جست‌وجوی استاد و پژوهشگر

Ahmet Avsarمشاهده پروفایل

استادیار

• Spintronics
• 2D Materials
• Quantum Devices
• +۳ مورد دیگر

Dr. Ahmet Avsar is an Assistant Professor and NRF Fellow in the Department of Material Science and Engineering at the National University of Singapore (NUS), appointed since September 2022. Prior to this, he served as an Assistant Professor of Physics at Newcastle University (UK) and held an EPFL Fellowship (co-funded by the European Marie Curie COFUND) at the Swiss Federal Institute of Technology Lausanne (EPFL, Switzerland) from 2016 to 2020. He completed his PhD in Physics at NUS. His research focuses on exploiting quantum degrees of freedom (spin, pseudospin, valley) in atomically thin materials for energy-efficient information technologies. This includes fabricating mesoscopic devices with 2D heterostructures and studying their electronic, magnetic, and optical properties at low temperatures. His work emphasizes sustainable computing through spin, magnon, and superconducting quasiparticle-based information processing. Key research areas include spintronics in graphene and 2D materials, van der Waals magnetism, excitonic devices, and low-temperature characterization. His recent projects explore anisotropic spin transport in black phosphorus, valleytronics, and logic-in-memory systems using atomically thin semiconductors. Dr. Avsar has been recognized as an NRF Fellow and EPFL Fellow. His research is supported by the National Research Foundation (NRF) of Singapore. He has authored or co-authored numerous high-impact publications in journals like Nature Materials , Nature Nanotechnology , and Review of Modern Physics . His academic trajectory includes postdoctoral research at EPFL and prior roles in the UK, reflecting a trajectory of excellence in quantum materials and nanotechnology research.

Brenda Rubensteinمشاهده پروفایل

دانشیار

• Electronic Structure Methods
• Quantum Chemistry
• Molecular Computing
• +۲ مورد دیگر

Brenda Rubenstein is an Associate Professor of Chemistry and Physics at Brown University and Director of the Data Science Institute. Her research bridges quantum chemistry and materials science, developing stochastic electronic structure methods for accurate large-scale simulations. She also explores molecular computing and computational biophysics. Her group emphasizes diversity, collaboration, and work-life balance. Recent work includes quantum Monte Carlo techniques for materials discovery, machine learning approaches for protein dynamics, and quantum computing applications. She received a named professorship in 2025 and leads the Levermore Global Scholars program. Her publications focus on computational methods across chemistry, physics, and materials science.

M. Hadi Aminiمشاهده پروفایل

استادیار

• Distributed Machine Learning
• Federated Learning
• Interdependent Networks
• +۷ مورد دیگر

M. Hadi Amini is an Assistant Professor at Florida International University's Knight Foundation School of Computing and Information Sciences. He founded and directs the Sustainability, Optimization, and Learning for InterDependent networks (SOLID) laboratory, focusing on cyber-physical-social systems and distributed AI applications. Ph.D., Electrical and Computer Engineering (2019), Carnegie Mellon University M.Sc., Electrical and Computer Engineering (2015), Carnegie Mellon University M.Sc. (2013), Tarbiat Modares University B.Sc. (2011), Sharif University of Technology His research spans federated learning, interdependent network optimization, and AI applications in smart cities , energy systems , and healthcare . Recent work emphasizes privacy-preserving techniques, quantum encryption, and blockchain integration for secure distributed learning. The 15 most recent publications highlight trends in large language models , edge computing , medical imaging security , and infrastructure resilience , with interdisciplinary emphasis across computer science, systems engineering, and urban planning. Best Paper Award, IEEE Conference on Computational Science & Computational Intelligence (2019) Best Journal Paper Award, Springer Nature Operations Research Forum (2021) Excellence in Teaching Award, FIU (2020) Multiple Best Reviewer Awards, IEEE Transactions NSF Travel Awards (2019) As Associate Editor for Frontiers in Communications and Networks and book series editor for Sustainable Interdependent Networks , he actively shapes research discourse. His lab has secured $3.6M in federal/state funding for AI-driven infrastructure projects.

Horacio Castilloمشاهده پروفایل

دانشیار

• Condensed Matter Physics
• Statistical Mechanics
• Glass Transition
• +۳ مورد دیگر

Horacio Castillo is an Associate Professor in the Department of Physics and Astronomy at Ohio University, affiliated with the Nanoscale Quantum Phenomena Institute (NQPI). His research focuses on condensed matter theory, particularly glassy dynamics, dynamical heterogeneities, and non-equilibrium systems. He explores topics such as fluctuating relaxation times, aging dynamics, and the interplay between structure and dynamics in supercooled liquids and amorphous solids. Key research areas include the study of glass transition phenomena using molecular simulations and theoretical models. His work addresses questions about spatial and temporal correlations in glass-forming systems, dynamic susceptibility, and the application of spin-glass concepts to biological reprogramming processes. Castillo’s contributions span experimental collaborations and computational studies, with a focus on advancing understanding of complex materials and their underlying physics. Publications highlight advancements in characterizing rotational/translational dynamics in supercooled liquids, modeling dynamic heterogeneity, and analyzing aging regimes in silica glasses. His research bridges traditional condensed matter physics with interdisciplinary topics such as biophysics, leveraging tools from statistical mechanics and nonlinear dynamics. Castillo has contributed to the Ohio University community through involvement in academic events like the NQPI-CMSS Joint Poster Session (2015) and mentoring student research projects, as evidenced by his presence in student research expos. His grants and collaborations reflect a commitment to advancing fundamental knowledge in nanoscale and quantum phenomena.

Guofu Niuمشاهده پروفایل

استاد

• Semiconductor Devices
• Compact Modeling
• RF Circuit Design
• +۳ مورد دیگر

Guofu Niu is a Professor in the Department of Electrical and Computer Engineering at Auburn University, holding the Ed and Peggy Reynolds Family endowed chair. His research specializes in semiconductor device physics, compact modeling of SiGe heterojunction bipolar transistors (HBTs), FinFETs, and cryogenic electronics for RF and power applications. Key research areas include RF linearity characterization, avalanche effects, thermal noise, and low-temperature device performance. He has developed advanced models (e.g., Mextram) for circuit simulation tools, enhancing the accuracy of semiconductor design workflows. Publications focus on nano-scale device reliability, tunneling currents, and optimization of RF amplifiers, with applications in 5G technology and extreme-environment electronics. Collaborative projects span industry and academia to advance semiconductor modeling frameworks.

Nicola Dragoniمشاهده پروفایل

استاد

• Cybersecurity
• Internet of Things (IoT)
• Machine Learning
• +۷ مورد دیگر

Nicola Dragoni is a Professor in Cybersecurity Engineering at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU). As Deputy Director and Head of Section, he leads research initiatives focused on securing emerging technologies. Key Research Areas : Internet of Things (IoT) security, machine learning for intrusion detection, cyber-deception techniques, fog computing, malware analysis, blockchain applications, and wireless sensor network security. Supervision : Actively supervising multiple PhD students in projects related to cyber-deception, moving target defense, and bio-inspired security mechanisms. Recent Publications : Contributions to IoT honeypots, drone identification via RF signals, passkey adoption challenges, and cyber range taxonomies.

Alexander D Maloneyمشاهده پروفایل

استاد

• Theoretical Physics
• Quantum Information Theory
• Black Holes
• +۴ مورد دیگر

Alexander D Maloney serves as the Kathy and Stan Walters Endowed Professor of Quantum Science and Director of the Institute for Quantum and Information Science at Syracuse University's College of Arts and Sciences, Department of Physics. His leadership bridges theoretical physics and quantum information science through institutional and research initiatives. His academic foundation includes a Ph.D. in Physics from Harvard University (2003) with dissertation "Time-Dependent Backgrounds of String Theory," complemented by dual B.Sc. and M.Sc. degrees in Physics and Mathematics from Stanford University (1998). Maloney's research centers on quantum gravity and information theory, exploring black hole physics through string theory frameworks. His work connects quantum field theory, cosmology, and information paradox resolution, with particular focus on wormhole geometries, resurgence phenomena, and holographic dualities. This interdisciplinary approach examines how quantum information principles shape spacetime structure. Recent publications reveal evolving emphasis on Narain ensemble statistics, modular invariance applications, and quantum cosmology in reduced dimensions. His 2020-2025 output demonstrates methodological progression from semiclassical gravity to non-perturbative quantum gravity techniques, increasingly integrating machine learning concepts with theoretical frameworks. His scientific recognition includes: James McGill Professor at McGill University (2023) Sir William Macdonald Chair in Physics at McGill University (2020) Maloney secures major research funding including NSERC Discovery Grants (2015-2020, 2020-2025) and Simons Foundation's "It from Qubit" collaboration (2015-2022). He actively shapes academic discourse through search committee leadership, journal reviewing (Journal of High Energy Physics since 2007), and international conference organization at Aspen Center for Physics and Institute for Advanced Study. As Director of Syracuse's Institute for Quantum and Information Science, he cultivates collaborative research environments exploring quantum gravity applications to quantum computing and cosmological modeling.

Bhavin J. Shastriمشاهده پروفایل

استادیار

• Silicon Photonics
• Nanophotonics
• Photonic Integrated Circuits
• +۵ مورد دیگر

Bhavin J. Shastri is an Assistant Professor in the Department of Physics, Engineering Physics and Astronomy at Queen's University in Canada. His research explores the physics of light for computing , pushing frontiers in information and signal processing through photonic computing and quantum/neuromorphic photonics . He is affiliated with the Centre for Nanophotonics and NUCLEUS , a pan-Canadian photonic computing program funded by NSERC CREATE, bridging artificial intelligence and quantum information . Canada Research Chair & Principal Investigator Faculty Affiliate at Vector Institute (2020-) Editorial Board Member of JPhys Photonics (2019-) Member of IEEE Photonics Society Technical Affairs Council (2019-) Visiting Researcher Scholar at Princeton University (2018-) Shastri Lab members have access to world-class shared facilities, including the Centre for Nanophotonics (CFI-Innovation Fund), Nanofabrication Kingston , the Centre for Advanced Computing , and the Digital Research Alliance of Canada . The lab takes an interdisciplinary approach combining nanophotonics with complex systems on emerging substrates. His research focuses on silicon photonics , nanophonic processors , and photonic integrated circuits with applications to deep learning , nonlinear programming , and quantum information science . His articles show consistent exploration of quantum photonic neural networks , photonic memory systems , and optical signal processing for machine learning and quantum technologies . 2020 IUPAP Young Scientist Prize in Optics 2014 Banting Postdoctoral Fellowship 2012 D. W. Ambridge Prize 2011 IEEE Photonics Society Graduate Student Fellowship 2011 NSERC Postdoctoral Fellowship Multiple Best Student Paper Awards Shastri's lab supervises Ph.D. candidates and postdoctoral fellows working on quantum photonics , neuromorphic computing , and photonic AI systems . His recent work includes photonic tensor cores for scientific computing , quantum photonic neural networks , and all-optical memory systems. Shastri Lab designs programmable nanophotonic processors with potential to outperform microelectronic processors in energy efficiency and computational speeds by seven and four orders of magnitude respectively. Their work spans from device design to system-level implementations in optical computing for machine learning and quantum information processing .

Juan Felipe Carrasquilla Álvarezمشاهده پروفایل

استادیار

• Condensed Matter Physics
• Quantum Computing
• Machine Learning
• +۳ مورد دیگر

Juan Felipe Carrasquilla Álvarez is an Assistant Professor in the Department of Physics at the University of Toronto. His research focuses on the intersection of condensed matter physics, quantum computing, and machine learning, emphasizing quantum many-body systems, quantum device validation, and phase identification. He holds affiliations with the Acceleration Consortium and the Centre for Quantum Information and Quantum Control at the University of Toronto, and is a Perimeter Institute Visiting Fellow. Education: PhD in Physics from SISSA (Italy), followed by postdoctoral fellowships at Georgetown University (2011-2013), the Perimeter Institute (2013-2016), and a stint as a Research Scientist at D-Wave Systems Inc. Earlier, he completed the Abdus Salam ICTP Diploma Programme (2005-2006). Research interests span quantum Monte Carlo simulations, machine learning-driven analysis of quantum systems, and applications to quantum computing validation. His work bridges theoretical physics with computational methods, addressing challenges in both classical and quantum computing paradigms. Notable contributions include developing neural network architectures for quantum state reconstruction, error mitigation in quantum simulations, and optimal control strategies for quantum thermal machines. His publications explore topics like topological order detection, shadow tomography, and hybrid quantum-classical algorithms. Awards/Fellowships: Perimeter Institute Postdoctoral Fellowship (2013-2016), Georgetown University Postdoctoral Fellowship (2011-2013), SISSA PhD Fellowship (2006-2010), and Abdus Salam ICTP Diploma Programme Fellowship (2005-2006). Advising/Grants: No formal advisee list provided. Active in interdisciplinary collaborations through affiliations with major quantum research consortia and institutions. Lab/Teams: Part of the Acceleration Consortium and the Centre for Quantum Information and Quantum Control, contributing to cutting-edge quantum computing and machine learning research.

Abbas Edalatمشاهده پروفایل

استاد

• Computer Science
• Mathematics
• Exact Computation
• +۷ مورد دیگر

Abbas Edalat is a Professor of Computer Science and Mathematics at Imperial College London, and an Adjunct Professor at the Institute for Research in Fundamental Sciences, Tehran. He leads two research groups: Algorithmic Human Development and Continuous Data-Types and Exact Computation. His work spans computational mathematics, psychotherapy models, and exact real-number computation. Notably, he received the LICS 2017 Test-of-Time Award for foundational contributions to logic in computer science. Research interests include self-attachment psychotherapy, computational differential calculus, topology, and bisimulation in probabilistic systems. He has pioneered exact computation frameworks for real numbers, geometry, and dynamical systems, with applications in neuroscience and artificial intelligence. Professional activities include keynote talks at conferences like IJCNN and workshops on psychotherapy in Iran and the UK. Teaching includes advanced courses on dynamical systems, quantum computing, and computational techniques. He advises PhD students globally and chairs initiatives like the Science and Arts Foundation to expand educational access in developing nations. His interdisciplinary work bridges mathematics, computer science, and clinical psychology.

• Space Physics
• Magnetospheric Dynamics
• Plasma Turbulence
• +۶ مورد دیگر

Brian Walsh is an Associate Professor of Mechanical Engineering at Boston University, with affiliations in the Departments of Astronomy and Electrical and Computer Engineering. He holds a Ph.D. in Mechanical Engineering from Boston University (2011) and a B.A. from Colgate University (2006). His research focuses on experimental space physics and spacecraft instrumentation, particularly studying solar wind-magnetosphere interactions, magnetopause reconnection, and X-ray imaging techniques. His work investigates energy transfer from the Sun to Earth's space environment, with a primary focus on the magnetopause. Walsh develops instruments for NASA and ESA missions, including the LEXI lunar X-ray imager and the CuPID CubeSat. He has contributed to missions like SMILE and pioneered compact solar energetic particle telescopes. His research spans CubeSat-based observations and large-scale space missions, emphasizing cross-scale coupling and global magnetospheric dynamics. Key research interests include plasma turbulence, magnetosheath dynamics, and exosphere variability. Walsh collaborates on projects like the Trans-Heliospheric Survey and the Magnetospheric Constellation (MagCon), aiming to advance understanding of heliospheric plasma behavior. His work also addresses space weather prediction and instrument calibration, such as the Carruthers Observatory Student Solar Monitor (COSSMo). Walsh's recent studies explore solar wind acceleration, ionospheric outflow asymmetry, and the role of recirculated plasmasphere material in ring current dynamics. His contributions to instrumentation and mission design highlight his dual role as a researcher and engineer in aerospace and space physics.

Bassam Bamiehمشاهده پروفایل

استاد

• Control Systems
• Dynamical Systems
• Quantum Control
• +۷ مورد دیگر

Bassam Bamieh is a Professor of Mechanical Engineering at the University of California, Santa Barbara (UCSB), with affiliate roles in Electrical and Computer Engineering and the Center for Control, Dynamical Systems and Computation (CCDC). His research focuses on control systems, dynamical systems, and their applications in fluid mechanics, quantum control, and network science. He holds fellowships from IEEE and IFAC and has received accolades such as the NSF Early Career Award and IEEE Distinguished Lecturer designation. Education: B.Sc. in Electrical Engineering and Physics from Valparaiso University (1983), M.Sc. and Ph.D. in Electrical and Computer Engineering from Rice University (1986, 1992). Formerly an Assistant Professor at the University of Illinois at Urbana-Champaign (1991–98). Research interests span robust and optimal control, distributed systems, shear flow turbulence, and thermoacoustic energy conversion. He has authored over 200 publications and pioneered work in spatially invariant systems and network controllability. His teaching includes courses on linear systems, vibrations, and control systems design. Awards include the IEEE Axelby Award (twice), Hugo Schuck Best Paper Award, and recognition for student research mentorship (e.g., Outstanding Student Paper Awards at CDC and IFAC NecSys22). His group collaborates across disciplines, integrating mathematical analysis with engineering applications.

Haiyang Xueمشاهده پروفایل

استادیار

• Cryptography
• Post-quantum cryptography
• Threshold cryptography
• +۵ مورد دیگر

Affiliations Full-time Assistant Professor of Computer Science at the School of Computing and Information Systems (SCIS) , Singapore Management University (SMU). Research focuses on cryptography, post-quantum systems, and secure protocols. Previously affiliated with PolyU for select teaching and collaborations. Education PhD in Computer Science, Chinese Academy of Sciences (2015). Research Interests Specializes in advanced cryptographic techniques including: Post-Quantum Cryptography (e.g., lattice-based systems) Threshold Cryptography (e.g., secure distributed ECDSA) Zero-Knowledge Proofs and Privacy-Preserving Technologies Authenticated Key Exchange (AKE) protocols Efficient implementations of cryptographic primitives (e.g., Kyber, NewHope) Notable Awards First Prize (LAC.PKE) and Second Prize (SIAKE, LAC.KEX) in Chinese Post-Quantum Cryptography Competition (2020) Best Paper Awards at IWSEC 2015 and ProvSec 2014 Advising & Collaborations Advises PhD students JIANG Bowen and WANG Jiaheng at SMU. Collaborates with researchers such as Guofeng Tang (post-doc) and international teams. Active in organizing conferences (e.g., CCS, ProvSec) and contributes to open-source projects like the Preprocess-then-NTT library. Labs & Teams Leads research initiatives at SMU focused on cryptographic protocol design and implementation. Collaborates with PolyU on advanced security projects.

• Compiler Optimization for High Performance Computing
• Optimization of Sparse/Dense Matrix/Tensor Computations
• Scalable Machine Learning
• +۱ مورد دیگر

P. (Saday) Sadayappan is a Professor in the School of Computing at the University of Utah. He serves as a lead researcher in high-performance computing, with a focus on compiler optimization and algorithm-architecture co-design. His current projects include NIH SBIR Phase 2 funding for large-scale image analysis and NSF grants for tensor applications and cyber-infrastructure for AI. Research Interests : Compiler Optimization for High Performance Computing Optimization of Sparse/Dense Matrix/Tensor Computations Scalable Machine Learning Algorithm-Architecture Co-Design Optimization Research Trends in Publications : His work emphasizes optimizing computational workflows for emerging hardware architectures, with a focus on accelerating machine learning and scientific computing through compiler-level innovations. Recent trends include co-design for CNNs, sparse matrix optimizations, and distributed algorithms. Scientific Awards : ACM SIGPLAN Most Influential PLDI Paper Award (2018) Grants & Projects : NSF (2022–2027): Comprehensive Framework for Tensor Applications NSF AI Institute ICICLE (2021–2026): Cyber-infrastructure for environmental AI NIH SBIR (2023–2025): Next-gen machine learning for image analysis Labs & Teams : Collaborates with institutions like Ohio State University and RNET Technologies on projects involving parallel computing, sparse algorithms, and compiler design.

Victor Galitskiمشاهده پروفایل

استاد

• Quantum Chaos
• Theoretical Physics
• Quantum Information Science
• +۷ مورد دیگر

Victor Galitski is a Professor of Physics at the University of Maryland and a Fellow of the Joint Quantum Institute (JQI). He holds two PhDs in applied mathematics and condensed matter physics, joined UMD in 2002 as a postdoc, and became a faculty member in 2005. His research focuses on theoretical physics and quantum information science, with notable contributions to quantum chaos, superconductivity, and topological materials. He co-founded Aspen Quantum Consulting and ScienceCast.org, and serves as an Honorary Professor at Monash University and an editor for Annals of Physics . Galitski’s educational efforts include authoring ' Exploring Quantum Mechanics ' (Oxford Press) and teaching a Coursera MOOC on quantum physics (enrolled by 200,000+ students). His research interests span quantum spin glasses, hydrodynamic turbulence, Floquet topological insulators, and cavity quantum electrodynamics. Over 20 former students and postdocs now hold academic or industry leadership roles. Key scientific contributions include studies on Many-Body Quantum Chaos, quantum spin ice in Rydberg atom arrays, and the interplay of symmetry breaking in vertex models. His work frequently explores connections between quantum systems and machine learning, such as neural networks’ analogies to spin glass behavior. Galitski’s affiliations include leadership roles in the Ultra-Quantum Matter Simons Collaboration, the Institute for Robust Quantum Simulation, and the Aspen Center for Physics. He has published extensively on topics like cavity-enhanced superconductivity and quantum ergodicity, with recent work addressing universal speed limits in quantum systems and interacting anomaly effects in thermal transport.