جست‌وجوی استاد و پژوهشگر

Xiaodi Wuمشاهده پروفایل

دانشیار

• Quantum Computing
• Quantum Applications in Optimization and Machine Learning
• Formal Methods and Programming Languages in Quantum Computing
• +۲ مورد دیگر

Xiaodi Wu is an Associate Professor in the Department of Computer Science at the University of Maryland, College Park, with affiliations to the Institute for Advanced Computer Studies and the Joint Center for Quantum Information and Computer Science (QuICS). They also serve as an Amazon Visiting Academic at AWS Braket. Education: Ph.D. in Theoretical Computer Science (University of Michigan, 2013); B.S. in Mathematics and Physics (Tsinghua University, 2008). Their research bridges theoretical foundations of quantum computing with practical implementations, focusing on computational models for quantum device programmability and systems for operating quantum machines. Key areas include quantum programming languages, formal verification, and robustness analysis. Recent work includes SimuQ (quantum simulation frameworks) and Qafny (quantum program verification). Publications emphasize verification of quantum compilers, algebraic reasoning, and differentiable quantum languages. Scientific Awards: Sloan Research Fellow, NSF CAREER, AFOSR YIP. Xiaodi Wu has advised numerous students and mentored interns, contributing to quantum complexity theory and cryptographic protocols. They actively participate in organizing committees for conferences like POPL and PLDI.

Frank Muellerمشاهده پروفایل

استاد

• Parallel Computing
• Quantum Computing
• Real-Time Systems
• +۵ مورد دیگر

Frank Mueller is a Professor in the Department of Computer Science at North Carolina State University's College of Engineering. He maintains an active research and teaching profile with upcoming courses scheduled through 2025, including Parallel Systems (CSC 548), Embedded/Real-Time Systems for Autonomous Driving with Machine Learning, and Quantum Computing. His research interests span multiple cutting-edge computing domains. Mueller is a member of The NSF Quantum Leap Challenge Institute for Robust Quantum Simulation His work bridges theoretical computer science with practical applications in high-performance computing environments. Professor Mueller has been actively involved in numerous conferences including PLDI, PPoPP, LCTES, and IEEE Quantum Week events through 2026, serving on program committees and organizing workshops related to quantum computing and high-performance systems. His teaching portfolio demonstrates significant expertise across multiple domains of computer systems, with courses ranging from foundational operating systems to advanced quantum computing. He has developed specialized teaching resources including the Arc Cluster for parallel systems education and maintains active connections with industry through equipment donations from companies like ARM, Google, and Microsoft.

• Virtual Reality
• Serious Games
• 3D Visualization
• +۴ مورد دیگر

Ivan Carmosino is a Contract Professor in the Department of Italian, Romance, Classical, Arts, and Entertainment Studies (DIRAAS) at the University of Genoa. He teaches the course '3D Visualizations for the Analysis of Artistic and Architectural Heritage' within the Master's Degree Course in History of Art and Promotion of Artistic Heritage. His research spans virtual reality, serious games, and 3D visualization with direct applications in cultural heritage preservation, transportation systems, and health monitoring. He develops interactive environments leveraging gamification principles and real-time data processing to solve domain-specific challenges in artistic analysis, traffic management, and ergonomic assessment. Analysis of his recent publications (2017-2018) reveals a consistent interdisciplinary approach bridging computer science with practical domain applications. His work demonstrates strong focus on immersive technologies for tangible real-world problems, particularly in virtual heritage reconstruction, traffic flow optimization, and health-focused behavioral interventions through game mechanics.

Jérôme DURAND-LOSEمشاهده پروفایل

استاد

• Computational Models
• Cellular Automata
• Unconventional Computation
• +۷ مورد دیگر

Jérôme DURAND-LOSE is a Professor of Computer Science at the University of Orléans, France, affiliated with the Faculty of Science and Technology and the Department of Computer Science. He is a member of the Graphs, Algorithms and Calculation Models team at LIFO (Fundamental Computer Science Laboratory of Orléans) and serves as Deputy Scientific Director for Europe and International at CNRS Computer Sciences since May 2024. He completed his PhD in Computer Science at the University of Bordeaux I in 1996, followed by a Habilitation à Diriger des Recherches (HDR) from the University of Nice-Sophia Antipolis in 2003. His academic career includes positions as Lecturer at the University of Nice-Sophia Antipolis (1998-2004), CNRS delegation to LIP (Laboratory of Parallel Computing) at ÉNS Lyon (2002-2004), and recruitment as University Professor at the University of Orléans in 2004. He has been promoted through the professorial ranks to the second exceptional class in 2023. DURAND-LOSE's research focuses on unconventional models of computation, particularly signal machines for abstract geometrical computation in Euclidean spaces. His work explores cellular automata, reversible computing, distributed systems, and self-stabilization. He has made significant contributions to understanding geometric computation, collision computing, and computational universality in continuous space-time models. His research demonstrates how continuous geometry can be harnessed for both classical and hypercomputation. His recent publications demonstrate a consistent focus on abstract geometrical computation, with particular emphasis on signal machines capable of representing complex mathematical structures like infinite countable linear orderings. His work bridges theoretical computer science with geometric and continuous models of computation, exploring both classical and hypercomputation capabilities through the manipulation of signals in Euclidean space. Member of the Editorial Board of the International Journal of Unconventional Computing (2011-) Chair of the Steering Committee of the International Conference on Machines, Computations and Universality (2013-) Member of the Board of the Computability in Europe association (2011-2014) Participation in 32 international conference program committees, including 9 as chair As an academic leader, DURAND-LOSE has supervised four PhD students to completion, served as Director of LIFO (Fundamental Computer Science Laboratory of Orléans) from 2010-2016, and held various administrative roles including Provisional Administrator of the UFR Sciences and Technology (2020-2021). He has been actively involved in the organization of numerous international conferences in unconventional computation, including chairing program committees for MCU and UCNC conferences. He is affiliated with LIFO (Fundamental Computer Science Laboratory of Orléans, ÉA 4022), where he leads the Graphs, Algorithms and Calculation Models team. His laboratory work focuses on geometric computation models, signal machines, and their applications to understanding computational universality in continuous spaces.

• Network Science
• Applied Dynamical Systems
• Mathematical Biology
• +۴ مورد دیگر

Joel Nishimura is an Associate Professor at Arizona State University's School of Mathematical and Natural Sciences. His research spans several interconnected fields including network science, dynamical systems, and mathematical biology. He focuses on how simple rules can create complex behaviors and structures, with applications in biological systems, network algorithms, and engineered protocols. Dr. Nishimura received his Ph.D. from Cornell University in 2013. His dissertation explored decentralized coordination and how actors with limited information can coordinate their timing. His research interests include Network Science, Applied Dynamical Systems, Mathematical Biology, Mathematical Modeling, and Game Theory. A unifying feature of his work is examining how simple rules can create complex behaviors and structures. In biological settings, these simple models capture key qualitative features of observed behaviors, suggesting generalizable principles. In network settings, simple rules form the basis for predictive algorithms, while in engineered settings, they serve as backbones for robust decentralized protocols. Analysis of Dr. Nishimura's recent publications reveals a strong focus on network science and its applications across multiple domains. His work spans theoretical foundations of graph theory and network models, applications to social and biological systems, and connections to decision-making processes and game theory. A notable trend is his consistent exploration of how simple rules or interactions can produce complex emergent phenomena, whether in network structures, biological behaviors, or decision-making processes. Dr. Nishimura has supervised several undergraduate and graduate students, as indicated by the asterisks and other symbols in his publication record. His teaching includes courses such as Applied Linear Algebra (MAT 343), Individualized Instruction (MAT 499), Honors Directed Study (MAT 492), and Honors Thesis (MAT 493). His research has been supported by various grants, though specific details are not provided in the available information. His GitHub repository for the "Double Edge Swap MCMC Graph Sampler" suggests involvement in computational tools development for network science research.

Karine Even-Mendozaمشاهده پروفایل

مدرس

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

Karine Even-Mendoza is a Lecturer in Systems & Programming Languages at King's College London, working within the Department of Informatics in the Faculty of Natural, Mathematical & Engineering Sciences. Previously, she was a Research Associate at Imperial College London's Department of Computing, where she worked in the Software Reliability Group and Multicore Programming Group. She completed her PhD at King's College London, where she also spent four years working with the Software Systems (SSY) group. Dr. Even-Mendoza's research focuses on the intersection of software testing, verification, and programming languages, with recent work increasingly incorporating machine learning and quantum computing techniques. Her work addresses critical challenges in compiler testing, system simulation validation, and the application of large language models to software engineering problems. She has developed innovative approaches like ReFuzzer for enhancing the validity of LLM-generated test programs and SearchGEM5 for improving the reliability of system simulators through search-based testing. Her publication record demonstrates a strong trajectory in top-tier software engineering venues, with a notable shift toward incorporating large language models and quantum computing in recent years. She has become particularly active in applying AI techniques to traditional software engineering challenges, bridging the gap between classical software verification methods and modern AI approaches. Her work spans both theoretical foundations and practical applications, with implementations like CsmithEdge and GrayC contributing tangible tools to the software testing community. Dr. Even-Mendoza has been actively involved in the software engineering research community, serving on program committees for major conferences including ASE, ISSTA, ECOOP, and SPLASH. She has also contributed to artifact evaluation processes, demonstrating her commitment to research reproducibility and scientific rigor in software engineering.

Andreas Demouمشاهده پروفایل

پژوهشگر

• Fluid Dynamics
• Computational Fluid Dynamics
• Turbulent Flows
• +۳ مورد دیگر

Andreas Demou serves as a Computational Scientist at the Computation-based Science & Technology Research Center (CaSToRC) of The Cyprus Institute, where he conducts research at the intersection of fluid dynamics and computational methodology. His academic background includes: Bachelor of Science in Physics Master of Science in Energy Technologies and Sustainable Design Doctor of Philosophy in Mechanical Engineering from the University of Cyprus Research Interests: Dr. Demou specializes in thermally-driven turbulent flows, weakly compressible multiphase systems, and wetting hydrodynamics. His methodological approach combines direct numerical simulation (DNS), large-eddy simulation (LES), and cutting-edge data-driven techniques to model complex fluid phenomena. This work bridges classical computational physics with modern machine learning applications in fluid mechanics. He is currently engaged in the CoE RAISE project, which funds his research on data-driven wetting hydrodynamics through computational innovation and interdisciplinary collaboration within CaSToRC's high-performance computing environment.

Abigail P. Dowlingمشاهده پروفایل

دانشیار

• Environmental History
• Medieval Studies
• Classical Studies
• +۴ مورد دیگر

Dr. Abigail P. Dowling serves as Associate Professor of History in Mercer University's College of Liberal Arts and Sciences, where she has taught since 2015. Her courses include the Western Histories survey, pre-modern history sequences (HIS 201, 301, 307, 310), and Great Books seminars (GBK 101, 304), featuring innovative pedagogical tools like Minecraft, virtual reality, and role-playing simulations. She advises Mercer's Phi Alpha Theta History Honors Society chapter and serves as Historian for the university's Phi Beta Kappa chapter. Her academic credentials include: Ph.D. in History and Medieval Studies, University of California, Santa Barbara M.A. in History, University of California, Santa Barbara B.A. in History and French, University of Arizona As an environmental historian and digital medievalist, Dowling investigates premodern resource systems through socio-cultural and intellectual lenses. Her research employs spatial analysis and database methodologies to examine how medieval societies constructed, utilized, and conceptualized natural resources, with current work focusing on fourteenth-century France. She actively integrates students into her digital humanities projects. Her publication portfolio reveals consistent thematic threads across environmental history, medieval resource management, and gender studies. Recent works demonstrate sophisticated interdisciplinary approaches combining GIS visualization, archival research, and theoretical frameworks from sustainability studies, with recurring emphasis on spatial dynamics of resource exploitation and socio-political implications of environmental management in premodern Europe. No scientific awards are documented in the source material, though Dowling holds significant leadership roles in two prestigious academic honor societies. Student mentorship defines Dowling's academic practice through Phi Alpha Theta advising, conference preparation support, and event coordination. She cultivates research opportunities by integrating students into her digital projects, providing hands-on training in MySQL databases and GIS visualization for historical analysis. Dowling is developing a collaborative research environment centered on her spatial analysis project of medieval French resource management, designed to train students in digital methodologies while reconstructing historical resource flows through innovative technological approaches.

Daniel Grierمشاهده پروفایل

استادیار

• Quantum complexity theory
• Quantum computing
• Quantum algorithms
• +۴ مورد دیگر

Daniel Grier is an Assistant Professor in the Computer Science and Engineering department at the Jacobs School of Engineering and the Mathematics department at the University of California, San Diego. His research focuses on quantum complexity theory, particularly near-term quantum computing paradigms and proving quantum advantage over classical counterparts. His educational background includes: PhD in Computer Science from MIT under Scott Aaronson B.S. in Computer Science and Mathematics from the University of South Carolina Postdoctoral research at the Institute for Quantum Computing at the University of Waterloo Grier's research interests center on quantum computational complexity, with particular emphasis on demonstrating quantum advantage through rigorous complexity-theoretic proofs. His work spans quantum algorithms, circuit complexity, and the theoretical foundations of quantum computing. He has made significant contributions to understanding the complexity of BosonSampling variants, Clifford circuits, and interactive quantum protocols that demonstrate quantum advantage even with limited computational resources. His publications reveal a consistent focus on establishing unconditional separations between quantum and classical computational power, particularly in near-term settings. His work often bridges theoretical computer science with practical considerations for implementing quantum algorithms on emerging hardware platforms, making him a key contributor to the field of quantum complexity theory. His scientific achievements include: Best Paper Award at TQC 2025 / CCC 2025 for 'Quantum Threshold is Powerful' Grier actively mentors students and has advised several researchers who have become co-authors on his publications. He teaches graduate and undergraduate courses including 'Quantum Complexity Theory,' 'Introduction to Quantum Computing,' and 'Discrete Mathematics and Graph Theory.' His teaching spans multiple departments, reflecting the interdisciplinary nature of his work. He leads a research group focused on quantum complexity theory where students explore theoretical foundations of quantum computing, working on problems related to quantum advantage, circuit complexity, and quantum algorithms for near-term devices.

Narayanan Rengaswamyمشاهده پروفایل

استادیار

• Classical Error Correction
• Quantum Error Correction
• Quantum Computing
• +۳ مورد دیگر

Narayanan Rengaswamy is a tenure-track Assistant Professor in the Department of Electrical and Computer Engineering at the University of Arizona. He is also a member of the NSF Engineering Research Center for Quantum Networks (CQN) and the DoE-funded Superconducting Quantum Materials and Systems (SQMS) Center. His educational background includes: PhD in Electrical and Computer Engineering from Duke University (2020) MS in Electrical Engineering from Texas A&M University (2015) BTech in Electronics and Communication Engineering from Amrita University, India (2013) Rengaswamy's research focuses on the intersection of classical and quantum information theory, with particular expertise in error correction techniques for quantum systems. His work spans quantum computing, quantum networking, and quantum communications, developing novel approaches to fault-tolerant quantum information processing. He has made significant contributions to quantum LDPC codes, stabilizer codes, and the Clifford hierarchy, bridging classical coding theory with quantum applications. His research has practical implications for building scalable quantum computers and quantum networks. His publication record reveals a strong focus on quantum error correction, with particular attention to LDPC codes, stabilizer codes, and fault-tolerant architectures. The research trajectory shows progression from foundational work on classical-quantum connections to increasingly sophisticated quantum error correction schemes, with growing emphasis on practical implementations for quantum hardware. Awards and recognitions include: Selected for a talk at the 2020 Conference on Quantum Information Processing (QIP) Chosen finalist for the NSF ERC Perfect Pitch Competition Rengaswamy serves as a reviewer for several journals and conferences, and was on the Posters Program Committee of the 2022 International Conference on Quantum Computing and Engineering (QCE22). He is actively involved in quantum research initiatives through the NSF-ERC Center for Quantum Networks and the DoE-funded SQMS Center. His work combines theoretical depth with practical applications for emerging quantum technologies. He is a member of the IEEE and the Information Theory Society, contributing to the quantum information community through research, service, and academic leadership.

• Quantum Physics
• Quantum Computing
• Quantum Technology
• +۳ مورد دیگر

Göran Johansson is a Professor of Applied Quantum Physics at Chalmers University of Technology in Gothenburg, Sweden. Since January 1, 2025, he has served as the director of the Wallenberg Centre for Quantum Technology, a major research initiative spanning from 2018 to 2030. His academic career is centered on quantum physics research with a focus on both fundamental phenomena and practical quantum technology applications. Professor Johansson's research spans quantum physics, quantum technology, and quantum computing. He investigates fundamental quantum mechanical effects such as the dynamic Casimir effect, which describes photon generation from vacuum when a mirror accelerates at relativistic speeds. His applied research focuses on building quantum computers that leverage quantum superposition and entanglement to solve problems beyond the reach of classical supercomputers, with potential applications in drug discovery, artificial intelligence, and optimization problems like traffic planning. His work bridges theoretical quantum physics with practical implementation in superconducting circuits. An analysis of his recent publications reveals a strong focus on quantum computing hardware, particularly superconducting qubits and quantum processors. His research addresses key challenges in quantum computing including decoherence, quantum gate fidelity, quantum error correction, and quantum state engineering. There's a clear progression toward more complex quantum systems, with recent work exploring multi-qubit gates, quantum algorithms for practical applications, and integration of quantum processors. His publications consistently appear in top physics journals including Physical Review Letters, Physical Review A/B, and npj Quantum Information. Professor Johansson has received two significant awards for his contributions to quantum physics: Edlund Prize 2016 from the Royal Swedish Academy of Sciences Albert Wallin Science Prize 2015 from the Royal Society of Science and Letters in Gothenburg He leads or participates in multiple major research projects including the Wallenberg Centre for Quantum Technology (2018-2030), Quantum Networks with Delay and High-Impedance Transmission Lines (2022-2025), Quantum Information with Microwaves and Surface Acoustic Waves (2018-2021), and Quantum Plasmonics (2017-2022). These projects involve collaborations with numerous researchers across Chalmers and with external partners, supported by funding from the Swedish Research Council (VR) and the Knut and Alice Wallenberg Foundation. As director of the Wallenberg Centre for Quantum Technology, Professor Johansson oversees one of Sweden's largest quantum research initiatives, which includes a broad team of researchers working on quantum computing, quantum communication, and quantum sensing. His research group focuses on superconducting quantum circuits, exploring both fundamental quantum phenomena and practical implementations for quantum information processing. The group works extensively with microwave quantum optics and has made significant contributions to the understanding and manipulation of quantum states in superconducting systems.

Christine Muschikمشاهده پروفایل

دانشیار

• Quantum Computing
• Quantum Information Science
• Quantum Simulation
• +۳ مورد دیگر

Christine Muschik is an Associate Professor and University Research Chair at the University of Waterloo. Her research focuses on quantum computing, quantum simulation, and theoretical physics, particularly in the context of lattice gauge theories and quantum algorithms. She explores applications of quantum technologies to problems in particle physics, condensed matter physics, and high-energy phenomena. Her work bridges quantum information science with experimental implementations in superconducting circuits, trapped ions, and optical systems. She is affiliated with research groups in Photonics, Atomic/Molecular/Optical Physics, and Quantum Information & Computing. Her research interests emphasize developing scalable quantum algorithms for simulating complex physical systems, error mitigation techniques, and hybrid quantum-classical methods. She investigates topological phases, gauge symmetries, and real-time dynamics in quantum systems. Recent work includes quantum simulations of quantum chromodynamics, variational approaches for hadron dynamics, and superposed quantum gate protocols. Muschik’s publications span quantum error correction, measurement-based algorithms, and the integration of quantum technologies with classical computational frameworks. She collaborates across disciplines to advance both theoretical and experimental quantum computing. Her research contributes to foundational understanding of quantum systems while addressing practical challenges in quantum hardware and algorithm design. Her articles highlight advancements in simulating lattice gauge theories, optimizing variational quantum eigensolvers, and applying neural networks to quantum state tomography. These contributions underscore her role as a leader in applying quantum computing to fundamental physics problems.

Robyn Macdonaldمشاهده پروفایل

استادیار

• Hypersonic Flows
• Chemically Reacting Flows
• Chemical Kinetics
• +۴ مورد دیگر

Robyn Macdonald is an Assistant Professor in the Department of Aerospace Engineering Sciences at the University of Colorado Boulder, affiliated with the Aerospace Mechanics Research Center (AMREC). She holds a PhD and BS in Aerospace Engineering from the University of Illinois at Urbana-Champaign (2019 and 2013, respectively). Her research focuses on predictive modeling of hypersonic flows, including gas-phase chemistry modeling, turbulent flow dynamics, and laminar-to-turbulent transition predictions. She employs computational tools ranging from molecular dynamics to high-fidelity CFD simulations to study hypersonic vehicles' flowfields. Key research interests include hypersonic flows, chemically reacting flows, chemical kinetics, and radiation modeling. Her lab develops reduced-order models and advanced simulation techniques to address challenges in non-equilibrium aerothermodynamics and high-speed aerodynamics. Educations: PhD in Aerospace Engineering, University of Illinois at Urbana-Champaign, 2019 BS in Aerospace Engineering, University of Illinois at Urbana-Champaign, 2013 Dr. Macdonald has received prestigious awards such as the NASA Early Career Faculty Fellow (2023), Air Force Office of Scientific Research Young Investigator Program (2021), and the President’s Postdoctoral Fellowship at the University of Minnesota (2019–2020). Her work bridges fundamental physics and engineering applications, with contributions to hypersonic vehicle design and aerothermal environment modeling. Her lab actively explores computational methods for hypersonic boundary layer transition, compressible LES modeling, and energy transfer processes in hypersonic flows. She collaborates on predictive tools for next-generation aerospace systems, emphasizing both academic and defense-related applications.

Henry Yuenمشاهده پروفایل

استادیار

• Quantum Computing
• Computational Complexity Theory
• Cryptography
• +۳ مورد دیگر

Henry Yuen is an Assistant Professor of Computer Science at Columbia Engineering, Columbia University. He is affiliated with the Cybersecurity and Foundations of Data Science centers. His research focuses on quantum computing, complexity theory, cryptography, and information theory. Yuen holds a BA in Mathematics from the University of Southern California (2010) and a PhD in Computer Science from MIT (2016). He has received prestigious awards including the NSF CAREER Award and a Sloan Fellowship. His work bridges quantum mechanics and computational complexity, with contributions to quantum non-locality, pseudorandomness, and cryptographic protocols. His recent research explores quantum advantage in algorithms, quantum circuit design, and quantum cryptographic primitives. Notable achievements include advancing the theoretical foundations of quantum pseudorandomness and demonstrating hardness results in quantum learning and state tomography. Key contributions span quantum interactive proofs, error correction, and quantum money schemes. His grants include funding for exploring theoretical foundations of quantum pseudorandom primitives. He collaborates on projects like unitary complexity analysis and superdense coding rigidity, contributing to both algorithmic and foundational aspects of quantum computing.

Tameem Albashمشاهده پروفایل

عضو هیئت علمی

• Quantum Information Science
• Quantum Computing
• Quantum Annealing
• +۷ مورد دیگر

Tameem Albash is a Research Associate Professor at the University of New Mexico , affiliated with the Department of Physics and Astronomy in the College of Arts and Sciences . His research focuses on quantum information science, quantum computing, and quantum annealing. He holds a PhD from the University of Southern California (2010). Education: PhD in Physics, University of Southern California, 2010 Research interests include quantum annealing optimization, quantum simulation, noise mitigation in quantum systems, and the interplay between quantum error correction and classical computational methods. His work explores topics like non-stoquastic Hamiltonians, many-body localization, and the application of machine learning to quantum systems. Recent studies investigate the efficiency of quantum annealing hardware for combinatorial problems, decoherence effects in quantum simulations, and the use of neural networks for state approximation. His articles highlight advancements in classical simulation techniques for quantum phenomena, such as analyzing macrostate vs. microstate dynamics in 1D Ising models. He also examines hybrid approaches combining quantum and classical methods to address limitations in current quantum hardware. Despite no listed awards, his contributions to quantum computing benchmarks and hardware validation are notable. Labs/Teams: Albash's research aligns with UNM's Quantum Information Science initiatives, though specific lab affiliations are not detailed in the provided text.