithms that are efficient, fair, and robust. His research spans memory-efficient learning, algorithmic fairness, robustness in deep learning, and the theoretical underpinnings of transformers and large language models. A significant portion of his work explores how memory constraints affect learning algorithms and whether memory can serve as a distinguishing factor between 'efficient' and 'expensive' techniques in machine learning. His recent publications demonstrate a strong focus on multicalibration, transformer interpretability, and trustworthy AI systems. Scientific Awards: Amazon Research Award (2021 and 2023) SoCal NLP Symposium 2023 Best Paper Award COLT 2022 Best Paper Award Vatsal Sharan advises a diverse group of Ph.D. students including Siddartha Devic, Bhavya Vasudeva, Julian Asilis, Deqing Fu, Devansh Gupta, Spandan Senapati, and Tianyi Zhou. His research is supported by multiple prestigious grants from the NSF, Amazon Research, Google Research, and the Okawa Foundation. He is an active participant in the Learning Theory Alliance (LeT-All), a community-building and mentorship initiative for the learning theory community. His teaching portfolio includes advanced courses on machine learning theory and trustworthy machine learning at USC, where he shapes the next generation of researchers in theoretical aspects of artificial intelligence.

• Computer Vision
• Machine Learning
• Deep Learning
• +۵ مورد دیگر

Abhinav Shrivastava is an Associate Professor in the Department of Computer Science at University of Maryland, College Park, with a joint appointment in the Institute of Advanced Computer Studies (UMIACS). Previously, he served as an Assistant Professor at the same institution from August 2018 to June 2024, and spent one year as a Visiting Research Scientist at Google Research from September 2017 to August 2018. His educational background includes: PhD in Robotics and Artificial Intelligence from Carnegie Mellon University (2017), advised by Abhinav Gupta, with thesis titled 'Discovering and Leveraging Visual Structure for Large-scale Recognition' MS in Artificial Intelligence from Carnegie Mellon University (2011), supervised by Alyosha Efros and Martial Hebert BTech in Computer Science and Engineering from Jaypee Institute of Information Technology (2010) Professor Shrivastava's research focuses on computer vision and machine learning, with particular expertise in object detection, image recognition, and neural representations. His work bridges theoretical advances with practical applications, exploring how visual systems can discover and leverage structure in large-scale recognition problems. He has made significant contributions to understanding the role of supervision in vision transformers, developing novel approaches for object-state composition recognition, and creating efficient neural representations for videos and 3D scenes. His research often addresses fundamental challenges in visual recognition, including handling novelty in open-world environments and improving the efficiency of visual systems. An analysis of his recent publications reveals a strong emphasis on neural representations, particularly for dynamic content like videos and 3D scenes. His work demonstrates increasing sophistication in handling open-world vision problems, with research spanning object discovery, localization, and representation learning. The publications show a clear progression toward more efficient and scalable models, with recent work focusing on model compression, sparse representations, and addressing the challenges of working with limited annotations. His scientific contributions have been recognized with several prestigious awards: Best Paper Award (Applications) at IEEE Winter Conference on Applications of Computer Vision (2020) Microsoft Research PhD Fellowship (2014-2016) Best Student Paper Award at IEEE Winter Conference on Applications of Computer Vision (2014) Outstanding Reviewer Award at IEEE CVPR (2015) Professor Shrivastava has successfully mentored numerous graduate students, many of whom have become prominent researchers in computer vision. His Amazon Research Awards (2020 and 2023) have supported innovative projects including 'The pursuit of knowledge: discovering and localizing new concepts using dual memory' and 'Audio-conditioned Diffusion Models for Generating Lip-synchronized Videos.' He has served as Area Chair for major conferences including ICCV, CVPR, and AAAI, demonstrating his leadership in the computer vision community. His research has attracted significant funding from both academic and industry sources, supporting his exploration of fundamental questions in visual recognition and representation learning.