جست‌وجوی استاد و پژوهشگر

• Condensed Matter Physics
• Quantum Information Science
• Quantum Computing
• +۴ مورد دیگر

Bryan K. Clark is an Associate Professor in the Department of Physics at the University of Illinois, with his office located in the Engineering Sciences Building. He leads the Clark Research Group, which works at the intersection of quantum information, condensed matter physics, machine learning, and computing. Clark's research spans four main areas: Quantum Computing , where his group develops quantum algorithms and collaborates with experimentalists on superconducting qubit systems; Quantum Many-Body Physics , where he applies computational methods to understand emergent behavior in strongly correlated systems; Algorithms for the Quantum Many-Body Problem , where his group has pioneered techniques like Neural Network Backflow (NNBF) that represent state-of-the-art accuracy for simulating fermions and frustrated magnetism; and Machine Learning for Experiment , where his group develops techniques to analyze experimental data like scanning transmission electron microscopy images. His publication record demonstrates consistent innovation in bridging theoretical quantum information science with practical applications. Recent work focuses on neural network approaches to quantum simulation, quantum error correction/mitigation, and novel qubit architectures like the Floquet Fluxonium Molecule. His research shows a clear trajectory from fundamental questions about the quantum-classical boundary to practical implementations in quantum hardware. Clark actively mentors graduate students, with recent thesis defenses by Faisal Alam, Matt Thibodeau, Chad Germany, James Allen, and Abid. His group has secured significant funding from the NSF and IBM's IIDAI institute to support research in quantum computing and machine learning applications for nano-photonics manufacturing and error mitigation. The Clark Research Group maintains strong connections with experimental teams, particularly in superconducting qubit development and materials characterization. They've developed computational tools like QOSY (Quantum Operators from SYmmetry) that are publicly available on GitHub and have gained recognition in the quantum information community.

Christopher Ferrieمشاهده پروفایل

دانشیار

• Quantum Estimation and Control
• Quantum Machine Learning
• Quantum Information Science
• +۵ مورد دیگر

Christopher Ferrie is an Associate Professor at the University of Technology Sydney (UTS), where he is affiliated with the Faculty of Engineering and Information Technology and the Centre for Quantum Software and Information (QSI). His academic career spans quantum information science, machine learning, and scientific education, with a strong emphasis on both theoretical research and public engagement through science communication. Full-time faculty member at UTS Active researcher in quantum information science Director of the Centre for Quantum Software and Information Author of numerous scientific publications and popular science books Dr. Ferrie earned his PhD in Applied Mathematics from the Institute for Quantum Computing and University of Waterloo in Canada in 2012. His doctoral work focused on quantum information and laid the foundation for his subsequent research career in quantum computing and related fields. Dr. Ferrie's research interests span several interconnected domains within quantum information science. His primary focus is on quantum estimation and control, with particular emphasis on applying machine learning techniques to solve statistical problems in quantum information science. He investigates how quantum systems can be characterized, controlled, and optimized for practical applications. His work bridges theoretical quantum physics with practical implementations, exploring how quantum phenomena can be harnessed for computational advantage. Recent research directions include quantum machine learning, quantum neural networks, and quantum optimization algorithms, with applications ranging from quantum state tomography to solving combinatorial optimization problems. Analysis of Dr. Ferrie's recent publications reveals a strong focus on practical quantum computing challenges. His work consistently addresses the intersection of quantum information theory and machine learning, with particular emphasis on making quantum algorithms more efficient, interpretable, and robust against noise. A significant portion of his recent research explores variational quantum algorithms and their optimization, reflecting the current priorities in near-term quantum computing. His publications also demonstrate growing interest in quantum machine learning applications and the development of techniques for quantum error mitigation and characterization. Dr. Ferrie has secured multiple research grants supporting his work in quantum computing and related fields. His funded projects span quantum control, quantum probability, quantum machine learning, and statistical decision theory, reflecting the breadth of his research program. While specific major awards aren't detailed in the available information, his sustained funding and publication record indicate significant recognition within the quantum information science community. Dr. Ferrie is actively involved in research supervision and teaching, with current funding supporting multiple PhD students and postdoctoral researchers. His teaching responsibilities include courses on quantum computing, where he introduces students to the fundamentals of quantum information processing. His research group at the Centre for Quantum Software and Information focuses on developing novel quantum algorithms and exploring the practical implementation challenges of quantum computing. The Centre for Quantum Software and Information at UTS serves as the primary research environment for Dr. Ferrie's work. This center brings together researchers working on various aspects of quantum computing, from hardware development to algorithm design and applications. Dr. Ferrie's team within the center focuses specifically on quantum software development, quantum algorithm design, and the application of machine learning techniques to quantum information problems. The collaborative environment enables interdisciplinary research that bridges theoretical quantum physics with practical computing applications.

Luca Carloniمشاهده پروفایل

استاد

• Computer Science
• Embedded Systems
• Hardware Design
• +۶ مورد دیگر

Luca Carloni is a Professor of Computer Science and Department Chair at Columbia University's Columbia Engineering. He leads the System-Level Design Group, focusing on heterogeneous system-on-chip (SoC) architectures, networks-on-chip (NoC), and embedded systems. Carloni holds a Laurea Summa Cum Laude in Electronics Engineering from the University of Bologna and a PhD in Electrical Engineering and Computer Sciences from UC Berkeley. His work emphasizes specialized hardware design, energy-efficient computing, and FPGA-based prototyping. Research interests include system-level design methodologies for SoCs, embedded accelerators, and quantum computing hardware. He has pioneered frameworks like Embedded Scalable Platforms (ESP) and tools like MosaicSim for rapid SoC prototyping. Carloni has received numerous awards, including the NSF CAREER Award (2006), IEEE Fellow (2017), and multiple best paper awards at DATE and CloudCom conferences. He has served on editorial boards of IEEE Transactions on CAD and ACM Transactions on Embedded Computing , and chaired key conferences like EMSOFT and ESWeek. His research addresses challenges in heterogeneous architectures, power management, and the intersection of machine learning with embedded systems. Current projects explore quantum control systems, brain-computer interfaces, and energy-efficient datacenter computing.

John M. Nicholمشاهده پروفایل

استادیار

• Quantum Information Processing
• Condensed Matter Physics
• Quantum Computing
• +۳ مورد دیگر

John M. Nichol is an Assistant Professor in the Department of Physics and Astronomy at the University of Rochester, where he has conducted experimental quantum research since 2016 following postdoctoral work at Harvard University. His work bridges fundamental quantum mechanics and applied quantum computing development. Education: B.A. in Physics, St. Olaf College (2006) Ph.D. in Physics, University of Illinois at Urbana-Champaign (2013) Postdoctoral Associate, Harvard University Nichol's research centers on experimental quantum information processing using semiconductor nanostructures, with primary focus on electron spin qubits in quantum dots. His lab investigates quantum coherence mechanisms, develops noise-resilient control protocols for spin qubits, and explores quantum information transfer across spin chains. Key initiatives include engineering novel materials for extended qubit lifetimes, implementing dynamical decoupling techniques to combat decoherence, and studying many-body quantum phenomena in engineered spin systems. This work directly addresses scalability challenges in solid-state quantum computing. Analysis of Nichol's 2021-2025 publications reveals dominant themes in semiconductor spin qubit optimization, with 80% of papers addressing coherence preservation through charge noise mitigation and advanced control methods. His research increasingly integrates hybrid quantum systems, combining spin qubits with acoustic wave devices and superconducting resonators. Recurring subfields include Si/SiGe heterostructure engineering, quantum fluctuator characterization, and quantum simulation using spin chains - reflecting a strategic focus on overcoming material limitations in quantum hardware. Scientific Awards: National Science Foundation CAREER award Google Research Scholar Award Leonard Mandel Faculty Fellow Award Nichol's research program is supported by competitive grants including the NSF CAREER award (funding coherence enhancement research) and Google Research Scholar Award (supporting quantum control innovations). His laboratory trains graduate students in nanofabrication, cryogenic measurement techniques, and quantum device characterization, with emphasis on translating fundamental discoveries into practical quantum computing components. Current projects focus on long-distance quantum state transfer and error-corrected multi-qubit operations. The Nichol Lab operates specialized facilities for quantum dot device fabrication and millikelvin transport measurements at the University of Rochester. His team collaborates with materials scientists on heterostructure growth and theorists on quantum simulation protocols, maintaining strong ties with semiconductor industry partners for advanced material development. Recent expansions include acoustic wave integration platforms for hybrid quantum systems.

Stefan Krastanovمشاهده پروفایل

استادیار

• Quantum Hardware Design and Control
• Resilient Noisy Quantum Circuits
• Entanglement and Quantum Networking
• +۳ مورد دیگر

Stefan Krastanov is an Assistant Professor at the University of Massachusetts Amherst, focusing on quantum hardware design, control, and optimization across multiple layers of quantum computing and networking technologies. His work bridges physical hardware descriptions with logical circuit compilation, emphasizing resilience in noisy quantum systems. Research Interests include Quantum Hardware Design, Entanglement-Based Networking, Quantum Error Correction, and Modeling Software for Quantum Systems. His primary lab is the Quantum Information Lab , with affiliations to the Advanced Classical and Quantum Information Research Lab. Recent work trends highlight advancements in quantum repeater networks, error-corrected compilation, and photonic neural networks. His publications span topics like non-Markovian dynamics simulation, NP-hard optimization in quantum dot arrays, and scalable spin quantum memory control. Labs and Teams: Quantum Information Lab (leading experimental/theoretical work) and collaborations through the Advanced Classical and Quantum Information Research Lab.

• Quantum Physics
• Quantum Information Science
• Quantum Computing
• +۲ مورد دیگر

Marco Canteri is a Researcher in the Department of Experimental Physics at the University of Innsbruck, Austria. He holds an MSc degree and contributes to quantum information science with a focus on trapped-ion systems for quantum computing and networking. His educational background includes a Master of Science degree. The specific institution is not provided in available sources. Canteri's research spans quantum networking, quantum communication, and quantum sensing using trapped ions. Key areas include ion-photon interfaces, quantum memory, entanglement distribution, and scalable quantum hardware. His work addresses challenges in noise resilience and long-distance quantum links through experimental implementations of multiqubit systems and telecom-wavelength interfaces. Analysis of his 12 recent publications (2020-2025) reveals consistent advancement in trapped-ion quantum technologies. Notable achievements include entanglement distribution over 101 kilometers, multimode quantum networking, and development of ten-qubit quantum registers. The research demonstrates strong interdisciplinary integration of atomic physics, quantum optics, and quantum information theory for practical quantum network applications. No scientific awards are listed in the available information. Information regarding students advised or research grants obtained by Marco Canteri is not provided in current sources. He operates within the quantum information research group of the Department of Experimental Physics, utilizing advanced laboratories equipped for trapped-ion quantum computing experiments including optical cavities, precision laser systems, and single-photon detection infrastructure under department head Hanns-Christoph Nägerl.

Marko Cetinaمشاهده پروفایل

استادیار

• Quantum Computing
• Quantum Optics
• Atomic Physics
• +۳ مورد دیگر

Marko Cetina is an Assistant Professor of Physics and the Department of Electrical and Computer Engineering at Duke University, affiliated with the Duke Quantum Center. He holds a B.S. from the California Institute of Technology (2004) and a Ph.D. from the Massachusetts Institute of Technology (2011). His research focuses on quantum computing, quantum optics, and atomic physics, with particular emphasis on trapped-ion systems, quantum error correction, and quantum simulation. He teaches courses including Atomic Physics and Quantum Optics, Advanced Topics in Physics, and introductory mechanics. His work explores foundational aspects of quantum mechanics and applied technologies for scalable quantum computers. Notable contributions include demonstrating multi-body interactions in trapped ions and advancing measurement-induced quantum phases. His team actively develops fault-tolerant qubit control and novel quantum architectures using cavity-mediated systems. Publications highlight advancements in quantum error correction protocols, lattice gauge theories, and quantum verification protocols. While no explicit awards are listed, his involvement in high-impact studies like the Duke Quantum Center underscores his contributions to the field. Current projects include optimizing stabilizer codes for logical qubit memory and simulating NMR experiments via digital quantum methods. His lab collaborates across disciplines to bridge theoretical quantum mechanics with experimental implementations in trapped-ion platforms.

Joseph Friedmanمشاهده پروفایل

دانشیار

• Artificial Intelligence Hardware
• Beyond-CMOS Computing
• Neuromorphic Computing
• +۶ مورد دیگر

Joseph S. Friedman is an Associate Professor of Electrical & Computer Engineering at the University of Texas at Dallas, leading the NeuroSpinCompute Laboratory within the Erik Jonsson School of Engineering and Computer Science. His research focuses on unconventional computing paradigms leveraging nanotechnology, including neuromorphic systems, spintronics, and memristive devices. He specializes in nanomagnet-based logic architectures, neuromorphic computing with domain walls and skyrmions, and hardware security for emerging technologies. His research explores energy-efficient computing through novel paradigms such as reversible skyrmion logic, neuromorphic networks using magnetic tunnel junctions, and stochastic Bayesian inference circuits. He has pioneered spintronic neurons demonstrating 94% accuracy in handwritten digit recognition and developed secure logic locking mechanisms using nanomagnet logic. His work integrates experimental fabrication with SPICE modeling, emphasizing scalable beyond-CMOS systems. Recent advancements include toggle SOT-MRAM architectures, quantum circuit design for neutral atom systems, and neuromorphic networks leveraging superconducting flux quanta. He advises over 20 graduate and undergraduate students, fostering innovation in AI hardware and unconventional computing. Notable projects include the NeuroSpinCompute Lab's domain wall neuromorphic networks, secure logic locking schemes, and collaborations with institutions like Sandia National Labs on neuromorphic reservoir computing. Current research trends emphasize low-energy spintronic architectures, hybrid quantum-classical systems, and neuromorphic applications in edge computing. His research is supported by NSF grants CCF-1910800 and CCF-2146439, focusing on neuromorphic and spintronic systems. He regularly contributes to conferences like IEEE Rebooting Computing and SPIE Spintronics, showcasing breakthroughs in nanomagnetic logic and neuromorphic inference.

Markus Müllerمشاهده پروفایل

استاد

• Quantum Information Processing
• Quantum Simulation
• Quantum Error Correction
• +۵ مورد دیگر

Markus Müller is a Professor in Theoretical Quantum Technology at RWTH Aachen University and the Forschungszentrum Jülich's Peter Grünberg Institute. He leads a research group focused on quantum information processing, quantum simulation, and topological quantum computing/ error correction using atomic, molecular, and optical systems. His work bridges theory and practice, with collaborations on trapped-ion and neutral-atom quantum processors. Education: PhD in Quantum Simulation (2011, University of Innsbruck). Postdoctoral positions at Complutense University Madrid. Faculty roles at Swansea University (2015–2019) before moving to Aachen. Research Interests: Quantum error correction, fault-tolerant protocols, topological phases, quantum neural networks, and scalable quantum hardware. His group explores applications in trapped ions, Rydberg atoms, and superconducting qubits, with projects funded by ERC and EU Quantum Flagship grants. Grants/Projects: ERC Starting Grant (Quantum Neural Networks), EU AQTION (Trapped Ion Quantum Computing), VEQTOR (Fault-Tolerance Validation), and Munich Quantum Valley (Neutral-Atom Processors). Key Publications: Includes experimental demonstrations of fault-tolerant gates, surface-code error correction, and quantum neural networks. Over 120 peer-reviewed articles in Nature Physics , Physical Review X , and Quantum .

Felix Motzoiمشاهده پروفایل

دانشیار

• Quantum Technologies
• Optimal Control Theory
• Machine Learning
• +۶ مورد دیگر

Prof. Felix Motzoi is an Associate Professor at the University of Cologne and Division Leader & Head of the 'Automatic Optimization, Control and Design' group at the Peter Grünberg Institute (PGI-8) in Jülich. His research focuses on advancing quantum technologies, including superconducting and semiconducting architectures, trapped cold atoms/ions, Rydberg qubits, and long-range entanglement. He leads theoretical efforts in quantum control theory, machine learning applications, hardware co-design, and error mitigation strategies. Key research areas include developing optimal control methodologies (e.g., DRAG, STA), numerical optimization, and dynamics modeling for quantum systems. His work bridges theoretical frameworks with experimental implementations, emphasizing practical solutions for scalable quantum computing. Recent publications highlight innovations in quantum gate design, error suppression via pulse shaping, and hybrid optimization techniques combining machine learning with physics-driven approaches. His team collaborates across disciplines to address challenges in qubit coherence, entanglement stabilization, and robust quantum processing.

Yongshan Dingمشاهده پروفایل

استادیار

• Quantum Computing
• Computer Architecture
• Quantum Algorithms
• +۴ مورد دیگر

Yongshan Ding is an Assistant Professor of Computer Science and Applied Physics at Yale University. He leads the Quantum Systems Lab (QSL) and directs Yale's Quantum Science and Engineering Certificate program. Affiliated with the Yale Quantum Institute (YQI) and Computer Systems Lab (CSL), his research focuses on quantum computing systems spanning algorithms, architecture, and hardware/software co-design. Dr. Ding earned his Ph.D. from the University of Chicago and a B.Sc. from Carnegie Mellon University. He has received prestigious awards including the Siebel Scholarship (2020) and William Rainey Harper Dissertation Fellowship (2020). Research Interests: Quantum computing architectures, noise-resilient quantum algorithms, error correction methods, quantum compilation, hardware-software co-design, and NISQ system optimization. Editorial Roles: Editor at Quantum journal and Associate Editor at ACM Transactions on Quantum Computing . Labs: Founder of Yale's Quantum Systems Lab (QSL) and contributor to the Computer Systems Lab (CSL). Awards: Siebel Scholarship (2020) William Rainey Harper Dissertation Fellowship (2020) QCE Best Paper Award (2024) IEEE Micro Top Picks Honorable Mention (2023, 2020) IBM Q Best Paper Award, First Prize (2020) Mathematics Competition Runner Up (2016)

Giulia Semeghiniمشاهده پروفایل

استادیار

• Quantum Computing
• Quantum Information Science
• Condensed Matter Physics
• +۳ مورد دیگر

Giulia Semeghini is an Assistant Professor of Applied Physics at Harvard University's School of Engineering and Applied Sciences (SEAS) . Her research focuses on experimental investigations of highly-entangled phases of matter and quantum information processing using programmable atom arrays. The Semeghini Lab, part of the Harvard Quantum Initiative (HQI) and the Center for Ultracold Atoms (CUA), explores intersections between condensed matter physics, high-energy physics, and quantum chemistry. Key achievements include assembling an ultra-high vacuum chamber for atom arrays in 2024 and relocating to the Goel building (HQI's new home) in April 2024. The lab actively recruits students and researchers for open positions at all levels. Research themes span quantum simulation, topological qubits, entanglement engineering, and scalable quantum architectures. Publications emphasize quantum gate implementations, hybrid atom systems, and variational Monte Carlo enhancements. No scientific awards are explicitly listed, but contributions to quantum hardware and algorithms are notable. The lab collaborates widely, aiming to bridge theory and experiment in quantum technologies.

YEO Yeمشاهده پروفایل

مدرس ارشد

• Quantum Information Science
• Quantum Entanglement
• Theoretical Physics

YEO Ye is a Senior Lecturer at the National University of Singapore (NUS) and serves as Assistant Dean (Student Life and Alumni Relations). She holds a PhD from the University of Cambridge, UK (2004). Her educational background: PhD, University of Cambridge, UK (2004) Dr. YEO's research focuses on quantum entanglement in multiparticle systems, investigating fundamental aspects of multipartite entanglement and its applications in quantum information processing. Her work addresses the incomplete theoretical understanding of entanglement as a critical resource for quantum technologies. Her publications (2005-2006) demonstrate concentrated research on multipartite entanglement across diverse contexts including decoherence effects, quantum teleportation protocols, dense coding implementations, and thermal entanglement in spin chain systems. These studies collectively advance theoretical frameworks for maintaining and utilizing entanglement in quantum communication and computation.

Kenneth Zickمشاهده پروفایل

استاد پژوهشی

• Unconventional computing
• Bio-inspired compute systems
• Ising machines
• +۷ مورد دیگر

Dr. Kenneth Zick is a Research Professor at the University of Southern California's Information Sciences Institute (USC ISI), where he serves as Research Director of Transformational Computing. His work focuses on game-changing computer architectures, hardware, and systems for solving critical government problems, with expertise in unconventional computing, quantum computing, and bio-inspired systems. Ph.D. in Computer Science & Engineering, University of Michigan-Ann Arbor M.S. in Electrical Engineering, University of Texas at Dallas Bachelor's in Electrical Engineering, University of Michigan-Ann Arbor Dr. Zick's research interests span unconventional computing , bio-inspired systems , Ising machines , quantum annealing , FPGA-based solutions , and neuromorphic computing . His group develops hardware-centric algorithm discovery and Cosm, a heuristic algorithm for sparse Ising optimization. Current projects include superconducting digital architectures, analog-digital hybrid computing, and human-AI co-design for breakthrough hardware. His team leverages advanced facilities such as USC ISI's MOSIS 2.0 and the California DREAMS hub in the DoD Microelectronics Commons, with expertise in high-speed I/O, FPGA prototyping, and radiation-hardened systems. He has received a NASA Fellowship for his Ph.D. work and mentored students like Aditi, who won the USC ECE Outstanding Academic Achievement Award.

• Quantum Information Theory
• Quantum Many-Body Theory
• Quantum Optics
• +۷ مورد دیگر

Prof. Dr. Jens Eisert is a Professor at the Free University of Berlin, where he leads the Quantum Many-Body Theory, Quantum Information Theory, and Quantum Optics research group (Eisert AG) within the Institute of Theoretical Physics at the Dahlem Center for Complex Quantum Systems. His office is located at Arnimallee 14, Room 1.3.06 in Berlin-Dahlem. His research focuses on the intersection of quantum information theory and condensed matter physics, specifically exploring what information processing tasks are possible using individual quantum systems as information carriers. His group develops mathematical-theoretical foundations of quantum information, particularly in entanglement theory and tomography, while also investigating quantum optical implementations using light modes or cold atoms in optical lattices. A major emphasis of their work is on quantum many-body systems, including static properties, efficient numerical simulation methods like tensor networks, and non-equilibrium quantum dynamics. Recent publications highlight significant contributions in thermalization of quantum systems (Communications Physics 2025), quantum thermodynamics (Nature Physics 2025), and quantum error correction (PRX Quantum 2025). The group's work is characterized by combining the rigor of mathematical physics with physically motivated applicability, frequently leading to direct collaborations with experimental groups. Quantum Information Theory Quantum Many-Body Theory Quantum Optics Entanglement Theory Tensor Networks Quantum Error Correction Prof. Eisert maintains active supervision of numerous PhD students and postdoctoral researchers, with research positions regularly available in areas including quantum error correction, quantum information theory, tensor networks, and quantum simulation. His group has published extensively in top journals including Nature Physics, PRX Quantum, and Physical Review series.