جست‌وجوی استاد و پژوهشگر

George Amvrosiadisمشاهده پروفایل

استاد پژوهشی

• Distributed Systems
• Cloud Storage
• High Performance Computing (HPC)
• +۴ مورد دیگر

George Amvrosiadis is a Research Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University, with a courtesy appointment in Computer Science. He is a core member of the Parallel Data Lab and spends part of his time at Amazon S3 as an Amazon Scholar. Education: 2016 - Ph.D., Computer Science, University of Toronto 2009 - BA, Computer Science, University of Ioannina Research Interests: His work focuses on distributed systems , operating systems , data analysis , cloud computing , and storage technologies . He explores high performance computing (HPC), zoned storage , systems security , and storage solutions for machine learning . Scientific Trends: Articles highlight innovations in storage systems, including zoned storage , HPC data services , and machine learning infrastructure . Research spans distributed systems , I/O optimization , and data integrity in large-scale environments. Scientific Awards: DeltaFS project received the R&D 100 Award from R&D World Magazine Teaching & Service: He co-teaches graduate courses on storage and cloud systems, serves on program committees for top conferences (SOSP, OSDI, FAST), and mentors students in systems research and infrastructure projects.

Josh Hihathمشاهده پروفایل

استاد

• Molecular Electronics
• Bioelectronics
• Nanoscale Systems
• +۵ مورد دیگر

Josh Hihath is a Professor at Arizona State University and Director of the Biodesign Center for Bioelectronics and Biosensors. He is affiliated with the School of Electrical, Computer, and Energy Engineering and the Biodesign Center for Sustainable Macromolecular Materials and Manufacturing. His interdisciplinary research spans engineering, chemistry, biology, and physics, focusing on molecular-scale systems for electronics, sensing, and healthcare applications. Ph.D. Electrical Engineering (ASU, 2008) M.S. Electrical Engineering (ASU, 2005) B.S. Electrical Engineering (Kettering University, 2003) Research interests center on molecular electronics and biosensors, particularly: Quantum transport in molecular-scale devices Single-molecule conductance measurements Graphene and 2D material-based sensors MEMS-integrated nanosystems Molecular thermoelectrics Electric field-controlled chemical reactions Scientific contributions include pioneering work in nanobioelectronics, with recent publications on DNA-based memory, SARS-CoV-2 variant detection, and hyperbolic metamaterials. His research group develops platforms for integrated single-molecule circuits and high-throughput biosensing.

• Embodied Cognition
• Cognitive Psychology
• Human-Machine Interaction
• +۶ مورد دیگر

Elodie Labeye is a Lecturer in Cognitive Psychology and Ergonomics at the University of Toulouse - Jean Jaurès , affiliated with the Cognition, Languages, and Ergonomics (CLLE) laboratory. She co-directs the L1 Epistemology and L2 Cognitive Psychology Bachelor's degree programs and serves as Deputy Director of the Department of Cognitive Psychology and Ergonomics since 2024. Research Themes : Embodied cognition's role in memory and learning, human-machine interactions in transport (electric/autonomous vehicles), and psycholinguistic norms. Key Projects : Hybrid learning tools via MOODLE (€17,000 regional funding), postdoctoral collaboration on the C2C project (€175,000 regional funding). Academic Contributions include 14 peer-reviewed articles, 9 conference communications, and 5 posters since 2016, focusing on embodied simulations in abstract concept retention, Likert scale reliability, and pedestrian interactions with autonomous vehicles. Her work bridges cognitive theory with applied ergonomics, emphasizing sensory-motor integration in memory and technology acceptability. Advising : Co-supervises doctoral students Quentin Marre , Dimitri Paisios , and Lockman Aalioui , including an industry-linked CIFRE thesis with AFPA.

• Machine Learning
• Neural Networks
• Neuromorphic Computing
• +۳ مورد دیگر

Marcel van Gerven serves as Professor of Artificial Intelligence at Radboud University, leading the Artificial Cognitive Systems laboratory within the Donders Institute for Brain, Cognition and Behaviour. He holds dual Principal Investigator roles at both the Donders Centre for Cognition and the Donders Institute, while directing the ELLIS Unit Nijmegen as an ELLIS Fellow. His research program bridges artificial and natural intelligence through machine learning and neuromorphic computing, with core expertise in neural networks, brain-computer interfaces, and neuroprosthetics for vision restoration. Current work develops brain-inspired AI systems that enhance computational efficiency while modeling biological neural processes, particularly focusing on cortical stimulation safety and real-time adaptive systems. Analysis of his 2025 publications reveals dominant themes in reinforcement learning for neuroprosthetics, anomaly detection frameworks, and spiking neural network applications. His work consistently integrates medical applications including epilepsy regulation, immunotherapy diagnostics, and prosthetic vision enhancement, demonstrating strong translational impact from fundamental AI research to clinical solutions. Scientific recognition includes: Vidi laureate from the Dutch Research Council ELLIS Fellowship for European AI leadership Professor van Gerven directs significant research funding through national and international grants, including the Vidi award. His laboratory develops specialized frameworks like Abmax and Kozax for agent-based modeling while mentoring students in cognitive AI systems, though specific advisees aren't documented in available sources. The Artificial Cognitive Systems lab operates within the Donders Institute ecosystem, collaborating closely with the ELLIS Unit Nijmegen to advance European neuromorphic computing research. Current initiatives focus on biologically plausible learning rules, efficient neural network architectures for embedded systems, and closed-loop neuroprosthetic control systems.

Jonathan Aldrichمشاهده پروفایل

استاد

• Programming Languages
• Software Engineering
• Verification
• +۷ مورد دیگر

Jonathan Aldrich is a Professor of Computer Science at Carnegie Mellon University in the School of Computer Science , jointly appointed in the Software and Societal Systems Department and the Computer Science Department . He is an internationally recognized expert in programming languages, software engineering, and verification, with a strong emphasis on human factors and usability in language design. Education: Ph.D. in Computer Science and Engineering, University of Washington (2003) B.S. in Computer Science, Caltech Research Interests: Prof. Aldrich's research lies at the intersection of programming languages and software engineering , focusing on how language design affects software quality and developer productivity. His work spans: Gradual verification and type systems Ownership and typestate checking Security and information flow control Usability of advanced type systems Domain-specific languages for blockchain and IoT Recent Work Trends: His recent publications emphasize gradual verification techniques, which allow developers to incrementally verify software correctness. He has also explored liquid types , information flow control , and usability barriers in advanced type systems. His work often combines formal methods with empirical studies to ensure practical impact. Awards & Recognition: NSF CAREER Award (2006) Dahl-Nygaard Junior Prize (2007) ICSE Most Influential Paper Award (2012) DARPA Computer Science Study Group Leadership & Service: Prof. Aldrich has held numerous leadership roles in the academic community, including: Director, CMU Software Engineering Ph.D. Program (2013–2019) General Chair, SPLASH 2015 Program Chair, OOPSLA 2017 Steering Committee Chair, SPLASH (2017–2019) Member, ACM Publications Board Industry Engagement: He is the Chief Technology Officer of Noteful , a startup he co-founded during his 2022 sabbatical, focused on music education through interactive apps.

Michael Rudermanمشاهده پروفایل

استاد

• motion control
• robotics and mechatronics
• nonlinear systems with memory
• +۳ مورد دیگر

Michael Ruderman is a Professor in the Department of Engineering Sciences at the University of Agder, Norway, where he has been working since June 2020 (previously as Associate Professor from October 2015 to June 2020). He is currently on sabbatical from January 2025. Prior to his position at UiA, he held academic appointments at Nagaoka University of Technology, Nagoya Institute of Technology, and Technical University Dortmund. His research focuses on: Motion control and robotics Mechatronics systems Nonlinear systems with memory Nonlinear, hybrid, and robust control methodologies Ruderman's work centers on the analysis and compensation of kinetic friction in robotic and mechatronic control systems, culminating in his 2023 book 'Analysis and Compensation of Kinetic Friction in Robotic and Mechatronic Control Systems'. His research bridges theoretical control concepts with practical engineering applications, particularly in hydraulic systems, robotic actuators, and systems with hysteresis and friction effects. His recent publications (2024-2025) demonstrate a strong emphasis on advanced control techniques for complex mechanical systems, with particular focus on sliding mode control, nonlinear damping, hysteresis compensation, and oscillation control. Many of his papers address real-world challenges in hydraulic actuators, robotic systems, and mechanical interfaces with friction. Professionally, Ruderman serves on the editorial boards of IEEE Transactions on Control Systems Technology, IFAC Control Engineering Practice, IFAC Mechatronics, and IEEE/ASME Transactions on Mechatronics. He previously chaired the IEEE-IES Technical Committee on Motion Control (2018-2021) and served on the Management Committee of IEEE/ASME Transactions on Mechatronics (2020-2023). Ruderman has been actively involved in numerous research projects including DAAD mobility grants, H2020-MSCA-RISE projects on robust control, and several Research Council of Norway (RCN) projects focusing on fractional-order systems, nonlinear control methods, and compensators for non-minimum phase systems. He teaches courses including Control Theory (MSc), Advanced Control and Robotics (PhD), Electromagnetic Modeling (PhD), and Feedback Control Systems 1 (BSc), demonstrating his commitment to educating the next generation of control engineers and robotics specialists.

Emanuel Grosuمشاهده پروفایل

پژوهشگر

• cultural memory
• ethics
• social epistemology
• +۵ مورد دیگر

Emanuel Grosu is a Researcher at the Institute for Interdisciplinary Research , Department of Socio-Human Sciences, affiliated with Alexandru Ioan Cuza University of Iași . His work bridges cultural memory , ethics , and medieval Latin literature with a focus on translation and hermeneutics , Latin paleography , and the transmission of classical values . Dr. Grosu specializes in medieval Latin texts and their modern interpretations, particularly examining religious and cultural memory through works like the Visio Tnugdali and History of the Lombards . He actively contributes to academic discourse as a translator and editor of significant medieval works, including Anselm of Canterbury and Summa Theologica by Thomas Aquinas. His research interests span medieval mentalities , digital humanities , and interdisciplinary methodologies . Recent publications explore digitalization in classical studies , medieval theological concepts , and scientific communication in medieval Europe. He has participated in national and international conferences, including the International Academy of Heraldry and Explorations in Biblical Tradition symposiums.

Eugene Terentjevمشاهده پروفایل

استاد

• Polymer Physics
• Soft Matter Physics
• Liquid Crystal Elastomers
• +۴ مورد دیگر

Professor Eugene Terentjev is a leading academic in Polymer Physics at the University of Cambridge , affiliated with the Department of Physics and the Biological and Soft Systems research group. His work bridges theoretical and applied research in soft matter, focusing on polymer networks and liquid crystal elastomers. Current academic rank: Professor Key research areas: Polymer Physics, Soft Matter, Smart Materials Publications highlight advancements in liquid crystal elastomers, dynamic crosslinking, and mechanical damping applications Research Interests: Terentjev's work centers on the physics of polymer networks , with emphasis on liquid crystal elastomers for smart and responsive materials. Recent projects include: Dynamic crosslinking for reprocessable polymers Photochemical and mechanical actuation in elastomers Pressure-sensitive adhesives and impact damping systems Biological applications like organoid patterning and cell mechanics Scientific Trends: His publications reveal a strong focus on liquid crystal elastomers for soft robotics, adhesives, and biofabrication. Key subfields include dynamic crosslinking , non-linear elasticity , and stimuli-responsive materials , often combining theoretical and experimental approaches. Collaborations & Legacy: Terentjev has collaborated with late pioneers like Professor Mark Warner , whose obituary he co-authored, indicating a deep engagement with the liquid crystal elastomer community. His work is prominently featured in Advanced Science and other high-impact journals.

Mohammad Rastegariمشاهده پروفایل

استادیار مدعو

• Computer Vision
• Efficient Machine Learning
• Model Compression
• +۳ مورد دیگر

Mohammad Rastegari serves as a senior technical manager in Apple's AI/ML organization and holds an affiliate assistant professor position in the Computer Science and Engineering Department at the University of Washington. Previously, he was a research scientist at the Allen Institute for AI (AI2) where he contributed to the PRIOR team, and co-founded XNOR.ai as Chief Technology Officer. He completed his Ph.D. at the University of Maryland under the supervision of Professor Larry S. Davis, focusing on computer vision and machine learning. His research centers on efficient deep learning with major contributions in binary neural networks (notably XNOR-Networks for resource-constrained devices) and model compression . Current work extends to large language model efficiency through weight clustering, token pruning, and memory optimization while maintaining strong foundations in computer vision. Analysis of his recent publications reveals a strategic shift toward optimizing transformer-based architectures across vision and language domains, with consistent emphasis on deployable solutions for edge computing and real-world applications. He co-founded XNOR.ai (acquired by Apple) and contributed to AI2's PRIOR initiative, demonstrating a career trajectory bridging academic innovation and industrial implementation in efficient AI systems.

• Temporal Data Representation
• Semantic Web
• Uncertainty Management
• +۳ مورد دیگر

Nassira Achich is a researcher at the Cédric Laboratory, Conservatoire National des Arts et Métiers (CNAM), specializing in temporal data representation and imperfection handling within Semantic Web frameworks. Her work develops OWL 2 ontological solutions for uncertain, imprecise, and conflicting temporal data with applications in Alzheimer's care systems and collective memory projects. She holds a PhD jointly awarded by HESAM Université and Université de Sfax (Tunisia) in 2021 for her thesis on temporal data imperfection in Alzheimer's patient software. Her educational background bridges French and Tunisian academic institutions with a focus on practical healthcare applications. Dr. Achich's research centers on integrating imperfection theories (possibility, probability, evidence theory) into semantic technologies for robust temporal reasoning. She addresses core challenges in representing uncertain time intervals, resolving data conflicts, and modeling imprecision within ontological frameworks, contributing significantly to knowledge representation under uncertainty. Analysis of her 12 publications (2019-2024) reveals consistent methodological progression from foundational typologies of temporal imperfection (2019) to advanced ontology implementations (2024). Her work spans theoretical comparisons of uncertainty frameworks and practical implementations in healthcare contexts, published in venues including Journal of Intelligent and Fuzzy Systems, New Generation Computing, and ISWC. No scientific awards or honors are documented in the source material. Information regarding student supervision, grant funding, or administrative roles is absent from the provided publications list. Her academic contributions appear focused on independent research within the Cédric Laboratory's collaborative environment. As a member of Cédric Laboratory's research teams, she contributes to axes including 'Complex data, machine learning and representations' and 'Data mining and statistics,' working within interdisciplinary groups advancing semantic technologies for real-world data challenges.

Supriyo Dattaمشاهده پروفایل

استاد

• Spintronics
• Quantum Computing
• Probabilistic Computing
• +۳ مورد دیگر

Supriyo Datta is the Thomas Duncan Distinguished Professor of Electrical and Computer Engineering at Purdue University, affiliated with the School of Electrical and Computer Engineering. His work bridges physics and computing, focusing on nanoscale devices and quantum phenomena. He pioneered spintronics and proposed spin transistors, foundational to modern spin-based electronics. His research on negative capacitance aims to extend Moore’s Law, while recent work explores probabilistic computing via p-bits, addressing complex problems at room temperature. Research Interests: Probabilistic Computing Spintronics and Quantum Transport Nanoelectronics and Device Simulation Unconventional Computing Architectures He authored seminal books like Quantum Transport: Atom to Transistor , which underpin semiconductor device modeling. His NEGF formalism is industry-standard for nanotransistor design. Datta’s contributions earned him NAE membership and global recognition in physics and engineering. Awards: Elected to the National Academy of Engineering (NAE) His group has advised over 50 PhD students, advancing fields from molecular electronics to autonomous probabilistic hardware. Current projects include p-bit-based Ising machines and spin-inspired quantum emulation systems.

• Quantum Optics
• Nanophotonics
• Nanofabrication
• +۳ مورد دیگر

Dr. Mehran Kianinia is a Chancellor's Research Fellow at the School of Mathematical and Physical Sciences, University of Technology Sydney (UTS) . His research focuses on quantum optics, nanophotonics, and nanofabrication, with an emphasis on optically active defects in hexagonal boron nitride (hBN) for quantum sensing and computation. He holds a PhD in Physics (2018) from UTS, following a B.Sc. (2007) and M.Sc. (2010) in Materials and Science Engineering. He has secured grants from the Australian Research Council (ARC) and the US Office of Naval Research to investigate quantum technologies using hBN defects. Notably, he received the Excellence in Research Award from his school in 2021. Dr. Kianinia supervises PhD and honors students, coordinates the Optics (68206) course, and lectures in physics bridging programs. His research outputs include pioneering work on spin defects in hBN, quantum emitters, and plasmonic enhancement strategies. Key contributions span optical coherence engineering, defect fabrication via focused ion beams, and magnetic field sensing optimizations. His funded projects aim to develop scalable quantum systems and memory technologies. Dr. Kianinia collaborates widely, with over 98 research outputs since 2018. His work bridges fundamental physics with applied nanotechnology, targeting quantum communication, computation, and high-precision sensing applications.

• Archaeology
• Near Eastern Studies
• Prehistoric Archaeology
• +۷ مورد دیگر

Pavol Hnila is a Researcher at the Institute of Ancient Near Eastern Studies within the Department of History and Cultural Studies at Free University of Berlin. He serves as Project Director for the DFG-funded project 'High Mountains as Cultural Landscapes: Studies on the Interconnection of Pastoralism, Cult, and Climate Change in Prehistoric Armenia', conducting fieldwork in the Armenian Highlands with a focus on Mount Aragats. Hnila specializes in high-altitude archaeology of the South Caucasus, with particular expertise in vishap stelae (dragon stones) and ritual landscapes. His research integrates traditional field archaeology with archaeometric methods including machine learning for obsidian sourcing, geochemical analysis of stone monuments, and digital elevation model assessment. He examines prehistoric adaptation to mountainous environments through studies of pastoralism, settlement patterns, and cultural responses to climate change. His publication trends reveal deep engagement with Armenian prehistory, particularly ritual practices surrounding vishap monuments and high-altitude burial sites. Recent work demonstrates increasing methodological sophistication through computational approaches to material culture analysis while maintaining strong field-based documentation of endangered cultural heritage sites across the Armenian Plateau. Dr. Hnila leads the DFG project team conducting interdisciplinary research in Armenia, supported by student assistant Nikolai Techow. His work involves collaboration with international specialists in archaeometry, geology, and remote sensing to document and interpret high-mountain cultural landscapes. The research team operates in challenging high-altitude environments of Armenia, focusing on the cultural significance of vishap stelae within ritual landscapes. Fieldwork combines systematic survey, targeted excavation, and scientific analysis to understand prehistoric adaptation strategies, monument construction techniques, and ritual practices in mountainous terrain, with particular attention to preservation challenges facing these unique heritage sites.

Tian Zhongمشاهده پروفایل

استادیار

• Quantum Photonics
• Quantum Information
• Quantum Networking
• +۳ مورد دیگر

Tian Zhong is an Assistant Professor of Molecular Engineering at the University of Chicago's Pritzker School of Molecular Engineering. His research focuses on quantum photonics and solid-state quantum technologies, particularly leveraging rare-earth doped materials for quantum networks and optical quantum memory. He completed his PhD in Electrical Engineering at MIT (2013) and a postdoc at Caltech’s Institute of Quantum Information and Matter. Key roles include pioneering rare-earth quantum nanophotonics and developing scalable quantum optical networks. Research interests include quantum entanglement purification, epitaxial thin films for quantum devices, and hardware-software co-design for quantum computing. Notable achievements include a DoD ARO Young Investigator Award (2020) and an NSF CAREER Award (2020). His lab, Zhong Quantum Lab, explores quantum interconnects and hybrid systems, with recent grants from the Betty Moore Foundation for novel quantum matter projects. Publications span quantum networking protocols, coherence properties of rare-earth ions, and interdisciplinary studies in microbiome-gut-brain interactions. Advising focuses on training students in quantum device fabrication and theoretical modeling, with active projects on dilution fridge setups and quantum repeater networks.

• Materials Science
• Mechanical Engineering
• Plasticity of Materials
• +۶ مورد دیگر

R. Klassen is a Professor in the Department of Mechanical and Materials Engineering at Western University, located in London, Ontario. He holds a Ph.D. from the University of Toronto (1990) and has extensive industry experience as a Scientist/Engineer at Atomic Energy of Canada Ltd. (1990–1999). His research focuses on experimental studies of rate-dependent plasticity, particularly the role of microstructural interfaces (e.g., grain boundaries) in material deformation. Education: Ph.D., Metallurgy and Materials Engineering, University of Toronto (1990) M.Sc., Mechanical Engineering, University of Manitoba (1986) B.Sc., Mechanical Engineering, University of Manitoba (1984) Awards: Dr. Terry Base Memorial Teaching Award (2009, 2013) R. Klassen’s lab is equipped with high-temperature nano/micro-indentation facilities and collaborates with specialized characterization centers like Surface Science Western and the Brockhouse Institute. His research group investigates materials such as zirconium alloys, nickel-based superalloys, and magnesium, focusing on deformation mechanisms, irradiation effects, and high-temperature behavior. Current students include postdoctoral researchers and Ph.D. candidates exploring topics like ion-implanted nickel alloys and irradiated zirconium. His articles emphasize nanomechanical testing, indentation-based stress analysis, and the impact of microstructural features on material performance. Key themes include FCC alloy behavior, flow forming processes, and the mechanical properties of nuclear materials. In teaching, he instructs graduate courses on plasticity and undergraduate courses in materials science and nuclear engineering. His lab also hosts projects like micro-pillar compression and micro-sphere testing, supported by advanced microscopy and diffraction techniques.