جست‌وجوی استاد و پژوهشگر

• Optical fiber communication
• Space-division multiplexing (SDM)
• Wavelength-division multiplexing (WDM)
• +۵ مورد دیگر

Itsuro Morita is Professor in the School of Fundamental Science and Engineering, Faculty of Science and Engineering, Waseda University, Tokyo. Before joining Waseda in 2022 he spent 23 years at KDDI R&D Laboratories, advancing from researcher to executive research fellow, and has been a visiting researcher at Stanford University. He is an IEEE Fellow and IEICE Fellow recognized for pioneering large-capacity, long-haul optical transmission systems. Education: 2004 – 2005 Tokyo Institute of Technology, Graduate School of Science & Engineering, Department of Electrical and Electronic Engineering (Doctoral coursework) 1990 – 1992 Tokyo Institute of Technology, Graduate School of Science & Engineering, Department of Physical Electronics (M.E.) 1986 – 1990 Tokyo Institute of Technology, School of Engineering (B.E.) Research Interests: Morita’s work sits at the intersection of optical fiber communication and software-defined networking. He explores ultra-high-capacity transmission via space-division multiplexing (multi-core/few-mode fibers), real-time MIMO digital signal processing for modal crosstalk mitigation, and SDN/NFV orchestration of disaggregated optical networks. Additional interests include quality-of-transmission estimation using machine learning, telemetry-enabled control planes (gRPC/gNMI), and metro-embedded edge/cloud architectures for IoT services. Publication Trends: Recent articles emphasize two converging themes: (i) petabit-per-second SDM/WDM experiments using novel fiber geometries and real-time DSP, and (ii) cloud-native SDN control frameworks that integrate machine-learning-based QoT prediction, YANG/NETCONF modeling, and open APIs (TAPI/OpenConfig) for multi-domain, partially disaggregated networks. These works collectively push both the physical capacity frontier and the agility of next-generation optical infrastructure. Scientific Awards: C&C Prize 2024 (NEC C&C Foundation) – contributions to WDM optical submarine cable systems IEICE Achievement Award 2021 – pioneering research on 10-Pbit/s ultra-large-capacity SDM transmission Telecom System Technology Award 2021 – 10.16-Pbit/s dense SDM/WDM transmission record IEEE Fellow (2021) – contributions to large-capacity high-speed transmission systems IEICE Fellow (2020) – research on trans-oceanic high-speed optical signal transmission Ichimura Industrial Award – Contribution Prize 2018 – development of terabit-class submarine cable systems Maejima Hisoka Award 2012 – proposal and demonstration of distributed-control soliton communication Minister of Economy, Trade and Industry Award for Advanced Technology 2006 – 160 Gbit/s ultra-high-speed optical transmission technology Advising & Grants: At Waseda University Morita advises graduate students on experimental photonic networking and leads externally funded projects on petabit SDM transmission and SDN orchestration. While specific grant numbers are not disclosed, his continuous industry-university collaborative testbeds (with KDDI, CTTC, and others) indicate substantial competitive funding. Labs & Teams: He heads the Optical Space-Division-Multiplexing Laboratory at Waseda, maintaining joint experimental facilities with KDDI Research and international partners (e.g., CTTC, Spain). The group operates real-time coherent MIMO testbeds, multi-domain SDN controllers, and fiber-level SDM prototypes capable of petabit-per-second demonstrations.

• Neuroscience
• Machine Learning
• Neuroimaging
• +۴ مورد دیگر

Dustin Scheinost is an Associate Professor at Yale School of Medicine, affiliated with the Department of Radiology & Biomedical Imaging, Yale Child Study Center, Department of Statistics, and Yale Biomedical Imaging Institute. His research focuses on connectomics , machine learning , and neuroinformatics through the Multi-modal Imaging, Neuroinformatics, & Data Science (MINDS) Lab. Radiology & Biomedical Imaging (Primary) Child Study Center (Secondary) Statistics (Secondary) Wu Tsai Institute Yale Stress Center Research Interests include developing novel statistical and machine learning methods for functional connectivity in big neuroscience data, leading the BioImage Suite Web (BISWeb) platform, and advancing early life neuroimaging through the Fetal, Infant, Toddler Neuroimaging Group (FIT’NG). His work is supported by grants from NIMH, NIAA, NIDA, and NHLBI. Selected Scientific Contributions span functional connectivity in laterality preferences, anti-racist AI governance in psychiatry, self-citation trends in neuroscience, and predictive modeling of mood disorders. He collaborates extensively with Todd Constable and others on multimodal neuroimaging studies.

Roselina Angelمشاهده پروفایل

استاد

• Poultry Nutrition
• Nutrient Utilization
• Environmental Sustainability in Animal Agriculture
• +۵ مورد دیگر

Dr. Roselina Angel is a Professor in the Department of Animal and Avian Sciences at the University of Maryland's College of Agriculture and Natural Resources. With expertise in poultry nutrition, she holds a PhD in Poultry Nutrition from Iowa State University and has been with the university since 1998, initially joining as an Assistant Professor. Research Focus Areas Calcium and phosphorus metabolism in poultry Phytase and enzyme supplementation Environmental impact reduction Nutritional strategies for exotic animals Feed additive efficacy Mineral utilization optimization Her recent publications (2025–2023) concentrate on mechanistic modeling of mineral digestibility, circadian nutrient regulation in laying hens, and the environmental implications of poultry nutrition. These studies frequently examine interactions between dietary calcium/phosphorus ratios, phytase application, and ingredient selection across broilers and laying hens.

• Applied Mathematics
• Mathematical Biology
• Fluid Dynamics
• +۲ مورد دیگر

Silas Alben is a Professor in the Department of Mathematics at the University of Michigan, affiliated with the College of Literature, Science, and the Arts. His research focuses on applied mathematics and mathematical biology, particularly fluid-structure interactions in biological systems. He employs computational simulations and laboratory experiments to study fundamental physics of flexible bodies in fluids. Research interests include biomechanics of swimming organisms, vortex dynamics in fluid-structure interactions, and thermal transport optimization. His work bridges mathematical modeling with experimental validation to understand complex physical phenomena. Publications demonstrate strong focus on fluid dynamics applications, including vortex-enhanced heat transfer, membrane flutter dynamics, and bio-inspired locomotion. Recurring themes include optimization of fluid-structure systems, vortex wake interactions, and computational methods for aeroelastic problems.

Rita Aielloمشاهده پروفایل

دانشیار مدعو

• Music Psychology
• Neuroaesthetics of Music
• Cognitive Processes in Music
• +۴ مورد دیگر

Rita Aiello is an Adjunct Associate Professor in the Department of Psychology at New York University's College of Arts & Science. Her research focuses on the cognitive and perceptual processes involved in musical listening, with particular emphasis on neuroaesthetics, music learning, and memory. She holds an Ed.D. from Columbia University and has held faculty positions at institutions including the Juilliard School and the Manhattan School of Music. Her work bridges music theory, cognitive science, and education, with a lifelong background as a classical pianist. Education: Columbia University (Ed.D.), Manhattan School of Music (M.M., B.M.), Conservatorio San Pietro a Maiella (Diploma in Music Theory) Certifications: Kodály and Orff Methods Her research explores how musical training influences cerebral dominance, the relationship between mental representations and emotional responses to music, and the cognitive underpinnings of musical memory. She has published widely on topics ranging from musical expectation to pedagogical strategies for memorization. Recent work investigates evolutionary perspectives on singing and the psychological mechanisms behind musical communication. Publications reflect interdisciplinary engagement with music's structural rules, metaphorical dimensions, and its role in human cognition. While no specific grants or awards are listed, her extensive international teaching experience includes visiting roles at institutions in Rome and Lugano, Switzerland, and an honorary appointment at Columbia University's Teachers College.

Michael D. Ernstمشاهده پروفایل

استاد

• software engineering
• programming languages
• type theory
• +۶ مورد دیگر

Michael D. Ernst is a Professor in the Computer Science & Engineering department at the University of Washington's College of Engineering. His research aims to make software more reliable, more secure, and easier (and more fun!) to produce. Previously, he was a tenured professor at MIT and a researcher at Microsoft Research. Ernst's primary technical interests are in software engineering, programming languages, type theory, security, program analysis, bug prediction, testing, and verification. His research combines strong theoretical foundations with realistic experimentation, with an eye to changing the way that software developers work. He focuses particularly on programmer productivity and developing practical tools that can be integrated into developers' workflows. Analysis of his recent publications (2018-2025) reveals a continued focus on verification techniques, program analysis, and testing methodologies. His work spans from theoretical foundations of type systems to practical applications of NLP for test generation and LLMs for test oracle creation. A consistent theme is developing lightweight, modular approaches that can be practically applied in real-world development environments. Scientific Awards: ACM Fellow (2014) John Backus Award (2009) NSF CAREER Award (2002) ACM SIGSOFT Impact Paper Award (2013) 8 ACM Distinguished Paper Awards across multiple conferences ECOOP 2011 Best Paper Award Microsoft Academic Search ranked #2 in software engineering research (2013) Ernst has received significant research funding including the NSF CAREER Award, supporting his work on program analysis and verification techniques. His research combines theoretical rigor with practical impact, often resulting in tools that are adopted by the software engineering community. He actively collaborates with researchers across institutions and has served in leadership roles for major conferences in programming languages and software engineering. His research group develops practical tools that address real challenges in software development, with a focus on making verification and analysis techniques more accessible to working developers. Current projects include applying machine learning techniques to software engineering problems while maintaining strong theoretical foundations.

Jonathan Cannonمشاهده پروفایل

استادیار

• Timing and Rhythm Perception
• Neural Dynamics
• Dynamical Systems Theory
• +۶ مورد دیگر

Jonathan Cannon is an Assistant Professor in the Department of Psychology, Neuroscience & Behaviour at McMaster University's Faculty of Science. His research focuses on timing and rhythm in perception and action, with particular interest in timing-related neural dynamics in the basal ganglia, cerebellum, and supplementary motor area. His work combines mathematical modeling with experimental approaches to understand the neural basis of rhythm perception and production. Dr. Cannon's research interests span timing and rhythm perception , neural dynamics , dynamical systems theory , Bayesian cognition , neural oscillations , and autism research . His approach centers on formulating and simulating neurophysiological and cognitive models, drawing on dynamical systems theory and Bayesian cognitive frameworks. His work incorporates psychophysics, EEG experiments, and collaborations with experimentalists to investigate how the brain processes rhythmic information. Analysis of his recent publications reveals a strong focus on the intersection of rhythm perception, motor control, and autism spectrum disorder. His work demonstrates how beat perception co-opts motor neurophysiology, with particular attention to predictive processes in rhythmic cognition. His research shows reduced precision of motor and perceptual rhythmic timing in autistic adults, while also finding intact sequence learning abilities in certain contexts. Dr. Cannon teaches advanced courses including Machine Learning Methods for Brain Modelling and Neural Data Analysis (PSYCH 734), Computational Models in Neuroscience (NEUROSCI 3MN3), and Neuroscience Seminars. His teaching reflects his interdisciplinary approach that bridges mathematics, neuroscience, and cognitive science. Beyond his academic work, Dr. Cannon is an active musician who performs on violin and guitar, particularly in klezmer and folk music contexts. He has also demonstrated entrepreneurial spirit through founding Flying Leap Games and developing the storytelling game 'Wing It,' which successfully crowdfunded and reached numerous retailers.

Benjamin Eysenbachمشاهده پروفایل

استاد

• Reinforcement Learning
• Self-Supervised Learning
• Machine Learning
• +۲ مورد دیگر

Benjamin Eysenbach leads the Princeton Reinforcement Learning Lab, where he designs algorithms that enable artificial intelligence systems to learn intelligent behaviors through trial-and-error, specializing in self-supervised methods that eliminate the need for human labels. He joined Princeton after completing his PhD in machine learning at Carnegie Mellon University under Ruslan Salakhutdinov and Sergey Levine, supported by the NSF Graduate Research Fellowship and Hertz Fellowship. His research bridges fundamental machine learning principles with practical applications in robotics and decision-making systems. Eysenbach's research focuses on developing self-supervised reinforcement learning algorithms that enable autonomous skill acquisition without external rewards. His investigations span contrastive learning methods, temporal abstraction techniques, and scalable architectures for goal-conditioned behaviors. These innovations aim to create more efficient and generalizable learning systems that can discover useful behaviors from unlabeled experience. Eysenbach's publications demonstrate consistent advancement in self-supervised RL methodologies, with recent work focusing increasingly on temporal abstraction and representation learning theory. His research shows progression from foundational contrastive RL frameworks toward more sophisticated analyses of generalization properties and uncertainty quantification. The 2025 works indicate expanding investigation into hierarchical control, probabilistic alignment, and hyper-deep network architectures. Eysenbach has been recognized with prestigious awards including the Hertz Fellowship and NSF Graduate Research Fellowship, supporting his doctoral research in self-supervised RL methodologies. His work has been presented at top machine learning conferences including NeurIPS, ICML, and ICLR. As director of the Princeton Reinforcement Learning Lab, Eysenbach oversees research initiatives in self-supervised RL, including projects on intention-conditioned modeling, horizon generalization, and contrastive learning frameworks. He has secured funding from the Princeton AI Lab to study neural correlates of temporal contrast in decision-making. Eysenbach teaches courses in reinforcement learning and has developed new benchmarks like JaxGCRL to accelerate research in goal-conditioned RL.

Giuseppe Santucciمشاهده پروفایل

دانشیار

• Visual Analytics
• Information Visualization
• Human-Computer Interaction
• +۳ مورد دیگر

Giuseppe Santucci is an Associate Professor at the Department of Computer, Control and Management Engineering Antonio Ruberti at Sapienza University of Rome. He teaches courses on Fundamentals of Computer Science, Software Engineering, and Visual Analytics. His office is located in Room B218 at Via Ariosto 25, Rome, and his contact email is santucci@diag.uniroma1.it. Dr. Santucci's research focuses on Visual Analytics, Information Visualization, Human-Computer Interaction, and Information Retrieval. His work spans theoretical aspects of visual query languages for semantic models to practical applications in visual analytics for cybersecurity, cryptocurrencies, and deep learning explainability. He has published over 130 articles in international journals and conferences, demonstrating his significant contributions to these fields. His recent publications show a strong trend toward applying visual analytics to increasingly complex domains including cybersecurity, cryptocurrencies, and explainable AI. The work demonstrates an evolution from theoretical foundations of visual query systems to practical applications that help users understand complex data and systems. His research bridges the gap between theoretical computer science and practical user-centered solutions. Dr. Santucci has received notable recognition including: IEEE VizSec 2018 Best Paper Award Human-Computer Interaction Cybersecurity Awards 2018 He actively mentors students through thesis projects focused on information visualization and visual analytics. His PROMISE project provides a framework for students to engage in cutting-edge research in information retrieval and visual analytics. He has supervised work on topics including visual evaluation techniques, visual mappings optimization, and user studies for Infovis systems. Dr. Santucci leads the A.WA.RE (Advanced Visualization & Visual Analytics REsearch) group at Sapienza University. This group conducts research on visual analytics tools for information retrieval evaluation, cybersecurity analysis, and deep learning explainability. Their work includes developing frameworks like CryptoComparator for cryptocurrency analysis and BUCEPHALUS for cybersecurity platform analysis.

Sebastian Hillerمشاهده پروفایل

استاد

• Structural Biology
• NMR Spectroscopy
• Protein Folding
• +۴ مورد دیگر

Professor Sebastian Hiller is a Full Professor at the Biozentrum of the University of Basel, Switzerland, where he leads a research group focused on structural biology and biophysics. His laboratory specializes in using nuclear magnetic resonance (NMR) spectroscopy to elucidate the structures and functions of proteins and their interactions at the atomic level. His research spans several key areas including molecular chaperones and protein folding mechanisms, outer membrane protein biogenesis in bacteria, and kinase signaling pathways. Notably, his group has made significant contributions to understanding how chaperones like trigger factor function, the mechanisms of outer membrane protein assembly through the Bam complex, and dynamic kinase interactions. Their work has direct implications for neurodegenerative diseases and antibiotic development. The Hiller lab's recent publications demonstrate a strong focus on NMR methodology development, protein folding dynamics, and structural mechanisms of antibiotic action. Their research on darobactin's mechanism of action against Gram-negative bacteria represents a significant advance in antibiotic discovery. The group frequently publishes in high-impact journals including Nature, Science, and Nature Communications. ICMRBS Founder's Medal (2018) EMBO Young Investigator (2014) ERC starting grant (2011) SNSF professorship (2010) SNSF scholarship for young researchers (2008) Professor Hiller supervises numerous PhD students and postdoctoral researchers, with many alumni having secured prestigious positions in academia and industry. His laboratory maintains strong collaborations across multiple institutions and has received significant funding through ERC grants and other competitive mechanisms. The Hiller group also operates advanced NMR facilities that serve the broader research community at the University of Basel.

Aravind Rajeswaranمشاهده پروفایل

پژوهشگر

• Reinforcement Learning
• Representation Learning
• World Models
• +۵ مورد دیگر

Aravind Rajeswaran is a Research Scientist at Meta AI (FAIR) and Visiting PostDoc/Collaborator at Berkeley AI Research Lab (BAIR) at UC Berkeley's College of Engineering, Department of Electrical Engineering and Computer Sciences. He completed his PhD in Computer Science at the University of Washington under Profs. Sham Kakade and Emo Todorov, with additional collaborations with Sergey Levine and Chelsea Finn, and previously earned his bachelor's degree with the best undergraduate thesis award from IIT Madras working with Balaraman Ravindran. His research focuses on building generalist AI agents that operate in open worlds, combining reinforcement learning, representation learning, and world models. Key projects include Locate 3D for real-world object localization, OpenEQA for embodied question answering with foundation models, VC-1 as an artificial visual cortex for embodied intelligence, and R3M as a universal visual representation for robot manipulation. His work demonstrates how pre-trained visual representations can significantly enhance robotic capabilities with minimal supervision. Rajeswaran's publication record shows consistent high-impact contributions across premier AI conferences including NeurIPS, ICML, CVPR, and RSS from 2018 through 2025, with research spanning reinforcement learning, representation learning, robotics, and computer vision. His work on Decision Transformer demonstrated how sequence modeling frameworks can effectively train reinforcement learning policies. Best Paper Award, Scaling Robot Learning Workshop at ICRA 2022 best undergraduate thesis award from IIT Madras As an educator and mentor, Rajeswaran has guided numerous PhD students who have gone on to positions at Stanford, MIT, CMU, Berkeley, and top AI companies including Meta, DeepMind, and Anthropic. He designed and co-taught the Deep Reinforcement Learning course (CSE599G) at UW in 2018, with materials adopted by courses at MIT and CMU, and served as lead TA for Machine Learning for Big Data (CSE547). His research has been supported through his role as Principal Investigator for the Cortex Team at FAIR.

• Virtual Reality
• Social Interaction
• Human-Computer Interaction
• +۴ مورد دیگر

Andrea Stevenson Won is a researcher at Cornell University in the Department of Communication , focusing on virtual reality (VR), human-computer interaction, and social dynamics in immersive environments. Her work explores avatar embodiment , nonverbal behavior , and accessibility in VR for users with disabilities. Research Themes : Virtual embodiment and its psychological effects Accessibility solutions for blind and low-vision users in social VR Nonverbal communication analysis in immersive environments Pro-social behavior through VR interventions Collaborative VR systems and AI integration Recent Article Trends : 2024: Investigated avatar behavior transformation in mixed reality ( MRTransformer ), AI-guided accessibility tools, and nonverbal cue adaptations 2023-2022: Focused on educational VR applications, 360° video narratives, and longitudinal team dynamics 2021-2014: Pioneered avatar embodiment studies, anxiety detection via movement tracking, and homuncular flexibility in VR

Joshua T. Weinhandlمشاهده پروفایل

دانشیار

• Biomechanics
• Lower Extremity Injury Prevention
• Movement Coordination
• +۶ مورد دیگر

Dr. Joshua T. Weinhandl is an Associate Professor in the Department of Kinesiology at the University of Tennessee, part of the College of Education, Health, and Human Sciences. His research focuses on lower extremity injury biomechanics, movement coordination, and neuromuscular control deficits. He teaches courses such as KNS 332 Applied Anatomy and KNS 575 Matlab for Biomechanics. Education: PhD in Biomechanics, University of Wisconsin – Milwaukee MS in Biomechanics, Ball State University BS in Kinesiology, Grenville College Research Interests: Dr. Weinhandl investigates ACL injury mechanisms, knee osteoarthritis, chronic ankle instability, and musculoskeletal injury prevention using kinetic, kinematic, and electromyographic analyses. He emphasizes computational modeling and neuromuscular control to improve intervention strategies. Professional Activities: He serves as a reviewer for journals like Journal of Biomechanics and Medicine & Science in Sports & Exercise , and is a member of the American Society of Biomechanics and the American College of Sports Medicine. Labs: His work aligns with the Biomechanics/Sports Medicine Laboratory and other research groups within the department.

Celso Grebogiمشاهده پروفایل

استاد

• Nonlinear and complex dynamical systems
• Chaos theory
• Fractal geometry
• +۵ مورد دیگر

Professor Celso Grebogi, Sixth Century Chair in Nonlinear & Complex Systems at the University of Aberdeen, is a globally recognized leader in nonlinear dynamics , chaos theory , and systems biology . He founded the Institute for Complex Systems and Mathematical Biology and co-founded the Aberdeen-Lanzhou-Tempe Research Centre. His career spans institutions including University of Maryland, University of São Paulo, and Max-Planck-Society (External Scientific Member since 1998).

Sheng Yangمشاهده پروفایل

استادیار

• Additive Manufacturing
• Digital Twin Technology
• Smart Manufacturing
• +۷ مورد دیگر

Dr. Sheng Yang is an Assistant Professor in the School of Engineering at the University of Guelph. He leads the Design Innovation and Intelligent Manufacturing (DIIM) lab, focusing on advancing additive manufacturing, generative design, and smart manufacturing technologies. His research integrates IoT, big data analytics, and bio-inspired design to address challenges in aerospace, green energy, and healthcare. Key areas include computational design for additive manufacturing, data-driven mass customization, and digital twin-based optimization. Education: Ph.D. in Mechanical Engineering from McGill University (2019), followed by a Postdoctoral Fellowship at McGill (2019–2020). Joined University of Guelph in 2020. Research interests span energy efficiency, complex system optimization, and personalized healthcare products. Recent work emphasizes digital twin synchronization in robotics, machine learning for quality prediction, and sustainable additive manufacturing processes. Notable awards include the 2019 Association of Commonwealth Universities Blue Charter Fellowship and 2018 ASME Best Paper Award. His lab actively seeks partnerships in personalized healthcare, product design, and smart manufacturing. Grants and collaborations focus on advancing manufacturing technologies and sustainability. No formal advisees listed, but active in graduate training through lab projects. The DIIM lab explores cutting-edge solutions for industrial and societal challenges through interdisciplinary approaches.