جست‌وجوی استاد و پژوهشگر

• Digital signal processing
• Wireless communications
• Signal processing
• +۳ مورد دیگر

Xiaodan Pang is a Tenure Professor at Riga Technical University (RTU) specializing in cutting-edge photonics and communications research. Her work focuses on developing next-generation optical and wireless technologies for high-speed data transmission systems, with significant contributions to silicon photonics, terahertz communications, and integrated sensing and communication architectures. Her primary research interests include: Digital signal processing Wireless communications Signal processing Fiber optics Optoelectronics Photonics Professor Pang's recent publications demonstrate leadership in overcoming fundamental challenges in high-speed communications. Her 2025 work spans silicon photonics ring-resonator modulators for optical-amplification-free links, photonic terahertz chaos systems for secure ranging, and analog fronthaul solutions for 6G networks. Key themes include neural network equalization for ultra-high baudrate transmission, energy-efficient unamplified optical links, and integrated sensing-communication systems leveraging terahertz frequencies. This research directly addresses critical bottlenecks in data center interconnects, 6G mobile infrastructure, and secure high-precision wireless applications. Her technical profile is documented through ORCID (0000-0003-4906-1704), Scopus (54407301300), and Web of Science (D-5032-2015) identifiers, with active professional engagement via LinkedIn.

Sriram Krishnamoorthyمشاهده پروفایل

استاد پژوهشی

• Parallel Programming Models
• Fault Tolerance
• High-Performance Computing
• +۶ مورد دیگر

Sriram Krishnamoorthy is a Research Professor at Washington State University's School of Electrical Engineering & Computer Science and a research scientist at Pacific Northwest National Laboratory (PNNL), where he serves as the System Software and Applications Team Leader in PNNL's High Performance Computing group. Dr. Krishnamoorthy earned his B.E. from the College of Engineering, Guindy in Chennai, India, and his M.S. and Ph.D. degrees from The Ohio State University. He is a senior member of the Institute of Electrical and Electronics Engineers. His research focuses on parallel programming models, fault tolerance, and compile-time/runtime optimizations for high-performance computing. He has made significant contributions in areas including: Fault tolerance techniques that minimize rollback during failures Dynamic load balancing for irregular parallel applications Compiler and runtime optimizations for HPC applications GPU programming and heterogeneous computing Quantum chemistry simulations and quantum computing Dr. Krishnamoorthy's publications span computational science, high-performance computing, and quantum chemistry. His recent work shows strong trends toward quantum computing applications, fault tolerance in large-scale systems, and optimization of computational chemistry methods. He has developed techniques for density matrix quantum circuit simulation, floating-point error analysis, and scalable execution of coupled-cluster models. His scientific achievements have been recognized with several prestigious awards: Best Paper Award at International Conference on High Performance Computing (HiPC'03) Best Paper Award at International Parallel and Distributed Processing Symposium (IPDPS'04) U.S. Department of Energy Early Career award (2013) PNNL's Ronald L. Brodzinski Award for Early Career Exceptional Achievement (2013) The Ohio State University's Outstanding Researcher award (2008) Dr. Krishnamoorthy has advised numerous graduate students and collaborated extensively with researchers across computational science domains. His work on the NWChem project demonstrates significant grant funding and large-scale collaborative research efforts in computational chemistry. He leads research efforts in PNNL's High Performance Computing group, focusing on system software and applications development for next-generation supercomputing platforms.

Zhenman Fangمشاهده پروفایل

دانشیار

• Hardware Acceleration
• Computer Architecture
• Big Data Computing
• +۷ مورد دیگر

Dr. Zhenman Fang is an Associate Professor in the School of Engineering Science (Computer Engineering Option) and Associate Member in the School of Computing Science at Simon Fraser University, Canada. He founded and directs the HiAccel Lab, focusing on accelerator-rich architectures. His PhD (2014) is from Fudan University, China, with 15 months spent at the University of Minnesota. Prior to SFU, he was a Staff Software Engineer at Xilinx (2017-2019) and a postdoc at UCLA (2014-2017). His research spans: Hardware acceleration for ML, big data, genomics, and HPC FPGA-based customizable computing and near-data processing Compiler/runtime systems for heterogeneous platforms Performance/reliability optimization of accelerator-rich systems His recent publications (2024-2025) focus on FPGA acceleration for machine learning (e.g., on-device training, quantization), computational chemistry, image/video compression, database systems, and reconfigurable computing, demonstrating cross-domain applications of specialized hardware. Awards & Honors: Best Paper Awards: FPL 2024, MEMSYS 2017, TCAD 2019 Best Paper Nominations: ICCAD 2025, FCCM 2025, HPCA 2017, ISPASS 2018 SFU Research Excellence Horizon Award (2025) NSERC Alliance, CFI JELF, and Xilinx University Awards He advises 20+ PhD/Master's students in HiAccel Lab, focusing on accelerator design. Major grants include NSERC Alliance (2020) and CFI JELF (2019). The lab operates a 10-node cluster with FPGA/GPU infrastructure.

Giacomo Nanniciniمشاهده پروفایل

دانشیار

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

Giacomo Nannicini is an Associate Professor in the Daniel J. Epstein Department of Industrial & Systems Engineering at the University of Southern California's School of Advanced Computing, with a courtesy appointment in the Ming Hsieh Department of Electrical & Computer Engineering. His research focuses on optimization broadly defined, with particular interests in algorithms, software, models of computation, and quantum computing applications. His research interests span optimization theory , quantum algorithms , computational methods , and mixed-integer programming . Nannicini has made significant contributions to both classical optimization techniques and emerging quantum computing approaches, developing algorithms that bridge theoretical foundations with practical applications in various domains. Nannicini has received numerous prestigious awards including the 2021 Beale–Orchard-Hays prize, the best paper award at IEEE QCE 2021 (quantum algorithms track), the 2016 COIN-OR Cup, the 2015 Robert Faure prize, and the 2012 Glover-Klingman prize. His publication record demonstrates consistent high-impact contributions across top journals in operations research, computer science, and quantum computing. He has successfully advised multiple PhD students who have gone on to prominent positions including research scientists at Saint-Gobain and SINTEF, as well as tenure-track faculty positions. Nannicini actively recruits PhD students interested in computational optimization, quantum optimization, GPU-enabled computational optimization, and mixed-integer derivative-free optimization.

Souravlas Stavrosمشاهده پروفایل

دانشیار

• Computer Networks
• Quantum Computing
• Computer Architecture
• +۳ مورد دیگر

Souravlas Stavros serves as an Associate Professor in the Department of Applied Informatics at the University of Macedonia, teaching core computer science courses including Communication Networks Modeling and Optimization, Computer Architecture, Computer Systems, Digital Design, Operating Systems, and Quantum Computing. His research spans critical domains in computational systems: Network optimization and modeling Quantum computing architectures Computer hardware design Operating system frameworks Digital circuit engineering Applied informatics systems With 26 books, 32 journal articles, and 20 conference publications, Dr. Stavros demonstrates extensive scholarly output in computer engineering fields. His active teaching roster and office contact details confirm ongoing academic engagement at the University of Macedonia.

Matthew B Stoneمشاهده پروفایل

استاد پژوهشی

• Neutron Scattering
• Quantum Materials
• Magnetic Materials
• +۳ مورد دیگر

Matthew B Stone is a Distinguished Scientist in the Neutron Scattering Division at Oak Ridge National Laboratory, serving as Lead Instrument Scientist for the SEQUOIA instrument at the Spallation Neutron Source since 2013. He previously served as ARCS Instrument Scientist (2007-2013) and was the Quantum Materials Initiative Coordinator from 2021-2024. His research focuses on applying inelastic neutron scattering techniques to study magnetic materials and quantum phenomena. Dr. Stone received his educational training at premier institutions: Ph.D. in Physics, Johns Hopkins University, 2002 M.A. in Physics, Johns Hopkins University, 2000 B.S. in Physics summa cum laude, Moravian College, 1996 His research expertise centers on the relationship between connectivity of magnetic ions in different geometrical lattices and the resulting quantum excitations. He specializes in inelastic neutron scattering techniques and develops new methods and hardware for improving measurements using direct geometry time-of-flight spectrometers. His work spans quantum magnetism, frustrated spin systems, and advanced materials characterization. Analysis of his recent publications reveals a strong focus on quantum magnetic phenomena in geometrically frustrated systems, particularly kagome and triangular lattices. His research increasingly examines the interplay between electronic structure, magnetic ordering, and quantum effects in novel materials, with applications in quantum computing and energy technologies. The publications demonstrate sophisticated use of neutron scattering to probe subtle quantum phenomena that are difficult to observe with other techniques. Dr. Stone has received numerous scientific recognitions: Multiple ORNL Performance and Supplemental Performance awards (2013-2021) Winner of the Director's award for Outstanding Team Accomplishment (2016) Elsevier Valued Reviewer (2016) R&D 100 award finalist for additive manufacturing of boron carbide (2019) Invited Early Career Scientist to X-rays and Neutrons conference (2005) He has been awarded ORNL Laboratory Directed Research and Development funding for projects including 'In-situ Neutron Scattering Studies of Fuel Cell Materials' (2010-2012). While the text doesn't explicitly mention students he has advised, his leadership role suggests significant mentorship responsibilities within his research group. Dr. Stone maintains an active role as a reviewer for prestigious journals including New Journal of Physics and Annals of Nuclear Energy. As Lead Scientist for SEQUOIA, a high-resolution direct geometry chopper spectrometer at the Spallation Neutron Source, Dr. Stone oversees a critical facility for quantum materials research. His work with the Quantum Materials Initiative coordinated research efforts across the Neutron Scattering Division, fostering collaborations that advance understanding of emergent quantum phenomena.

Dimitrios Simosمشاهده پروفایل

مدرس ارشد

• Cybersecurity
• Cryptography
• Security Testing
• +۵ مورد دیگر

Dimitrios Simos serves as Senior Lecturer and Joint Professor of Cybersecurity in the Department of Information Technologies and Digitalisation at Salzburg University of Applied Sciences (FH Salzburg), with an additional appointment as University Professor for Cybersecurity at the University of Salzburg where he teaches Introduction to Cryptography and IT Security. His research expertise includes: Resilient Security Testing and Web Technologies Security via Interaction Testing Protocol Security Testing for Internet and Industrial Systems Hardware Security with focus on Trojan Detection in Chips Quantum Software Security Implementations Combinatorial Mathematics for Secure Systems Engineering Dynamics Modeling of Natural and Cyber-Disasters Prof. Simos supervises Bachelor and Master students in cybersecurity and software/systems testing, cyberattacks, and mathematical security modeling. His teaching portfolio encompasses Cryptology, IT Security Engineering, Advanced Networking/Security/Privacy topics, and Attack-Defense Simulation labs across multiple degree programs.

Federico Holikمشاهده پروفایل

پژوهشگر ارشد

• Foundations of Quantum Mechanics
• Quantum Information Theory
• Quantum Logic
• +۳ مورد دیگر

Federico Holik serves as a Research Fellow at Argentina's National Scientific and Technical Research Council (CONICET) with primary affiliation to Vrije Universiteit Brussel (VUB) in Belgium. His institutional presence is anchored through VUB's CRIS profile and publications portal, reflecting active engagement in quantum research despite the absence of specified departmental or school affiliations within the university structure. His research program critically examines the logical, algebraic, and geometrical frameworks underpinning quantum mechanics, with concentrated efforts in quantum information theory and foundational probability interpretations. Key investigations include quantum resource management for NISQ-era devices, ontological indistinguishability of quantum entities, and the development of quantum mereology to address part-whole relationships in quantum systems. His interdisciplinary reach extends to quantum-inspired AI through quasi-set theory and epidemiological applications via information quantifiers in pandemic data analysis. Analysis of his 2023-2025 publications reveals two dominant trajectories: (1) practical quantum computing challenges centered on resource optimization, error mitigation, and software engineering frameworks for noisy hardware, and (2) deep foundational inquiries into quantum ontology, probability structures, and mereological paradoxes. This dual focus bridges theoretical rigor with emerging quantum technologies while maintaining strong connections to philosophical questions about quantum identity and agency.

Nat Tantivasadakarnمشاهده پروفایل

پژوهشگر ارشد

• Theoretical Physics
• Quantum Computing
• Topological Order
• +۴ مورد دیگر

Nat Tantivasadakarn is a Sherman Fairchild Postdoctoral Scholar and Research Associate in Theoretical Physics at the California Institute of Technology (Caltech), affiliated with the Division of Physics, Mathematics and Astronomy. His research focuses on topological phases of matter, quantum computing architectures, and non-Abelian anyon systems. He explores theoretical frameworks to engineer topological order through gauging procedures, symmetry-enriched phases, and measurement-based protocols. Research areas include non-invertible symmetries, fracton models, and fault-tolerant quantum computation leveraging topological codes. He investigates protocols for creating anyons in trapped ion systems and developing scalable quantum error correction strategies. His work bridges abstract algebraic structures (e.g., cohomology invariants) with experimental realizations in quantum hardware. Key contributions involve constructing tensor networks for higher-dimensional topological phases and analyzing Nishimori transitions in quantum circuits. His research also addresses the interplay between measurement-driven dynamics and long-range entanglement, particularly in symmetry-protected topological systems. Tantivasadakarn collaborates with institutions like the Institute for Quantum Information and Matter (IQIM) at Caltech. No scientific awards are explicitly listed. His advising roles and grant details remain unspecified in available texts.

• Neuroscience
• Molecular Biology
• Neurodevelopmental Disorders
• +۳ مورد دیگر

Hong Li is an Associate Research Scholar in the Department of Neuroscience at Yale University's Yale School of Medicine. Their research focuses on molecular mechanisms of cortical developmental malformations in neurodevelopmental and psychiatric disorders, employing animal models and integrative methodologies including molecular biology, genetics, morphology, and transcriptomics. Dr. Li holds a DPhil from the University of Helsinki (2007) and an MD from Anhui University (1997). Their work aims to advance understanding of neuropsychiatric diseases and develop therapeutic strategies. Educational Background: DPhil in Neuroscience, University of Helsinki (2007) MD, Anhui University (1997) Research Interests: Investigating molecular pathways underlying cortical development abnormalities, with emphasis on translational research to bridge basic science and clinical applications. Techniques include advanced genetic engineering, transcriptomic profiling, and cross-disciplinary approaches combining neuroscience and molecular biology. Advising & Grants: No specific grants or trainees listed in available materials, though their publications suggest collaborative research in quantum computing, embedded systems, and telecommunication networks. Recent work includes cross-domain contributions to quantum error correction systems and LLM-based robotic applications. Professional Contributions: Active in systems engineering, publishing on operating systems design, FPGA-based quantum decoders, and secure memory management. Their work bridges biomedical research with computational and hardware innovations.

Yang Linمشاهده پروفایل

پژوهشگر

• Machine Learning
• Intelligent Image Sensors
• Computer Vision
• +۵ مورد دیگر

Yang Lin is a doctoral assistant at the AQUA Lab within the School of Engineering at École Polytechnique Fédérale de Lausanne (EPFL). He works on integrating single-photon avalanche diodes (SPADs) with artificial and spiking neural networks for biological and medical imaging applications, particularly fluorescence lifetime imaging. Ph.D. in Computational and Quantitative Biology (expected 2025), École Polytechnique Fédérale de Lausanne B.Eng. in Automation (2020), Shanghai Jiao Tong University His research focuses on developing intelligent image sensors by combining SPAD technology with neural networks, including ASIC SPAD sensors, FPGA-based processing units, and optical setups for biomedical applications. He is exploring spiking neural networks (SNNs) for energy-efficient, real-time imaging with SPADs. Yang's recent publications highlight advancements in quantum ghost imaging, SPAD sensor integration with neural networks, and fluorescence lifetime imaging. He has presented at conferences like WACV 2024 and received recognition for his work at BMPN 2022. Best Talk of a Young Researcher, BMPN 2022 He designs hardware-software co-systems for biomedical imaging and is open to research or engineering roles post-2025.

• Digital Signal Processing (DSP)
• Field-Programmable Gate Arrays (FPGA)
• Machine Learning Hardware Acceleration
• +۱۳ مورد دیگر

Gian Carlo Cardarilli is a researcher specializing in digital hardware design and machine learning acceleration. His work focuses on FPGA implementations, Residue Number System (RNS) architectures, and reconfigurable computing for applications in wireless communication, edge AI, and fault-tolerant systems. Key collaborations with institutions like IEEE and ACM through publications. Active in translating theoretical algorithms into practical hardware solutions for real-time systems. Research interests include: Optimizing deep learning models for heterogeneous platforms. Developing radiation-hardened memory systems. Creating energy-efficient signal processing architectures. Advancing reconfigurable functional units for embedded processors. His article analyses span fields like Quantum Cellular Automata , Variable Fractional Delay Filters , and RNS-Based Position Estimation , reflecting a trend toward adaptive, low-power, and domain-specific hardware.

• Hardware Security
• Cryptography
• Side-Channel Attacks
• +۳ مورد دیگر

Elena Dubrova is a Professor at the Division of Electronics and Embedded Systems, KTH Royal Institute of Technology. She specializes in hardware security, cryptography, and embedded systems security. Her roles include examiner and course responsible for advanced degree projects in Computer Engineering, Communication Systems, Embedded Systems, and Machine Learning. She also teaches courses such as Design of Fault-Tolerant Systems, Hardware Security, and Internet Security and Privacy. Her research focuses on side-channel attacks, cryptographic algorithm vulnerabilities, and FPGA security. Notable work includes analyzing hardware security flaws in cryptographic implementations (e.g., CRYSTALS-Kyber, AES), RF signal leakage in chips, and mitigating threats in FPGA-based systems. Her contributions span both theoretical advancements and practical countermeasure development. Dr. Dubrova’s articles highlight trends in post-quantum cryptography vulnerabilities, machine learning-assisted security analysis, and the integration of physical unclonable functions (PUFs) for secure authentication. She emphasizes hardware-software co-design for robust security solutions. No scientific awards are explicitly listed in the provided information. Her work involves collaborative projects on cryptographic protocol design and secure embedded system architecture, though specific grants or lab affiliations are not detailed here.

• Cryptography
• Post-Quantum Cryptography
• Cryptographic Engineering
• +۴ مورد دیگر

Peter Schwabe is a scientific director at the Max Planck Institute for Security and Privacy (MPI-SP) and a part-time professor in the Digital Security Group at Radboud University, Nijmegen, The Netherlands. His primary research focuses on cryptographic engineering, particularly post-quantum cryptography, secure cryptographic implementations, and high-assurance systems. He holds a PhD from Eindhoven University of Technology (2011) and a Diplom in Computer Science from RWTH Aachen University (2006). His work includes leading projects like the ERC-funded EPOQUE project, which engineered post-quantum cryptographic standards. He contributed to NIST’s post-quantum cryptography standardization efforts, notably as a core developer of CRYSTALS-Kyber and CRYSTALS-Dilithium. His research spans lattice-based cryptography, code-based cryptography, and formal verification of cryptographic software. Publications highlight advancements in secure implementations against side-channel and speculative execution attacks, high-assurance cryptographic libraries (e.g., EasyCrypt), and practical post-quantum TLS protocols. Key contributions include optimizing cryptographic algorithms for embedded systems (ARM Cortex-M) and formal verification of KEMs like ML-KEM. Scientific awards include an ERC Starting Grant (2018). He advises numerous PhD students and collaborates with industry and academia on cryptographic standards and security. His labs focus on cryptographic engineering, with teams advancing both theoretical and applied aspects of post-quantum security.

Jennifer Paykinمشاهده پروفایل

پژوهشگر

• Programming Languages
• Quantum Computing
• Formal Verification
• +۷ مورد دیگر

Jennifer Paykin is a researcher affiliated with Intel and previously with Galois, Inc., actively contributing to programming languages and quantum computing since at least 2016. Her work bridges formal verification, quantum circuit design, and type theory, with notable papers on QWIRE, modal types, and higher-inductive quantum lambda calculus. Key affiliations: Intel (current), Galois, Inc. (past) Active in conference committees: PriSC , PLanQC , CoqPL , and TyDe Research interests span programming languages, quantum computing, formal verification, linear logic, and type systems. Her contributions include: Quantum circuit languages (QWIRE) Phantom type applications for quantum programs Modal types in quantum SDKs Formalizing quantum lambda calculus Secure compilation models Higher-inductive type frameworks Trends in publications show increasing focus on quantum software infrastructure (2016–2025), with recurring themes of type-driven quantum verification, circuit compilation, and logical foundations. Key collaborations include work on the SAW scripting language and flow equivalence models.