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Z. (Zeila) ZanolliView profile

Professor

• Quantum Materials Physics
• Condensed Matter Physics
• Density Functional Theory
• +7 more

Prof. Dr. Zeila Zanolli is a Full Professor in 'Theory and Simulations of Quantum Materials' at Utrecht University, leading the 'Quantum Materials by Design' research group. She holds affiliations with the Debye Institute for Nanomaterials Science and the Condensed Matter and Interfaces department. Her work focuses on first-principles modeling of nanoscale materials, particularly topological materials and applications in nanoelectronics/spintronic devices. She has pioneered superconducting Density Functional Theory implementations in SIESTA and contributed to understanding quantum transport phenomena like spin-polarized currents and photoluminescence dynamics. Education & Career: Prior to Utrecht, she was a Ramon y Cajal Fellow (ICN2, Spain) and led the Nanospintronics Group at RWTH Aachen University. Her academic trajectory includes a Marie Curie Fellowship at Forschungszentrum Jülich (2012–2015). She serves as Deputy Chair of the European Theoretical Spectroscopy Facility (ETSF) and holds editorial roles at SciPost Physics and Journal of Physics Materials. Research Interests: Her expertise spans quantum materials, topological matter, computational modeling (DFT, GW/BSE, NEGF), and materials discovery. Key systems include 2D materials, carbon nanostructures, hybrid organic-inorganic materials, and multiferroics. She emphasizes open-source software development (SIESTA, YAMBO) and open science practices. Awards & Recognition: Notable recognitions include the Marie Curie Intra-European Fellowship (2012–15), Ramon y Cajal Fellowship (2018–20), and Treasurer of the Young Academy of Europe (2018–22). She coordinates international initiatives like the MaX Center of Excellence for materials design at exascale computing levels. Teaching & Outreach: Teaches quantum mechanics, quantum transport, and materials theory at Utrecht. Organized graduate schools and international conferences. Engages in science policy, public outreach via videos (e.g., 'Quantum Materials by Design' YouTube channel), and editorial leadership to advance open access science.

Yi LuView profile

Professor

• Correlated Electron Systems
• Quantum Many-Body Systems
• Condensed Matter Physics
• +3 more

Yi Lu is a Professor in the Department of Physics at Nanjing University, specializing in correlated electron systems and the development of advanced numerical methods. His research focuses on quantum many-body problems, with contributions to computational tools like the Quanty package. He holds a Ph.D. from the Max Planck Institute for Solid State Research (Germany) and completed postdoctoral work at Heidelberg University’s Institute for Theoretical Physics. His work bridges theory and materials science, addressing superconductivity in nickelates and cuprates. Research interests include method development for quantum impurity solvers, tensor networks, and machine learning applications in physics. Recent studies explore electronic correlations in superconducting materials and the theoretical interpretation of experimental techniques like resonant inelastic X-ray scattering. Teaching includes leading courses on Group Theory and its applications in condensed matter physics. Advising focuses on graduate students interested in computational and theoretical approaches to correlated electron systems. No specific grants or awards are listed, though his contributions to the field are evident through his publication record and software development efforts. Labs/Teams: The Quanty quantum many-body computation package, developed in his group, provides accessible tools for modeling quantum systems with minimal programming expertise.

• Quantum Computing Theory
• Open Quantum Systems
• Quantum State Estimation
• +3 more

Lev S Bishop is a Researcher at IBM Research - Yorktown Heights specializing in quantum computing. His work focuses on theoretical aspects of quantum systems with applications in practical quantum computing architectures. Affiliated with IBM's Quantum Computing research division, he contributes to advancing the field through both theoretical frameworks and practical implementations. Dr. Bishop's research interests center on the theory of quantum computing, strong driving of open quantum systems, quantum state and process estimation and verification, and scalable architectures for quantum computing. His work bridges theoretical quantum mechanics with practical quantum computing implementation challenges. Through innovative approaches to quantum circuit design, error correction, and system calibration, he addresses fundamental obstacles in building practical quantum computers. Analysis of his recent publications reveals a consistent focus on quantum circuit optimization, error mitigation techniques, and quantum assembly language development. His research demonstrates particular expertise in quantum gate calibration, qubit mapping algorithms, and noise characterization in multi-qubit systems. The publications show increasing sophistication in handling quantum hardware constraints while maintaining computational fidelity. Dr. Bishop collaborates extensively within IBM's quantum research team, working alongside prominent researchers including Jay Gambetta (VP of Quantum, IBM Fellow), Petar Jurcevic (Staff Research Scientist), Arkopal Dutt (Research Scientist), and Alexander Ivrii (Researcher in Quantum Computing). His collaborative work spans theoretical developments and experimental implementations across IBM's quantum computing initiatives.

• Computer Architecture
• Quantum Computing
• Superconducting Electronics
• +5 more

Georgios Tzimpragos is an Assistant Professor in the Department of Computer Science and Engineering at the University of Michigan, College of Engineering. His research focuses on advanced hardware systems, including superconducting electronics, quantum computing, FPGA design, and energy-efficient architectures. He emphasizes independent student research leadership, with weekly one-on-one meetings and occasional lab visits. Students are expected to present progress in weekly group meetings using slide summaries. He actively supports internships, particularly during summer, and encourages teaching experiences via GSI roles. Research interests span superconducting circuits, temporal logic applications, and hardware acceleration for machine learning. Key venues include ISCA, ASPLOS, MICRO, and PLDI. Funding for conference participation prioritizes students with accepted papers, leveraging university and external resources. Vacations are respected, with one-month advance notice required except during critical deadlines. Publications emphasize novel circuit designs (e.g., clockless SfQ logic, superconducting memory) and tools like PyLSE for superconductor electronics. His group develops hardware instrumentation frameworks and explores low-power computing paradigms. No formal awards are listed, but contributions to Rackham-funded initiatives highlight collaborative research efforts.

Heinz RienerView profile

Researcher

• Logic Synthesis
• Formal Methods
• Computer-Aided Verification
• +4 more

Heinz Riener is a Researcher at the Integrated Systems Laboratory (LSI) within the School of Computer and Communication Sciences (IC) at EPFL, Lausanne, Switzerland. He holds a Ph.D. (Dr.-Ing.) in Computer Science from the University of Bremen, Germany. Previously, he worked at the German Aerospace Center (DLR) and the University of Bremen's Reliable Embedded Systems group. His research focuses on logic synthesis , formal methods , and computer-aided verification of hardware and software systems. Key areas include quantum computing (e.g., AQFP circuits), nanotechnology (e.g., RFET-based circuits), and emerging technologies like adiabatic quantum-flux parametron systems. Developed open-source tools like mockturtle and easy for logic synthesis and ESOP forms. Principal Investigator on projects like the Open Logic Synthesis Libraries initiative. Active in program committees for conferences like DAC, DATE, and FDL. Collaborates with institutions such as TU Graz, TU Hamburg, and UC Berkeley. His work emphasizes reproducibility and open-source collaboration in logic synthesis, contributing to benchmarks and libraries widely used in academia and industry.

Martina NibbiView profile

Researcher

• Quantum Computing
• Quantum Algorithms
• Quantum Simulation
• +4 more

Martina Nibbi is a Researcher and PhD candidate at the Technical University of Munich (TUM) within the TUM School of CIT , Department of Computer Science. Her work focuses on quantum algorithms, quantum chemistry, and quantum simulation of fermionic systems. She holds a B.Sc. and M.Sc. in Physics from Università degli Studi di Milano (2016–2022) and has conducted a visiting research stint at the Lawrence Berkeley National Laboratory in Spring 2025. Research Interests: Martina’s research explores quantum computing applications in chemistry and physics, including block encoding techniques for matrix product operators, tensor networks, and multiwavelet-based methods. She investigates computational methods to optimize wavefunctions and simulate fermionic systems at the complete basis set limit. Teaching: She contributes to courses such as Informatics for Engineering (C programming) and Advanced Concepts of Quantum Computing , spanning both lectures and seminars. Publications: Her recent work includes advancements in quantum algorithm design and computational methods, such as optimizing wavefunctions using multiwavelets and DMRG, and developing block encoding frameworks for matrix product operators. Supervised Work: Cecilie Priller (B.Sc. 2024): Computational complexity analysis of linear combination of unitaries block encoding Robert-Mihai Budai (M.Sc. 2024): Quantum algorithms using Lindbladian dissipation Defne Tolun (B.Sc. 2025): Complexity analysis of linear combination of unitaries in quantum chemistry

Fraser BrownView profile

Adjunct Professor

• Systems
• Programming Languages
• Security
• +3 more

Fraser Brown is a Courtesy Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University, affiliated with the College of Engineering. His research focuses on the intersection of systems, programming languages, and security, with particular emphasis on verified compilers, cryptographic applications, and finding vulnerabilities in real systems. He holds a position at the university's Pittsburgh campus located at 5000 Forbes Avenue. His research interests include compiler optimization verification, cryptographic protocol compilation, and secure execution environments. Notable projects involve verified components of browser JIT compilers and compilation infrastructure for cryptographic use cases. He has contributed to frameworks like WaVe (verifiably secure WebAssembly runtime) and Icarus (trustworthy JIT compilers). Recent publications (2021–2025) explore topics such as zero-knowledge proof compilers, secure MPC protocols, and microarchitectural vulnerability mitigation. His work frequently combines formal verification techniques with practical system implementations to enhance software and hardware security. Fraser has collaborated on grants like the SaTC-funded project on verified secure sandboxed systems. While no formal advisees are listed, his research contributions reflect collaborative efforts in academic and industrial contexts. His work is disseminated through venues like programming language and security workshops (e.g., PLAS 2023) and peer-reviewed journals/conferences.

Richard AnsorgeView profile

Senior Lecturer

• Medical Imaging
• Biophysics
• High-Performance Computing
• +5 more

Dr. Richard Ansorge is a Retired Senior Lecturer at the University of Cambridge and Fellow of Fitzwilliam College. He specializes in interdisciplinary research at the intersection of physics and life sciences, particularly in medical imaging technologies. His work focuses on advanced imaging modalities such as MRI/PET integration, dose calculation algorithms for proton therapy, and high-performance computing applications in medical imaging. Ansorge’s research interests include the physics of life, computational methods for medical imaging, and the development of novel imaging systems. He has contributed to advancements in PET/MRI co-registration, GPU-accelerated image processing, and radiation therapy optimization. His academic career has involved pioneering work in MRI signal theory, attenuation correction techniques, and small-animal imaging systems. Notable research trends in his publications emphasize the fusion of medical imaging modalities (e.g., PET/MRI), optimization of radiation delivery systems, and leveraging parallel computing (CUDA/GPU) for real-time medical applications. His work bridges fundamental physics principles with practical biomedical engineering solutions. Awards: No scientific awards explicitly mentioned in the provided texts. However, his contributions to medical imaging and particle therapy reflect significant impact in the field. Advising and grants: No specific student advisees or grant details provided. His research has likely been supported by institutional funding and collaborative projects at Cavendish Laboratory. Labs/Teams: Affiliated with the Cavendish Laboratory at the University of Cambridge, focusing on interdisciplinary physics and life sciences research.

Claire GmachlView profile

Professor

• Quantum Cascade Lasers
• Optics
• Semiconductor Engineering
• +3 more

Claire Gmachl is the Eugene Higgins Professor of Electrical Engineering at Princeton University, serving as the Associate Chair of the Department of Electrical and Computer Engineering and Head of Whitman College. She is affiliated with the High Meadows Environmental Institute (HMEI) as an Associated Faculty member and contributes to the Grand Challenges Program. Her roles emphasize leadership in both academic administration and cutting-edge research. Her research interests focus on quantum cascade lasers, optics, semiconductor engineering, and their applications in optical sensors for environmental and health monitoring. Notably, she explores hyperuniform semiconductor metamaterials, wireless power systems for lasers, and machine learning-driven approaches to optimize laser design. Recent work highlights advancements in mid-infrared spectroscopy for non-invasive glucose sensing and novel cavity geometries for laser stability and efficiency. Her research outputs demonstrate a strong emphasis on interdisciplinary innovation, particularly at the intersection of machine learning and optoelectronics. Articles from 2022-2025 reveal trends in developing robust quantum cascade laser systems and exploring their use in precision applications like medical diagnostics and environmental sensing. While no scientific awards are listed, her contributions to the field are evident through collaborations with HMEI and Whitman College. Her advising and grant activities are not explicitly detailed in the text. She leads research in labs focused on metamaterials, semiconductor lasers, and sensor technologies, contributing to both the School of Engineering and the broader university community through her administrative roles.

Todd MartinezView profile

Professor

• Theoretical Chemistry
• Photochemistry
• Mechanochemistry
• +3 more

Todd Martinez is the David Mulvane Ehrsam and Edward Curtis Franklin Professor of Chemistry and Professor of Photon Science at Stanford University, affiliated with SLAC National Accelerator Laboratory. His research focuses on theoretical and computational chemistry, with emphasis on photochemistry, mechanochemistry, and quantum mechanical methods. He earned his PhD in Chemistry from UCLA in 1994, followed by postdoctoral work at UCLA and the Hebrew University in Jerusalem before joining Stanford in 2009. His group develops novel simulation tools, including GPU-accelerated quantum chemistry software (e.g., TeraChem) and virtual reality interfaces (InteraChem and MolAR) for interactive molecular modeling. Key interests include predicting molecular behavior under light and mechanical force, designing self-healing materials, and advancing reaction discovery through first-principles methods. Awards include the MacArthur Fellowship and recognition as a Fellow of the American Academy of Arts and Sciences. Education: PhD in Chemistry (UCLA, 1994); Postdoctoral Studies at UCLA and Hebrew University (Jerusalem) Research Themes: Molecular modeling, excited-state dynamics, mechanochemical reactions, and computational tools Publications span ultrafast spectroscopy, quantum mechanical modeling, and algorithm development for large-scale simulations. The Martinez Group’s work bridges theory and application, aiming to make molecular design predictive and accessible through interdisciplinary collaborations.

Mamoun AlazabView profile

Professor

• Cyber Security
• Data Analytics
• Digital Forensics
• +7 more

Professor Mamoun Alazab is a full Professor and Inaugural Director of the NT Academic Centre for Cyber Security and Innovation (ACCI) at Charles Darwin University. His expertise spans cyber security, data analytics, and digital forensics with a focus on AI-driven solutions for cybercrime detection and privacy preservation. Research Interests: Malware authorship attribution, adversarial AI, access control systems in CPS/IoT, cyber criminology, and privacy-preserving machine learning. He has secured ~A$16.7M in research funding and published over 300 top-tier papers (90% in top 10% journals), 11 books, and holds 3 patents. Editorial Roles: IEEE Transactions on Computational Social Systems, ACM Digital Threats: Research and Practice Professional Activities: Founding Chair of IEEE NT Subsection, convened 200+ conferences Awards: Clarivate Highly Cited Researcher (2022), Top 2% Global Scientists (2020–2022), and multiple IEEE leadership awards. Labs/Teams: Leads ACCI, collaborates on projects like Cyber Territory Skills Hub and CVE: Countering Violent Extremism Research.

Stefaan HessmannView profile

Researcher

• Deep Learning
• Materials Science
• Quantum Chemistry
• +1 more

Stefaan Hessmann is a doctoral researcher at the Machine Learning Group within the Technical University of Berlin, affiliated with BIFOLD (Berlin Institute for the Foundations of Learning and Data). His research focuses on applying deep neural networks to materials science, particularly in quantum chemistry and generative models. He holds a Bachelor's degree in Physics from Technische Universität Dresden and an MSc in Computational Sciences from Freie Universität Berlin (2019). Education: - MSc in Computational Sciences, 2019: Freie Universität Berlin - BSc in Physics: Technische Universität Dresden Research Interests: Hessmann explores the intersection of machine learning and materials science, with emphasis on generative models for molecular design and quantum chemistry simulations. His work integrates deep learning techniques to address challenges in computational materials discovery and molecular dynamics. Research Trends: His publications highlight advancements in neural network-based approaches for crystal structure prediction, molecular relaxation via reverse diffusion, and inverse design of 3D molecular structures. His tools (e.g., SchNetPack 2.0) contribute to atomistic machine learning frameworks. Awards: No awards explicitly mentioned in the text. Advising & Grants: No student advisees or grant details provided. His research is likely supported through institutional affiliations. Labs/Teams: Active member of the Machine Learning Group at TU Berlin and BIFOLD, collaborating on foundational AI research in materials science.

Gabriel NiculescuView profile

Professor

• Nuclear Physics
• Particle Physics
• Detector Development
• +3 more

Dr. Gabriel Niculescu is a Professor of Physics & Astronomy at James Madison University (JMU) since 2003. His research focuses on experimental nuclear and particle physics, emphasizing detector technology development and hardware/software R&D. He collaborates with major institutions like Jefferson Lab (JLab), Fermilab, and Brookhaven National Laboratory (BNAL). Education: PhD in Nuclear and Particle Physics, Hampton University (1998) MS and BS in Applied Nuclear Physics, University of Bucharest, Romania (1991) His work bridges theoretical predictions with experimental validation, particularly in optimizing photomultiplier tube performance and exploring fundamental particle asymmetries. Research outputs include advancements in detector calibration methodologies and insights into quark distribution dynamics. Dr. Niculescu’s contributions to accelerator-based experiments underscore his commitment to advancing precision instrumentation in high-energy physics.

Sergio MartíView profile

Researcher

• Computational Chemistry
• Biochemistry
• Molecular Modeling
• +3 more

Sergio Martí is a Researcher at the Institute of Advanced Materials (INAM) of Jaume I University in Castelló, Spain, leading the Computational Biochemistry research group (RG9). His work focuses on developing computational methodologies to investigate biological systems, particularly enzyme mechanisms and therapeutic target validation. He earned his Chemistry degree (1997) and PhD in Chemistry (2002) from Jaume I University under Prof. Iñaki Tuñón and Prof. Vicent Moliner. His postdoctoral training spanned the University of Bath (UK), Institut de Biologie Structurale (France), Université Henri Poincaré (France), and the University of Minnesota (USA). Dr. Martí specializes in quantum mechanics/molecular mechanics (QM/MM) simulations to unravel enzyme catalysis mechanisms. His research targets neurodegenerative diseases (Alzheimer's via RgpB gingipain inhibition) and viral infections (SARS-CoV-2 Mpro inhibition), combining computational modeling with experimental validation. He has developed the QMCube (QM3) software suite for multiscale simulations. Recent publication trends reveal increasing focus on covalent drug design against therapeutic targets, with strong emphasis on reaction mechanism elucidation through advanced computational techniques. His work bridges fundamental enzymology and translational drug discovery. As part of INAM's training programs, Dr. Martí supervises PhD and Master's students in computational biochemistry. His research group utilizes high-performance computing infrastructure within IDIFEDER-INAM laboratories to model complex biomolecular systems. The Computational Biochemistry group (RG9) operates within INAM's interdisciplinary framework, collaborating across materials science and biotechnology domains while maintaining strong focus on methodological development for biological applications.

José Bacelar AlmeidaView profile

Assistant Professor

• Cryptography
• Information Security
• Program Verification
• +3 more

José Bacelar Almeida is an Assistant Professor at the Department of Informatics at Universidade do Minho and a Senior Researcher at HASLab/INESC TEC since 2011. He holds a PhD in Computer Science from Universidade do Minho (2003). His research focuses on Cryptography, Information Security, and Program Verification, with an emphasis on formal methods for ensuring cryptographic software correctness and security. He has contributed to high-assurance implementations of cryptographic systems, bridging theoretical security with real-world applications. His research interests include provable security, formal verification of cryptographic proofs, and secure cryptographic software implementations. Notable work includes formally verified implementations of Kyber (a post-quantum cryptosystem) and machine-checked proofs for security protocols like ML-KEM. He also explores leakage-free probabilistic programs and secure compilation frameworks. Almeida has supervised multiple theses on topics such as cryptographic implementation verification, cloud security, and password management systems. His publications span conferences like CRYPTO and CPP, journals like the Journal of Logical and Algebraic Methods in Programming, and venues on formal methods and secure computation. He is part of the High-Assurance Software research center at INESC TEC and actively contributes to projects involving certified cryptographic software and secure multiparty computation. His work emphasizes practical, high-performance solutions with rigorous formal guarantees.