جست‌وجوی استاد و پژوهشگر

B Buchananمشاهده پروفایل

استاد

• Cryptography
• Cybersecurity
• Blockchain Technology
• +۵ مورد دیگر

Professor B Buchanan OBE FRSE is a Professor of Cryptography at the University of Edinburgh, based in Edinburgh. His research focuses on cryptography, cybersecurity, blockchain technology, quantum computing, and IoT security. He leads initiatives in post-quantum cryptography, secure IoT architectures, and privacy-preserving machine learning. His work spans theoretical developments and practical implementations, including frameworks for threat intelligence sharing and ethical AI integration in security systems. Research Interests: His core areas include cryptographic algorithm design, quantum-resistant protocols, machine learning in cybersecurity, and secure distributed systems. Recent projects explore homomorphic encryption for financial applications, GANs for anomaly detection, and blockchain frameworks for trust management. He is a vocal advocate for ethical cybersecurity practices and interdisciplinary collaboration. Scientific Awards: He has been awarded the OBE (Order of the British Empire) and is a Fellow of the Royal Society of Edinburgh (FRSE). These honors recognize his contributions to advancing cybersecurity and cryptography in both academic and industry contexts. Labs/Teams: His work is supported by the asecuritysite.com , a platform for cybersecurity research and analysis. Collaborations include EU initiatives on digital governance and industry partnerships in secure manufacturing.

Koutsopoulos Iordanisمشاهده پروفایل

استاد

• Federated Learning
• Explainable Artificial Intelligence
• Edge Computing
• +۳ مورد دیگر

Koutsopoulos Iordanis serves as a Professor in the Department of Informatics within the School of Information Sciences and Technology at Athens University of Economics and Business (AUEB). His office is located at 2, Troias, Kimolou & Spetson Str., 4th Floor, Office 402, with contact details including email jordan@aueb.gr and phone +30 210 - 8203 933. His research spans Federated Learning , Explainable AI for Healthcare , and Edge Computing Systems , with significant focus on the PRE-ACT project for breast cancer radiotherapy optimization. Key interests include energy efficiency algorithms, wireless networking, and AI deployment on resource-constrained devices. His work demonstrates strong interdisciplinary integration between computer science and clinical medicine. Recent publications reveal dominant trends in medical AI applications (particularly breast cancer treatment optimization), federated learning architectures for edge environments, and energy-aware systems . The PRE-ACT project constitutes a major research thrust, combining explainable AI with clinical radiotherapy decision support across multiple international institutions. He actively contributes to wireless networking research with emphasis on Software-Defined Networking (SDN) optimization, controller placement strategies, and tactical MANET implementations. His experimental work includes development of testbeds for federated learning on resource-constrained hardware.

Edmond Chowمشاهده پروفایل

استاد

• High-Performance Computing
• Scientific Computing
• Numerical Linear Algebra
• +۷ مورد دیگر

Edmond Chow is a Professor and Associate Chair in the School of Computational Science and Engineering at Georgia Institute of Technology. His research focuses on numerical methods, high-performance computing, and scientific computing applications in quantum chemistry, molecular dynamics, and machine learning. He holds awards including the 2009 ACM Gordon Bell Prize and 2002 PECASE. He leads the Intel Parallel Computing Center, advancing computational chemistry algorithms for Intel architectures. Education: Ph.D., Computer Science (minor in Aerospace Engineering), University of Minnesota, 1997 Honors B.A.Sc., Systems Design Engineering, University of Waterloo, 1993 Research Interests: Parallel algorithms for sparse linear systems and preconditioning High-performance quantum chemistry simulations Asynchronous iterative methods for extreme-scale computing Kernel-based methods and hierarchical matrices for Gaussian processes Applications in biological macromolecule dynamics and machine learning Awards & Recognition: ACM Gordon Bell Prize (2009) PECASE (2002) SIAM Fellow (2021) SC23 Test of Time Award Advising & Grants: Advised 11+ PhD/MSc students in numerical methods and HPC Funded by NSF, DOE, DARPA, and Intel Developed software tools like H2Pack (hierarchical matrices), GTFock (quantum chemistry), and Simint (electron integrals) Labs & Teams: Leads the Intel Parallel Computing Center and collaborates with institutions like LLNL, Sandia, and Temple University on asynchronous computing and quantum chemistry projects.

Ayres Freitasمشاهده پروفایل

استاد

• Theoretical Particle Physics
• Collider Physics
• Electroweak Symmetry Breaking
• +۳ مورد دیگر

Ayres Freitas is a Professor of Theoretical Particle Physics at the University of Pittsburgh's Department of Physics and Astronomy (Dietrich School). His research focuses on phenomenology of new particles and interactions at colliders, particularly exploring electroweak symmetry breaking mechanisms, beyond the Standard Model physics, and precision calculations in quantum field theory. He develops advanced computational tools like GRIFFIN and contributes to Monte Carlo methods for particle physics analyses. Recent teaching includes graduate courses such as Particle Astrophysics, Advanced Classical Electromagnetism, and Dynamical Systems. His work bridges collider physics with astrophysics/cosmology, especially in dark matter and ordinary matter origins. Collaborations include postdoctoral affiliates like Matthew Low and graduate students Jackson Wallace and Juhun Kwak. Freitas' research emphasizes precision analyses to reconstruct model frameworks from experimental data, with technical expertise in loop calculations and electroweak corrections. Current projects include probing dark sector fermions via Higgs precision studies and developing tools for future collider experiments like the LHC.

• Artificial Intelligence
• Data Science
• Social Network Analysis
• +۳ مورد دیگر

Marçal Mora Cantallops is a Visiting Professor at the Department of Computer Science, University of Alcalá. His research focuses on artificial intelligence, data science, social network analysis, and education technology. He holds a PhD from Universidad de Alcalá with a thesis on player experience in MOBA games (2018), supervised by Dr. Miguel Ángel Sicilia Urbán. His work bridges computational methods with societal applications, including healthcare innovation, digital transformation, and ethical AI education. Research Interests: Dr. Cantallops explores AI ethics, quantum computing applications, and the intersection of technology with culture and education. Notable themes include the preservation of gaming history, predictive analytics using social media (e.g., Twitter), and metacognitive scaffolding in e-learning. His studies often employ graph analytics and network analysis to uncover patterns in complex systems. Publications Trends: Recent work emphasizes trustworthy AI in healthcare, automated conversational agent design, and the role of Spanish innovation in retro gaming. Earlier research analyzed League of Legends player behavior and bacterial species modeling through clustering techniques. Awards: None explicitly mentioned in available texts. Grants & Advising: No specific grants or advisees listed. His contributions include collaborative projects with the I4 research group (Inteligencia, innovación, internet e información). Labs/Teams: Active member of the I4 research group at UAH, focusing on intelligence systems, internet studies, and information innovation.

Joel Davidssonمشاهده پروفایل

استادیار

• Quantum Technologies
• Semiconductors
• Point Defects
• +۳ مورد دیگر

Joel Davidsson is an Assistant Professor at Linköping University's Department of Physics, Chemistry and Biology (IFM), within the Theoretical Physics (TEOFY) division. His research focuses on identifying and characterizing point defects in semiconductors for quantum technologies, leveraging high-throughput computational methods. He leads the ADAQ Database Initiative, which provides open-access data on defect properties via automated workflows. Davidsson holds a Master's (2015) and PhD (2021) from Linköping University, specializing in orbital-free density-functional theory and quantum materials. His work emphasizes accelerating the discovery of defects suitable for quantum computing, single-photon emitters, and hybrid quantum systems. His research integrates First-principles calculations (DFT) Automated defect analysis (ADAQ platform) High-throughput screening of semiconductor defects Key projects include NV-like defect exploration in oxides and SiC, and developing symmetry analysis tools for defect orbitals. Collaborations involve teams at the University of Edinburgh and supercomputing facilities. His group includes PhD student William Stenlund and contributes to grants from WASP-WISE for sustainable materials research. Notable achievements include predicting MgO spin qubits, discovering telecom-wavelength emitters in 4H-SiC, and advancing defect database interoperability through initiatives like OMDI 2021.

• Materials Engineering
• Electrical and Electronic Engineering
• Condensed Matter Physics
• +۳ مورد دیگر

Dr Diego Alonso Alvarez is a Researcher and Head of the Research Software Engineering team at Imperial College London's Central Faculty. He joined in 2018 and leads the Grantham Institute RSE Team within Research Computing Services. His expertise includes software sustainability, accessibility, and GUI development for research software. Education: PhD in Semiconductor Nanostructures Postdoctoral Research in Solar Energy Concepts & Solar Cells Research Interests: Focus on advancing coding practices, software sustainability, and interdisciplinary applications in materials science and energy systems. Active contributor to projects like StrainMap, MUSE, and POWBAL. Awards: Software Sustainability Institute Fellow Advising/Grants: While no formal advisees are listed, his work spans collaborative projects funded by Imperial's Research Computing initiatives. He advocates for open-source methodologies to enhance reproducibility in research. Labs/Teams: Leads the central RSE Team and collaborates with the Grantham Institute, fostering innovation in computational tools for sustainability research.

David DiVincenzoمشاهده پروفایل

استاد

• Quantum Computing
• Superconducting Qubits
• Quantum Communication
• +۳ مورد دیگر

Prof. David DiVincenzo serves as Director of the Institute for Theoretical Nanoelectronics (PGI-2) and the JARA Institute for Quantum Information (PGI-11) at Forschungszentrum Jülich. His research focuses on quantum computing, superconducting qubits, quantum error correction, and many-body localization. He has contributed to foundational work on quantum hardware design, noise mitigation, and theoretical frameworks for scalable quantum systems. Key research themes include the development of superconducting qubit architectures, analysis of quantum chaos effects, and exploration of topological states in semiconductor materials. His work bridges theoretical insights with practical applications in quantum communication and fault-tolerant computing.

Peter Fletcherمشاهده پروفایل

مدرس

• STEM Education
• Place-Based Learning
• Outdoor Education
• +۱۲ مورد دیگر

Peter Fletcher is a Lecturer in STEM Education at the School of Education, University of New England, where he contributes to pre-service teacher education and digital learning initiatives. He holds a PhD in Physics Education from the University of Sydney and has extensive experience across primary, secondary, and tertiary education sectors in Australia and internationally. Doctor of Philosophy – University of Sydney Master of Science – University of Sydney Graduate Diploma in Education (Secondary) – University of Technology Sydney Bachelor of Education (Primary) – University of New England Bachelor of Science (Mathematics and Physics) – University of Sydney Graduate Diploma in Information Technology – University of New England Peter’s research centers on student-centered pedagogies, particularly place-based STEM education, outdoor learning, and the integration of science and technology in authentic community contexts. He advocates for interdisciplinary learning that connects students with nature, built environments, and Indigenous knowledge systems. His work emphasizes inquiry-based learning, inclusivity, and the use of digital tools to enhance engagement and self-regulation. His recent publications reflect a strong focus on online learning, teacher professional development, assessment innovation, and rural education. Themes across his work include equity in access, digital pedagogy, and the design of responsive learning environments. He frequently collaborates on projects supporting STEM outreach, astronomy education, and virtual learning systems. Citation for Outstanding Contributions to Student Learning, Australian Awards for University Teaching (2016) Citation for Outstanding Contribution to Student Learning, UNE Awards for Teaching Excellence (2016) Outstanding Paper Award, EdMedia Conference (2015) Vice-Chancellor’s Scholar, University of New England (2021) University of Sydney Research Scholarship (1999–2000) Peter has supervised multiple doctoral and master’s students in education and collaborated on significant research grants, including the ASELL in Schools project and the STEM Action Schools initiative. He has also contributed to national curriculum resources and professional development programs for rural teachers. He supports initiatives such as the Port Macquarie Astronomical Association and the New England Online Gifted and Talented program, demonstrating strong community engagement. He has led and participated in research teams focused on e-learning, physics education, and curriculum innovation. His academic service includes roles as Academic Integrity Officer and ICT Education Team Representative at UNE. He is a Fellow of the Royal Astronomical Society and actively promotes astronomy and technology education beyond the university.

• Formal Methods in Computer Science
• Cybersecurity
• Insider Threat Analysis
• +۴ مورد دیگر

Dr. Florian Kammueller is an Associate Professor in Software Engineering at Middlesex University , specializing in formal methods for cybersecurity and privacy. His research focuses on attack trees , GDPR compliance , insider threat modeling , and quantum cryptography using the Isabelle theorem prover. He has published extensively on formal verification of security protocols, privacy in IoT healthcare systems, and trust in AI. Recent publications emphasize federated learning , differential privacy , and distributed ledger security , often applying formal verification techniques to address regulatory and technical challenges. His work bridges theoretical computer science with practical applications in critical infrastructure security.

• Information Systems
• Grid Computing
• Data Storage
• +۵ مورد دیگر

Fokke Dijkstra is a Researcher at the University of Groningen , specializing in Information Systems , Grid Computing , and Petabyte-scale Data Storage . His work focuses on enabling large-scale scientific research through infrastructure development. Key Collaborations: Astro-WISE, LOFAR (Low-Frequency Array) projects Research Themes: Long-term archiving, distributed computing, and grid technology for astrophysics Recent Activity: Contributed to a memorial article for Joop van Lenthe in 2022 Academic Output includes 15+ publications on scaling data systems for astronomy, with notable work on LOFAR and Astro-WISE infrastructure. His research bridges computational methods with astrophysical data challenges. Activities include participation in the BioSB 2020 conference, demonstrating his interdisciplinary engagement.

Yu-Fang Chenمشاهده پروفایل

استاد پژوهشی

• Program verification
• Automata theory
• String constraint solving
• +۳ مورد دیگر

Yu-Fang Chen is a research professor at Academia Sinica, Taiwan, active across premier programming-languages venues such as PLDI, POPL, OOPSLA, SAS, APLAS and VMCAI. His work sits at the intersection of program verification , automata theory and constraint solving , with recent emphasis on quantum-circuit verification and string-number constraint solving . Research interests revolve around rigorous methods to ensure software reliability: developing novel automata models (level-synchronized tree automata, position-constrained string automata), building practical solvers that blend length, substring and numeric constraints, and extending automated reasoning to the quantum domain. His papers consistently introduce new decision procedures, learning algorithms and tool-chains that improve the scalability of static analysis and formal verification. Between 2017 and 2025 he (co-)authored more than a dozen peer-reviewed papers and served on over thirty program committees, including steering and organization chair roles for VMCAI 2026 and SAS 2023 . No doctoral students or funded-grant details are disclosed in the supplied sources.

• Tensor Decompositions
• Quantum Computing
• Fredholm Integral Equations
• +۷ مورد دیگر

Patrick Gelß is a Postdoctoral Researcher at Zuse Institute Berlin, working in the AI in Society, Science, and Technology department. He leads the iol.QUANT research group focused on quantum-inspired and tensor-based methods, with affiliations to Freie Universität Berlin and collaborative projects like MATH+ Cluster of Excellence. Diploma in Mathematics/Physics (2013, Freie Universität Berlin) PhD in Mathematics (2017, summa cum laude, Freie Universität Berlin) Postdoctoral roles at Zuse Institute Berlin (2020-present) and CRC 1114 (2017-2022) His research bridges tensor decompositions, quantum computing, and dynamical systems, with notable contributions to: Graph Isomorphism: Continuous optimization approaches via doubly stochastic matrices and Frank-Wolfe algorithms Quantum Simulation: Tensor network representations for quantum circuits and the open-source WaveTrain package KvN Mechanics: Mathematical analysis of existence/uniqueness solutions for bounded domains Fredholm Networks: Novel training paradigms for neural networks using integral equations Scientific achievements include: Developing Scikit-TT for tensor-train computations Organizing major workshops (QML@SC2024, TMQS 2024) Leading the Thematic Einstein Semester 2024 on Mathematics for Quantum Technologies His work spans chemical kinetics, quantum dynamics, and quantum machine learning, with applications to CO oxidation models, exciton-phonon systems, and mutational hierarchies in medicine.

Sebastian H. Trippelمشاهده پروفایل

پژوهشگر

• Molecular Physics
• Quantum Dynamics
• Laser-Matter Interaction
• +۳ مورد دیگر

Dr. Sebastian H. Trippel is a Team Leader at the Center for Free-Electron Laser Science (CFEL), part of Deutsches Elektronen-Synchrotron (DESY) in Hamburg, Germany. His research focuses on imaging chemical dynamics, particularly internal rearrangement processes of small molecules in the gas phase using advanced laser and imaging techniques. Education: Dissertation at Albert-Ludwigs-Universität Freiburg (2005-2010) Diploma at Albert-Ludwigs-Universität Freiburg (2003-2005) Dr. Trippel's research centers on quantum-state-selected molecules fixed in space with laser fields, studying processes like cis-trans isomerization and laser alignment dynamics. His work employs Coulomb explosion in combination with velocity-map imaging to probe molecular orientation and structural changes upon laser excitation. He specializes in ultrafast molecular dynamics and imaging techniques, with applications spanning atmospheric chemistry, radiation protection, and materials science. His recent publications demonstrate a strong focus on molecular beam injection systems, water dimer dynamics, polycyclic aromatic hydrocarbons, and advanced detector technologies like Timepix3. His research bridges physics, chemistry, and instrumentation, with significant contributions to understanding fundamental molecular processes through innovative experimental approaches. Dr. Trippel leads research efforts at CFEL/DESY, collaborating with numerous international partners across Europe. His team develops sophisticated experimental setups for molecular imaging and dynamics studies, contributing significantly to the field of ultrafast science and advancing capabilities at European x-ray free-electron laser facilities.

• Marketing
• Consumer Behavior
• Business Innovation
• +۵ مورد دیگر

Nora Rita Lado Couste is a Full Professor in the Department of Business Administration at Charles III University of Madrid. She leads the Research Group on Company Innovation, Organization and Marketing and is affiliated with the Institute for the Development of Enterprises and Markets (INDEM). Her research integrates marketing, economics, and information science, with emphasis on consumer behavior, innovation, and digital transformation in business contexts. Her work explores: Cross-cultural consumer psychology in co-branding strategies Technology adoption in service industries (e.g., robotics in hospitality) Semantic analysis of social media for marketing insights Market orientation in emerging economies Her publications show consistent focus on adaptive marketing strategies, with recent emphasis on technology-driven consumer interactions during global challenges like COVID-19 and financial crises. Research Projects: Principal researcher for 'Cátedra UC3M-Universia de Economía del Dato y la Inteligencia Artificial' (2024-2026) Led 'Estrategias de marketing y nuevos productos' project (MINECO, 2012-2014) Collaborated on Madrid's educational data innovation initiative (2018-2022) She supervised the thesis 'Three Essays on Social Media Marketing' (2019) and developed educational software 'Quantum: International Marketing Strategic Game'.