جست‌وجوی استاد و پژوهشگر

Daniel Grierمشاهده پروفایل

استادیار

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

Daniel Grier is an Assistant Professor jointly appointed in the Computer Science and Engineering and Mathematics departments at the University of California, San Diego (UCSD). His research focuses on quantum complexity theory , particularly exploring near-term quantum computing paradigms and proving quantum advantage over classical systems. He holds a Ph.D. from MIT and was previously a postdoctoral fellow at the University of Waterloo’s Institute for Quantum Computing. Education: Ph.D. in Computer Science, MIT B.S. in Computer Science and Mathematics, University of South Carolina Research Interests: Grier’s work bridges theoretical computer science and quantum computing, emphasizing algorithm design, complexity class separations, and foundational questions about quantum supremacy. He studies how low-depth quantum circuits, boson sampling, and other near-term technologies can achieve computational tasks classically deemed intractable. Recent Article Trends: His publications explore efficient quantum state learning (e.g., classical shadows), hardness results for quantum sampling problems (e.g., bipartite Gaussian boson sampling), and circuit lower bounds (e.g., depth-2 QAC circuits). These contributions highlight his focus on rigorously defining quantum computational advantages. Awards: None explicitly listed in the text. Advising & Grants: Advises at least one student, Jackson Morris. His research is supported by grants exploring quantum complexity and algorithm design. Teaches advanced courses on quantum complexity theory, computability, discrete mathematics, and quantum computing fundamentals. Labs/Teams: Maintains an active lab focused on quantum complexity theory, collaborating with colleagues on topics like interactive protocols and shallow quantum circuits.

• Quantum Computing
• Embedded Systems
• Electronic Engineering
• +۳ مورد دیگر

Andrea Marchesin serves as an Adjunct Professor at Politecnico di Torino, holding dual affiliations with the Department of Control and Computer Science (DAUIN) and the Department of Electronics and Telecommunications (DET) within the School of Engineering. His teaching responsibilities include Embedded Systems Integration for Electronic Engineering students and Quantum Hardware Design and Optimization modules within the Quantum Engineering program for the 2024/25 academic year. Dr. Marchesin's research centers on practical applications of quantum computing, with particular emphasis on quantum annealing approaches for real-world optimization problems. His scholarly work demonstrates a strategic focus on near-term quantum applications that can deliver tangible benefits despite current hardware limitations. He has developed quantum models specifically targeting urban traffic optimization and has contributed to computer architecture through tools like Octantis for exploring beyond von Neumann paradigms. His publication trend reveals a consistent trajectory toward engineering applications of quantum technologies, with recent work appearing in high-impact venues including IEEE Access and IEEE Transactions on Quantum Engineering. The research portfolio spans both theoretical algorithm development and practical implementation challenges, reflecting a bridge between quantum computing theory and engineering practice. As an academic advisor, Dr. Marchesin served as relatore (thesis advisor) for doctoral research on quantum algorithms for engineering applications. His teaching portfolio spans multiple academic years (2021/22-2024/25) and includes specialized workshops on SoC Verification Strategies alongside core courses in digital electronics and embedded systems.

Aida Todri-Sanialمشاهده پروفایل

استاد

• Energy-Efficient Circuits
• Quantum Computing
• Neuromorphic Computing
• +۴ مورد دیگر

Aida Todri-Sanial is a Full Professor in the Integrated Circuits group of the Electrical Engineering department at Eindhoven University of Technology (TU/e). She leads the NanoComputing Research Lab and is affiliated with the Center for Quantum Materials and Technology Eindhoven (CQMT-E), EAISI, and the Integrated Circuits group. Her research focuses on energy-efficient circuits, novel computing paradigms (e.g., 3D integration, neuromorphic computing, quantum computing), and nanotechnology-driven architectures. Education: PhD in Electrical and Computer Engineering, University of California Santa Barbara (2009) Bardeen Fellow at Fermi National Accelerator Laboratory (2009–2010) Scientist/Research Director at CNRS (2011–2021) Visiting Fellow at the University of Cambridge (2016–2017) Research Interests: Dr. Todri-Sanial’s work integrates physics and electronics to design unconventional computing systems. Key areas include: Physical design optimization for energy efficiency Oscillatory neural networks (ONNs) for edge AI Quantum computing hardware and error mitigation 3D integration and monolithic-3D architectures Nanomaterials (e.g., VO₂, MoS₂) for neuromorphic and sensing applications Awards & Grants: ERC Consolidator Grant THERMODON (2023) NWO AiNed Fellowship (2024) NWO Quantum Technology Grant (2024) CNRS Bronze Medal (2016), IBM Quantum Open Science Prize (2021), and IEEE Distinguished Lecturer (2022) Labs & Teams: Principal Investigator of the NanoComputing Research Lab Lead researcher in EAISI (Eindhoven Artificial Intelligence Systems Institute) Collaborator with global institutions (e.g., IBM, STMicroelectronics)

Steven Herbertمشاهده پروفایل

مدرس

• Quantum Computing
• Quantum Algorithms
• Quantum Sensing
• +۳ مورد دیگر

Steven Herbert is an Affiliated Lecturer in the Department of Computer Science and Technology at the University of Cambridge, where he teaches the Part II Quantum Computing course. In addition to his academic role, he serves as Head of Quantum Algorithms at Cambridge Quantum and is a By-Fellow at Churchill College. His research focuses on quantum computing, quantum algorithms, and their applications in areas such as sensing, communications, and optimization. A central theme of his work involves developing and analyzing quantum algorithms for Monte Carlo integration, entanglement distribution, and network coding, with a particular emphasis on practical implementations on near-term quantum hardware. He has contributed to theoretical advancements regarding quantum-classical algorithm comparisons, noise-aware techniques, and reinforcement learning applications in quantum compilation. Herbert’s research also explores interdisciplinary applications of quantum computing, including data-centric engineering and scientific computing. He actively investigates the intersection of quantum technologies with machine learning, particularly in generative adversarial networks (GANs), and has pioneered methods to optimize quantum circuit design and resource utilization. His work often bridges foundational theory with practical hardware constraints, addressing challenges such as qubit routing, error mitigation, and algorithmic efficiency in restricted quantum architectures. Through his affiliation with Cambridge Quantum, he collaborates on real-world quantum computing projects, emphasizing the translation of theoretical insights into tangible applications. His contributions span academic publications, industry partnerships, and educational initiatives aimed at advancing quantum literacy and innovation.

Daniel Grierمشاهده پروفایل

استادیار

• Quantum Complexity Theory
• Quantum Computing
• Quantum Algorithms
• +۳ مورد دیگر

Daniel Grier is an Assistant Professor at the University of California, San Diego in the Computer Science and Engineering and Mathematics departments. His research focuses on quantum complexity theory , particularly near-term quantum computing paradigms and proving quantum advantage over classical systems. PhD in Computer Science from MIT under Scott Aaronson Postdoc at the Institute for Quantum Computing (University of Waterloo) B.S. in Computer Science and Mathematics from University of South Carolina His work spans quantum algorithms , complexity theory , and quantum simulation , with notable contributions to BosonSampling , Clifford circuits , and classical shadow tomography . He has developed open-source tools like gridCHP++ , a C++ stabilizer simulator for planar quantum circuits. Publications highlight collaborations with researchers including Scott Aaronson , David Gosset , and Luke Schaeffer , covering topics such as quantum query complexity , quantum simulation efficiency , and quantum-classical separations .

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.

Lincoln D. Carrمشاهده پروفایل

استاد

• Quantum Information Science
• Complexity Sciences
• Condensed Matter Physics
• +۵ مورد دیگر

Lincoln D. Carr is a Professor in the Department of Physics at the Colorado School of Mines, where he investigates fundamental questions at the quantum-classical boundary, novel quantum computing paradigms beyond standard models, and interdisciplinary STEM education approaches. His work bridges theoretical physics with real-world problem-solving for global challenges like energy systems and political stability. His research spans critical domains: Quantum Information Science and Engineering Complexity Sciences and Emergent Phenomena Condensed Matter and Atomic Molecular Optical Physics Applied Mathematics and Computational Science Science Policy and Diplomacy Initiatives Humanities-STEM Integration Frameworks Analysis of his 2023-2025 publications reveals dominant themes in fractional quantum mechanics (Schrödinger/Ising models), Goldilocks quantum cellular automata, multiscale quantum media, and quantum optimization via oscillating fields. His numerical work achieves unprecedented precision in modeling anomalous transport, while his quantum education leadership drives national workforce development strategies. No specific scientific awards are documented in the source material. As a core faculty member, Carr mentors graduate students in quantum information and complexity science, though individual advisees aren't listed. His national workshop leadership indicates active grant involvement in quantum education infrastructure. He spearheads national quantum education policy through workshops establishing centers for quantum workforce development, demonstrating commitment to science diplomacy and interdisciplinary training frameworks that connect quantum physics with societal challenges.

Stacey Jefferyمشاهده پروفایل

استاد

• Quantum Algorithms
• Quantum Cryptography
• Quantum Computation Models
• +۳ مورد دیگر

Stacey Jeffery serves as Professor of Quantum Information at the University of Amsterdam's Korteweg-de Vries Institute for Mathematics since 2023 and Senior Researcher at Centrum Wiskunde & Informatica (CWI) and QuSoft since 2017. Her foundational work bridges theoretical computer science and quantum information processing, with emphasis on algorithmic frameworks and cryptographic security in quantum systems. Her educational trajectory includes a PhD in Computer Science from the University of Waterloo (2014), where she was affiliated with the Institute for Quantum Computing, following prior research at Caltech as an IQIM Postdoctoral Fellow. Jeffery's research centers on quantum algorithms and quantum cryptography, with pioneering contributions to quantum walk frameworks that enable quadratic speedups for graph problems. She has developed critical frameworks for secure delegation of quantum computation and advanced models for quantum error correction. Her work on multidimensional quantum walks and subroutine composition establishes new paradigms for quantum algorithm design, while investigations into space-time tradeoffs challenge fundamental limits of quantum computation. These theoretical advances directly enable practical quantum cryptographic protocols and error mitigation strategies. Analysis of her 15 most recent publications reveals a cohesive evolution toward unified frameworks for quantum algorithm composition, particularly through quantum walk methodologies. Her 2023-2025 works demonstrate increasing sophistication in error reduction techniques and space-efficient quantum computation, while maintaining strong connections to cryptographic applications like software leasing and multi-party computation. The consistent focus on foundational complexity questions—span programs, query complexity, and graph connectivity—underscores her commitment to advancing theoretical underpinnings of quantum computing. Her scientific recognition includes: NWO WISE Fellowship NWO Veni Grant ERC Starting Grant QDNL Award (for co-founding WIQD) CIFAR Fellow in Quantum Information Science Jeffery leads significant research initiatives including an ERC Starting Grant and NWO-funded projects. Her academic mentorship extends through QuSoft's collaborative environment, though specific advisee names aren't publicly cataloged. Professional service includes co-chairing QIP 2022, chairing TQC's steering committee (2021), and directing the Lorentz Center Informatics Advisory board. She actively shapes community standards through roles in QCrypt and ACM SIGACT. As a core QuSoft researcher and co-founder of WIQD (Women in Quantum Development), Jeffery drives both technical innovation and diversity initiatives. Her laboratory focuses on quantum algorithm frameworks with real-world cryptographic applications, while WIQD—awarded the inaugural QDNL Award—creates vital networking and development opportunities for women across quantum technology sectors. Current efforts target quantum subroutine composition and space-efficient error correction for near-term quantum devices.

John Preskillمشاهده پروفایل

استاد

• Quantum Computing
• Quantum Information Theory
• Theoretical Physics
• +۳ مورد دیگر

John Preskill is the Richard P. Feynman Professor of Theoretical Physics at the California Institute of Technology (Caltech). He is a leading figure in quantum information science, focusing on quantum computing, quantum error correction, and the theoretical foundations of quantum mechanics. His work bridges fundamental research and practical quantum technologies, including contributions to the NISQ (Noisy Intermediate-Scale Quantum) era framework and quantum machine learning. In 2024, he was awarded the prestigious John Stewart Bell Prize for his advancements in quantum information processing and machine learning applications in quantum experiments. Preskill's research emphasizes leveraging quantum principles for novel computational paradigms, such as quantum advantage in learning from experimental data and scalable quantum error correction. His articles explore topics like quantum field theory simulations, entanglement dynamics, and fault-tolerant quantum architectures. He collaborates across disciplines, contributing to both theoretical breakthroughs and experimental implementations of quantum technologies. Notably, his 2018 paper Quantum Computing in the NISQ era and beyond outlines near-term quantum computing challenges and opportunities. His work on Bell Prize-winning research highlights foundational links between quantum learning and efficient information processing. Preskill is affiliated with Caltech's Institute for Quantum Information and Matter, driving interdisciplinary quantum science initiatives.

Samson Wangمشاهده پروفایل

پژوهشگر ارشد

• Quantum Computing
• Quantum Algorithms
• Quantum Machine Learning
• +۱ مورد دیگر

Samson Wang is an IQIM Postdoctoral Scholar Research Associate in Theoretical Physics at Caltech, focusing on quantum computational complexity and algorithm design. His research bridges quantum information theory and practical algorithm development for near-term quantum devices. Key research themes include: 1) Diagnosing and mitigating trainability challenges in variational quantum algorithms; 2) Developing resource-efficient quantum linear algebra methods; 3) Characterizing quantum kernel methods in machine learning; and 4) Designing error-mitigated algorithms for imperfect hardware. Recent publications establish frameworks for partial error correction (2023) and analyze barren plateau phenomena (2021-2025). Office location: Annenberg IST Center; contact: 626-517-6999.